Fast Company Technology

While U.S. companies continue to dominate global news, these companies are solving problems abroad. The three honorees, from diverse industries, are addressing specific challenges in the markets they serve: reducing drag on boats, helping ranchers manage livestock, and improving customer interactions. Each company is applying new technology to a practical problem in the market where it operates.

Halter
For giving ranchers a high-tech solution to manage their livestock
Livestock ranching has traditionally relied on labor-intensive work. Halter is making it easier for ranchers to manage livestock, helping them track elements like grazing systems and herd movement while relying less on physical infrastructure. This is especially important as the effects of climate change increase and ranchers need to develop solutions for more sustainable food production.

Synthesia
For using AI to improve customer interactions
Synthesia makes AI avatars that help employees practice interactions, including role-play scenarios like handling issues during sales calls. Employees then receive feedback, while the software tracks their skills progression. A USC study found AI avatars statistically equivalent to human presenters in terms of message impact. The company raised a $200 million Series E at a $4 billion valuation.

Vessev
For creating technology that reduces drag on boats
Vessev makes electric boats that move people across the water more efficiently by adding carbon-fiber underwater wings called hydrofoils, which lift the hull above the water as the boat moves, cutting down on drag. The company’s technology is used by ferries and in the tourism industry to give riders a more comfortable alternative to typical passenger boats.

The companies and individuals behind these technologies are among the honorees in Fast Company’s Next Big Things in Tech awards for 2026. Read more about the winners across all categories and the methodology behind the selection process.

As these honorees show, the future of medicine is looking more and more . . . futuristic. They include AI that diagnoses more than a dozen serious conditions from a single abdominal scan, a sci-fi-worthy clinic that reimagines the preventive care model, and a psychedelic that tackles treatment-resistant depression with a synthetic version of a Sonoran Desert toad secretion. Need help with paying rising out-of-pocket medical costs? There’s even a solution for that.

Aidoc
For massively streamlining the interpretation of medical imaging 
Roughly one in four adults will need medical imaging this year, creating a daunting caseload for radiologists who interpret the scans. AI can help, but most tools assess single conditions, resulting in diagnostic blind spots and critical care delays. Aidoc’s operating system for clinical radiology, called aiOS, consolidates these separate workflows. In January 2026, the FDA cleared Aidoc’s comprehensive abdomen CT triage tool, which can diagnose 15 acute conditions—including appendicitis, aortic dissection, and bowel obstruction—from a single scan. With a total of 30-plus FDA-cleared algorithms to date—spanning cardiology, oncology, and vascular conditions—Aidoc has analyzed more than 120 million patient cases at over 1,600 hospitals and raised more than $500 million to date. In August, the company announced the creation of the Diagnostic AI Consortium, in which a dozen of the largest hospitals and health systems in the U.S. will develop standards for AI usage in clinical decision-making. 

Akido
For expanding healthcare capacity through improved teamwork 
Akido‘s ScopeAI clinical automation platform expands the effectiveness of  multidisciplinary care teams by enabling nonmedically trained outreach workers to begin patient intake and diagnosis before a doctor is available. Trained on more than 10 million real-world clinical encounters, it listens to patient interviews on a tablet or laptop and suggests follow-up questions. An initial diagnosis and treatment plan is then sent to a physician to sign off on or modify. In Akido’s street medicine program in Los Angeles, ScopeAI enabled provider teams to double the number of patients they could serve, driving a 55% reduction in emergency department visits and achieving 82% retention at three months in a population with traditionally high dropout rates. The company has expanded into clinics in Rhode Island and New York, including a chronic-disease management program for New York City rideshare drivers. Akido now serves 500,000 patients annually across nearly 100 clinics and 26 specialties. 

AtaiBeckley
For bringing next-generation psychedelics into the mainstream
In July, Eli Lilly announced it would acquire AtaiBeckley in a deal worth up to $3.8 billion—a major validation of a pioneer in regulated psychedelic therapies. Its lead asset, BPL-003 (mebufotenin benzoate), is a nasal spray based on a compound found in the defensive secretions of the Sonoran Desert toad. After early studies showed substantial improvement over existing approaches to treatment-resistant depression, the FDA granted BPL-003 Breakthrough Therapy Designation in October 2025. The spray could shrink clinical visits to about two hours, versus six to eight hours for first-generation therapies based on psilocybin. With phase 3 trials initiated in June 2026, the drug could become the first next-generation psychedelic medicine to obtain FDA approval.

Axoft
For developing a more brain-friendly brain-computer interface
Made from a bio-inspired material called Fleuron that mimics the soft tissues of the brain, Axoft‘s minimally invasive brain-computer interface (BCI) can be surgically implanted through two tiny holes in the skull. With 32 times more sensors per thread than current flexible probes and 60% less signal loss than BCIs made from conventional polyimide, it gives high-resolution access to neural activity not available through traditional exams or external imaging. Because it can be safely implanted in any brain region, including previously unreachable deep areas, Axoft’s device is uniquely suited to evaluating patients in a coma or vegetative state. The device has been implanted in 11 patients so far across three clinical sites, including Mass General Brigham.

Neko Health
For making the annual physical fast—and kind of fun 
Cofounded by Spotify founder Daniel Ek and Hjalmar Nilsonne, Neko Health is reinventing preventive healthcare through a growing network of spa-like clinics offering a comprehensive health assessment in one hour. Combining data from its proprietary Dermascan imaging device, biometric measurements, blood testing, advanced sensor readings, and a consultation with a human physician, the Neko Health exam identifies early indicators of cardiovascular disease, metabolic conditions, circulation issues, and skin cancers. The company has opened two clinics in Sweden, six in London, and one in New York City. Neko Health has raised over $1 billion to fund growth, including a $700 million funding round this July.

Paytient
For making out-of-pocket health costs more manageable
Americans spent $98 billion out of pocket on medications in 2024, a cumulative 25% increase over five years, according to analytics firm IQVIA. Paytient’s healthcare affordability platform, which is typically underwritten by employers, acts like an interest-free line of credit to help people pay for things that health insurance doesn’t, including copays, coinsurance, and deductibles. Members get a Paytient card that pays providers in full up front, then repay over time via payroll deduction, bank account, or HSA/FSA. The company now serves more than 26 million members and partners with nearly 7,000 employers, insurers, and providers. In 2026, Paytient expanded into pharmacy benefits, partnering with GoodRx and Cost Plus Drugs and adding transparent drug pricing to its app.

SetPoint Medical
For easing rheumatoid arthritis pain without pills 
SetPoint Medical‘s is the first FDA-approved neuroimmune modulation device for rheumatoid arthritis. The multivitamin-size wireless neurostimulator is implanted on the vagus nerve and delivers a daily one-minute electrical signal to regulate inflammation without drugs. In a trial of 242 patients with RA, 75% of participants managed their symptoms with SetPoint alone at 12 months. Since the FDA nod in July 2025, adoption has accelerated—the therapy is now available in six markets, with expansion planned in up to 30 new cities by the end of 2026. In April 2026, the company began enrollment for a pilot study evaluating the device as a potential therapy for relapsing multiple sclerosis.

The companies and individuals behind these technologies are among the honorees in Fast Company’s Next Big Things in Tech awards for 2026. Read more about the winners across all categories and the methodology behind the selection process.

AI innovation may feel like it’s utterly dominated by a few giants, but the reality couldn’t be more different. These honorees have thrived by zeroing in on specific challenges, including teaching the technology to interpret sensor data, speeding up inference, and giving researchers better insight into how models actually work.

Archetype AI
For turning sensor data into intelligence
Large language models may know a lot, but because they have been trained on text and images, that limits their understanding of our world. By contrast, Archetype AI’s Newton foundation model can interpret data from cameras, lidar, radar, inertial measurement units, and other sensors used in enterprise domains such as construction, logistics, manufacturing, and urban planning. Customers ranging from the city of Bellevue, Washington, to data services firm NTT Data to construction giant Kajima Corporation have adopted the model, which outperforms the major general-purpose LLMs on sensor-related tasks.

Cerebras Systems
For putting inference’s pedal to the metal
If you’ve ever asked AI to do something and then drummed your fingers waiting for it to respond, you’ve run up against slow inference. To pick up the pace, Cerebras developed its own inference platform from the semiconductor wafer up. In January 2026, the company unveiled a partnership with OpenAI to launch a 750-megawatt deployment of its technology. Two months later, it announced that its systems had been deployed in Amazon’s AWS data centers. It’s also working with AWS on an AI architecture that pairs the companies’ technologies to quintuple a hardware footprint’s token capacity.

d-Matrix
For powering real-time AI
In June 2026, d-Matrix’s Corsair AI platform entered full production. It reduces typical latency inherent to AI by placing compute and memory alongside each other, an approach that an independent benchmark showed slashing AI response time to 2 seconds from 24 seconds. The company’s investors including Microsoft, SK Hynix, and Samsung, along with the Qatar Investment Authority and Singapore’s EDBI.

Goodfire
For taking the mystery out of models
Silico, Goodfire’s AI development and interpretability platform, is designed to overcome AI models’ notoriously opaque nature. It allows researchers to examine the innards of a model, make precision adjustments, and steer its behavior in ways that might otherwise be impossible. Mayo Clinic adopted Silico to catalog 4.2 million genetic variants and predict their likelihood of causing disease. Rakuten used it to excise sensitive data from its agent platform with better performance and dramatically lower cost than typical approaches.

Liquid AI
For helping AI think small
AI running at massive scale in data centers gets most of the industry’s attention. Liquid AI’s LFM2.5 is a set of AI models optimized to run on processors in laptops, smartphones, vehicles, and IoT devices—no internet connection necessary. Instead of being based on transformers like a conventional model, each one is customized by Liquid AI’s own meta-AI system to operate within specific processor and memory constraints. Chipmakers AMD, Intel, and Qualcomm are shipping LFM2.5 versions for their respective platforms. Last April, Liquid AI also signed a multiyear deal with Mercedes-Benz to embed the technology directly into vehicles.

Merge
For plugging enterprise AI into the real world
Released in October 2025, Merge’s Agent Handler lets organizations use AI to unlock the value of data that lives in their essential applications. Instead of engineering teams having to wire up Model Context Protocol (MCP) connections themselves, they can use Merge’s library, which covers of hundreds of enterprise tools, such as Salesforce, Workday, Gmail, and GitHub. These connectors are prebuilt and designed with security and observability in mind. Some 1,700 paying customers call on the platform for more than 1.1 billion daily API requests; it also powers Perplexity’s Enterprise Pro service.

Runpod
For delivering AI infrastructure as a service
Runpod is a cloud provider focused entirely on helping organizations train and deploy fast, reliable AI without having to invest in GPU hardware or manage it on their own. Its platform provides access to more than 30 Nvidia and AMD GPU models in 31 global regions and offers proprietary technologies such as FlashBoot, which speeds inference by cutting cold-start times to under 200 milliseconds. The company says it’s passed $120 million in annual recurring revenue from more than 1 million customers.

The companies and individuals behind these technologies are among the honorees in Fast Company’s Next Big Things in Tech awards for 2026. Read more about the winners across all categories and the methodology behind the selection process.

Climate change is making food harder to produce, even as agriculture remains a major source of emissions. At the same time, farmers are contending with labor shortages, rising costs, and pressure to get more out of every acre. New technologies are helping them do that, from robotic beekeeping and AI systems that reduce crop loss and pesticide use to tools that identify the genes behind more resilient crops.

Beewise
For automating beekeeping at scale
For commercial beekeepers, keeping tabs on thousands of hives across miles of farmland is a challenge. A hive can develop a health problem without anyone noticing, simply because it’s not physically possible to visit every hive often enough. ROBI, Beewise‘s solar-powered robotic beekeeper, is designed to help by autonomously moving down flexible rails that sit between rows of beehives. It captures images of each frame in a hive so software can analyze colony health. It can also feed bees and treat disease as needed. Some of the largest pollination providers in the U.S. are now beginning to roll it out.

Farmwave
For using AI to reduce crop loss
Farmers harvesting crops such as corn and soybeans can lose tens of thousands of dollars in produce because tractors struggle to adapt to varying field conditions, leaving portions of the crop unharvested. Farmwave uses cameras and AI to track grain loss in real time so farmers can adjust tractor settings, reducing loss by three to eight bushels per acre. The tech runs on Dell’s Pro Rugged tablets, designed to work in dusty, demanding field conditions. Thousands of images captured by the AI system each day are processed directly on the device, allowing the technology to work in areas with limited or no Wi-Fi connectivity.

Heritable Agriculture
For finding the genes behind better crops
Conventional plant breeding is slow—scientists can spend as long as ten years just figuring out which gene matters for a particular trait. Heritable Agriculture uses AI to identify key genes in 14 to 18 months. The startup spun out of X, Alphabet’s “Moonshot Factory,” in 2024 after five years of research. It uses deep learning and large language models to analyze plant data, including DNA and proteins, alongside environmental data on soil and water to help develop crops optimized for a particular location and adapted for climate change. In one project backed by the Gates Foundation, Heritable is developing drought- and heat-tolerant crops for sub-Saharan Africa.

Verdant Robotics
For slashing pesticide use with AI
Verdant Robotics’s SharpShooter technology, mounted on tractors, uses AI to aim herbicide directly at weeds and not at crops, reducing herbicide use by as much as 99%. The system builds a live digital twin of the field, including every crop plant and weed, and it targets unwanted plants with millimeter-level accuracy. Farms can save hundreds of thousands of dollars on labor and roll out treatment at the moments it’s most useful, something that’s challenging with current labor shortages. The payback period is between six and 18 months. In one study, yield at early harvest more than doubled.

The companies and individuals behind these technologies are among the honorees in Fast Company’s Next Big Things in Tech awards for 2026. Read more about the winners across all categories and the methodology behind the selection process.

Fintech and blockchain technology has seen its fair share of boom and bust cycles in the past decade, from the cryptocurrency explosion during the COVID pandemic to the AI era launched by ChatGPT. But the tech has continued to evolve in step with it all, and the work being done in this space is exciting—from companies that are challenging social norms to those that are betting on futuristic visions.

Mesh
For connecting crypto’s fragmented payment ecosystem
Even as cryptocurrency matures, a pain point for consumers remains: The system is fragmented by design. Hundreds of different blockchains, digital wallets, exchanges, and payment platforms exist as islands on their own. That may be frustrating for the more than 900 million global crypto users—who made over $27 trillion in transactions with stablecoins alone this year—as moving money around often requires custom engineering. Mesh bridges the islands. It built a layer of infrastructure that links wallets, exchanges, and platforms at a single point, turning a cacophony into a harmonious orchestration—a shopper in Lagos could pay in Bitcoin, Solana, or any other token owned, and a merchant in Manila could instantly settle in USDC, dollars, euros, yen, or any currency preferred. With Mesh, those conversions are automatic rather than manual. The company stands as a neutral party—it does not mint tokens, run a trading desk, or hold custody itself—and bills itself as future-proof for the age of AI agents, even giving a live demo of an AI-driven e-commerce transaction at Singapore’s TOKEN2049. In January, Mesh raised $75 million in funding at a $1 billion valuation. It powers crypto payments for PayPal and Kalshi, and partnered with Google for the emerging autonomous payments economy.

Seon
For making fraud intelligence portable across AI models
AI might enable more fraud, but Seon is enabling more fraud protection across AI bots. In June, the company released a fraud detection and anti-money-laundering tool that can be freely layered onto any existing AI model—from Anthropic’s Claude to OpenAI’s ChatGPT to Google’s Gemini. That’s in stark contrast to other fraud tools on the market, which lock customers into proprietary experiences that don’t talk to each other. According to Seon, companies often stack those disconnected tools—one for identity checks, one for activity monitoring, et cetera. But Seon’s “portable intelligence layer,” or “Model Context Protocol,” sends its 900 real-time signals to any AI, allowing it to seamlessly reference them across the full user journey. And that makes fraud detection more effective—for example, it could catch criminal rings by flagging clusters of activity that only seem suspicious when put together versus being viewed in isolation. Seon processes 15 million transactions daily and is used by more than 5,000 businesses globally across fintech, retail, and gaming, including Afterpay, Bally’s, and Tecovas. It helped a top fast-casual restaurant chain across North America, Europe, and the Middle East cut fraud by 40%. In 2025, it grew its annual recurring revenue by 80%, from new customers and deeper adoption.

Wealth.com
For bringing estate planning into the digital age
Nearly 3 in 4 Americans regard estate planning as important—yet simultaneously, nearly 3 in 4 Americans lack even a basic estate plan, according to Caring.com. That’s begotten unfortunate consequences: More than half (58%) of families have squabbled over inheritances after a death in the absence of a proper estate plan—which has, counterproductively, locked up that wealth for months if not years, InvestmentNews reports. Why don’t Americans plan for post-mortem? Studies suggest it’s a combination of confusion about the process, concerns that it will be too costly, and the belief that they don’t have enough net worth to justify an estate plan. But with new AI technology that cuts expensive attorneys and lengthy paperwork out of the equation, Wealth.com is hoping to de-frictionize the process. Its engineering teams leveraged artificial intelligence to translate thousands of pages of state-specific legislation and factor in decades of estate-planning logic, creating a platform that can walk clients in all 50 states (plus Washington, D.C.) through the whole journey, end to end. It claims that what once took months can now be done in 30 minutes. Since its founding in 2021, Wealth.com has delivered 100,000-plus estate plans and is used by 5 out of 7 of the nation’s largest private banks, representing more than $15 trillion in client assets. Following four consecutive years of over 300% revenue growth, in 2026, the company raised $65 million from Google Ventures, Charles Schwab, Citi Ventures, and other investors.

The companies and individuals behind these technologies are among the honorees in Fast Company’s Next Big Things in Tech awards for 2026. Read more about the winners across all categories and the methodology behind the selection process.

Some innovations have potential beyond the bounds of a single industry. These honorees include a company that is combining AI and advanced genetic life science to better track disease pathology, and another developing models that could help avoid animal testing by simulating human organ functions. 

Algen Biotechnologies
For blending genetics and AI to advance pathology
One of the most promising health applications for AI is earlier identification of genes that can be targeted by therapies to reverse disease processes. Spun out of Nobel Laureate Jennifer Doudna’s lab, Algen is the creator of AlgenBrain. It uses CRISPR and AI to better understand disease biology and accelerate next-generation approaches. The system maps causal links between gene regulation and disease progression, going beyond data analysis to generate solutions. The company recently announced a $555 million partnership with AstraZeneca to develop AI-powered drug discovery, giving Algen access to the pharmaceutical giant’s immunology pipeline.

Emulate
For developing human organ simulators that can supplant animal testing
Organ-on-a-Chip technology from Emulate uses microfluidic devices containing human cells to replicate key aspects of human organ functions. That offers more relevant data for modeling—for example, drug reactions—than traditional 2D cell culture models. Emulate’s next-generation platform focuses on scalability, attacking the high-cost and labor-intensive workflows that its first systems required. The company’s Human Liver Chip is in the final stages of the FDA’s ISTAND qualification program, which could enable it to partially replace animal testing in regulatory submissions for pharmaceuticals.

The companies and individuals behind these technologies are among the honorees in Fast Company’s Next Big Things in Tech awards for 2026. Read more about the winners across all categories and the methodology behind the selection process.

As companies emerge from early startup stage, pressure mounts to focus on execution. But they must also have an eye toward opportunities to improve, expand, and serve evolving marketplace needs. This year’s honorees have used AI to streamline and automate common back-office tasks, help companies meet mission-critical requirements, and serve doctors and mothers by more precisely determining pregnancy due dates.

Rippling
For teaching AI “that’s how we do things here“
The more AI understands about our work, the better it can help us navigate and perform tasks in that world. Rippling is a platform focused on streamlining and automating many of the administrative tasks in areas such as HR, IT, and finance. Its agentic prowess stems from having access to the native data structures, context, and controls defined within a company. That creates outputs that reflect the actual state of a business, helping humans in these roles focus on more strategic tasks. The company, which largely serves mid-market customers, recently crossed $1 billion in annual recurring revenue and raised $450 million at a $16.8 billion valuation. 

Seekr
For bringing AI to mission-critical tasks
While many organizations are piloting AI across a range of jobs, the vagaries around its operation have kept it out of many mission-critical applications. Seekr’s SeekrFlow aims to change that with an end-to-end AI platform for creating, deploying, and managing LLMs using an organization’s own data. Designed for enterprises, government agencies, defense organizations, and regulated industries, it addresses challenges around such issues as data quality and oversight via high-quality AI datasets and domain-specific models and agents. Earlier this year, the company partnered with General Dynamics Information Technology to build agentic AI solutions for federal agencies. It’s available now on AWS GovCloud.

Ultrasound AI
For delivering more accurate pregnancy due dates
For hospital staff, an expectant mother’s due date is key to a range of obstetric care decisions, such as how to time an induction or cesarean or when to prepare for a potential high-risk birth. Predictions made via traditional means can be off by more than two weeks. Ultrasound AI‘s Delivery Date AI (DDAI) replaces the manual formula measurements with one derived from analysis of a standard ultrasound image in less than a minute, creating a more accurate delivery date prediction. In February, Ultrasound AI received FDA De Novo clearance for DDAI tech, paving the way for broader adoption.

The companies and individuals behind these technologies are among the honorees in Fast Company’s Next Big Things in Tech awards for 2026. Read more about the winners across all categories and the methodology behind the selection process.

Large companies have scale, but scale can also make change difficult. This year’s enterprise-size honorees show what happens when established organizations use new technology to rethink core operations, from hiring tens of thousands of workers to managing sprawling retail networks. Their innovations are notable not just for what they do but for how widely they can be deployed.

Albertsons Companies
For putting AI to work across the grocery business
Rather than deploy AI through isolated pilots, grocery giant Albertsons Companies has built a unified data and AI platform that connects operations across its stores, supply chain, corporate functions, and digital channels. The system is being used to improve demand forecasting and inventory management, optimize promotions and product assortments, and power more personalized digital shopping tools. Albertsons has also introduced AI tools for employees to reduce repetitive work and to help associates make faster decisions. The company says these efforts are contributing to a multibillion-dollar productivity target.

Chipotle Mexican Grill
For using AI to speed up restaurant hiring
Chipotle partnered with Paradox to build Ava Cado, an AI-powered hiring assistant that guides restaurant applicants from initial application through interview scheduling and offer. The mobile-first system answers questions, collects candidate information, coordinates interviews, and sends offers around the clock, including during the roughly 30% of interactions that occur outside normal business hours. Since its launch, Chipotle says the average time from application to start date has fallen from 12 days to four, while application completion rates have climbed from about 50% to nearly 88%. Applicant flow has nearly doubled, and 96% of offers are accepted.

The companies and individuals behind these technologies are among the honorees in Fast Company’s Next Big Things in Tech awards for 2026. Read more about the winners across all categories and the methodology behind the selection process.

As enterprises scale their use of LLMs and autonomous agents, the big questions are shifting from adoption to control and cost. Instead of providing organizations with generic AI tools, this year’s honorees bring domain expertise and niche solutions to solve complex problems. They’re helping legacy organizations such as government agencies and hospitals modernize processes to improve compliance and quality while reducing cost.  

Integrate
For modernizing government project management
Integrate is helping to modernize government project management, where complex programs and secure data need to work across fragmented systems, government agencies, and contractors. Its platform can run over classified networks, with permissions that can limit access down to individual data elements while keeping project timelines continuously updated instead of relying on periodically refreshed reports. These upgraded systems could be even more important as government agencies work with more AI model providers, software platforms, and outside partners. In 2025, the company signed a $25 million contract with the U.S. Space Force to help improve management and coordination of space programs over the next five years.

Knox Systems
For taking the headache out of government sales
Cloud companies selling to federal agencies often need to prove they can securely handle government data, which can involve a lot of red tape and technical hurdles. Instead of making companies start from scratch, Knox Systems created a way to fast-track the process by connecting its own prehardened infrastructure and security controls within existing environments. It’s also adapting for FedRAMP’s focus on continuous vulnerability monitoring, with KnoxAI already in use by more than 100 government agencies, including the U.S. Navy and U.S. Treasury. Knox, which says it helps cut FedRAMP approval time to less than 90 days and slash first-year costs by 90%, has customers such as Adobe and Celonis. It recently announced an infrastructure partnership with Microsoft Azure Government Cloud. 

Midstream Health
For helping hospitals find hidden revenue 
It’s no secret that hospital finance is notoriously slow and fragmented. Hospitals such as Houston Methodist and Mount Sinai are turning to Midstream Health for help. Instead of optimizing coding or billing, the company uses AI to find money hospitals are already owed but haven’t collected yet from missed rebates, pricing errors, and underpayments. One of the largest not-for-profit health systems used Midstream’s AI to analyze data from 20 disconnected systems of record, uncovering “tens of millions” in uncollected rebates. Over the next five years, Midstream plans to expand its portfolio of agents across healthcare supply chains, managed care, and pharmacies to tackle other operational and economic issues.

Sonar
For applying quality control to coding agents
As AI makes code generation cheap and abundant, verification and trust become even more valuable. Sonar has built a new independent verification layer around that shift by evolving its SonarQube platform for the agent-centric development cycle to improve accuracy, security, and reliability. New tools include ways to guide coding agents with repository-specific context, hunt for hard-to-spot security flaws, automatically fix or flag existing issues within agentic workflows, and verify outputs. Rather than trusting one LLM to grade another, it verifies outputs by analyzing code deterministically as an independent analysis. Sonar works with coding platforms such as Claude Code and Cursor, and it recently acquired the AI code-review startup Gitar. Its customer base covers over 75% of the Fortune 100, including Nvidia, ServiceNow, AstraZeneca, and Ford.

Tailscale
For bringing order to API key chaos
Expanded use of AI agents and LLMs has made usage harder to track. To give security and finance teams more granular visibility into usage and spending, Tailscale’s Aperture platform centralizes API credentials and better connects agent and LLM traffic to users, devices, and workloads. Earlier this year, it made its first acquisition when it bought the Vancouver-based firm Border0, which helps companies manage and monitor how autonomous AI tools access servers and databases. Tailscale also recently added browser-based AI access, universal data connectors, and sandbox support to help tackle “shadow AI” by giving employees easier ways to use approved models. 

The companies and individuals behind these technologies are among the honorees in Fast Company’s Next Big Things in Tech awards for 2026. Read more about the winners across all categories and the methodology behind the selection process.

Innovation can be challenging, even for companies with a clean slate. Those who have an established track record of 15 or more years of business must navigate history, culture, product lines, and other entrenched forces that can be both assets and inhibitors. Our honorees have shown that past success doesn’t preclude tomorrow’s progress by leveraging robot fleets for construction and extending real-time intelligence to billions of devices.

DeWalt and August Robotics
For getting fleets of robots to drill down into construction efficiency
Gargantuan data centers do not spring up overnight. Their many construction complexities include holes for structural support as well as mechanical, electrical, and plumbing systems. To streamline what can be a particularly labor-intensive process, DeWalt and August Robotics developed robots that can be operated together as a fleet to handle physically demanding tasks such as concrete drilling while supporting a collaborative human-machine model. In July, August Robotics reported that its drilling robot delivers up to 10x faster drilling speeds versus traditional methods, reducing construction times by 190 weeks across 26 major projects.

Synaptics
For developing edge intelligence in an open-source model
With AI token expenditures soaring in many businesses and security, privacy, and latency concerns preventing many applications from using cloud-based AI, many companies are eager to explore edge-based options. Best known for its pioneering work in developing the touchpad 30 years ago, Synaptics has developed Astra, an open platform to bring real-time intelligence into devices such as factory equipment, medical devices, home appliances, and retail systems. At Google’s developer conference, Synaptics showed off how an Astra-powered development board equipped with Google’s Coral NPU could generate real-time music based on the tracked movement of jellyfish.

The companies and individuals behind these technologies are among the honorees in Fast Company’s Next Big Things in Tech awards for 2026. Read more about the winners across all categories and the methodology behind the selection process.

Much of the discussion around AI and young people has focused on what career opportunities may exist in the future. But the technology is already changing education. These honorees have leveraged it to personalize preparation for standardized tests as well as help teachers generate compliant curricula and supporting educational materials.

Acely
For personalizing college entrance exam preparation
Many families pay about $1,000 for college entrance exam prep programs that offer one-size-fits-all instruction, with private tutoring stretching well beyond that. Acely seeks to flip that investment on its head with a personalized program starting at $49 per month that requires only about 20 minutes a day. While that still adds up, the service provides personalized, responsive instruction, not just a barrage of drills. In August, the company formed a partnership with the organization behind the ACT to co-market its prep platform nationwide.

Chalkie
For making AI a helpful teacher’s pet
The exceptional emotional intelligence needed to effectively connect with young minds likely leaves teaching relatively low on the list of jobs humans will soon cede to AI. Chalkie keeps the technology squarely in the toolset of human teachers by creating educational resources grounded in sound pedagogy, learning objectives, activities, assessment, and recap tasks, with a special emphasis on making lessons academically and structurally effective. It can also tailor curricula to national and state standards such as Common Core and even adapt lessons to meet IEP-mandated requirements. In March, the edtech startup raised a $4 million seed round. It also recently crossed the million-teacher mark in its user base.

ClassDojo
For helping to develop early reading skills
Education platform ClassDojo’s Dojo Sparks coaches young readers using specially tuned speech recognition, an adaptive science-driven curriculum, and a child-friendly design that integrates motivation and repetition. The company says that using it for 15 minutes a day can take some children from pre-literacy to second-grade reading in six months or less. ClassDojo, which has been expanding its online tutoring and school communications offerings, recently shared that it is used by 45 million families and teachers worldwide.

The companies and individuals behind these technologies are among the honorees in Fast Company’s Next Big Things in Tech awards for 2026. Read more about the winners across all categories and the methodology behind the selection process.

Training data begat large language models—and ever since, they’ve been intimately bound. This year’s honorees include a database tuned for AI agents, a dataset for AI-aided diagnosis of breast tumors, and a platform that gives companies more control over how their data is acquired and used.

Databricks
For bringing databases up to AI speed
According to Databricks, AI agent creation of test and development environments on its platform has grown from 0.1% two years ago to 97% today—a dynamic that traditional database architectures have been ill-equipped to accommodate. In response, the company developed Lakebase, a ground-up rearchitecture of databases that can spin them up and shut them down at AI speeds, facilitating the multitude of small, fast workloads of AI-driven development. In August, Databricks raised $5 billion in a strategic funding round, valuing it at $190 billion. The company’s revenue run rate has grown 80% year over year.

DataPelago
For transparently routing code to the optimal processor
While GPUs and NPUs are the processor architectures most closely aligned with AI, high-performance computing tasks also take advantage of two other kinds of processors, CPUs and FPGAs. Effectively routing the right computations to the right processors can reduce significant overhead. DataPelago’s Nucleus modernizes CPU-centric designs of legacy systems and acts as a bridge between data lakes and query engines. It routes computing requests to the most efficient processor type available without requiring any code changes. The company says that its Accelerator for Apache Spark delivers up to 10x faster performance at 80% lower compute costs. In August, DetaPelago was acquired by NetApp, which put Nucleus at the core of its full-stack AI offering.

DDN
For scaling storage to supercomputer workloads
Training ever larger and more capable data models has been hampered by slow data path throughput, which can result in GPU underutilization. DDN’s EXAScaler is a parallel file system technology. One of its highest-profile clients is Google Cloud’s Managed Lustre, a file service used for AI and high-performance computing models. Salesforce and Nvidia are also customers. The managed service can scale up to 10 terabytes per second by combining parallel I/O and high-throughput shared storage. DDN is on track to double revenue to $1 billion in 2026 on surging AI storage demand.

Hydrolix
For improving site traffic insights by watching the bots
AI agent and bot traffic now accounts for more than half of all web traffic, according to Cloudflare. Hydrolix’s Bot Insights makes this behavior visible, providing personalized dashboards for different job roles and allowing customers to decide which ones to block. They can also query the data to answer questions about latency during checkouts or rising search costs. Hydrolix reports that Bot Insights reduces incident attribution time by 95%. The company recently raised an $80 million Series C venture round and was featured as the engine powering AWS’s Agentic Intelligent Operations platform for streaming media

iMerit
For improving breast cancer diagnosis through a breakthrough dataset
When detected early, the five-year survival rate for breast cancer exceeds 90%. The clinical standard for screening—Digital Breast Tomosynthesis, also known as 3D mammography—outperforms traditional 2D mammography for detecting lesions that could be cancerous, particularly in women with dense breast tissue. Unfortunately, this method is held back by a shortage of biopsy-confirmed datasets. iMerit has worked with Segmed and Advocate Health to release an open-source, freely available dataset of more than 500 biopsy-confirmed exam results. The dataset was released in accordance with HIPAA regulations and split roughly between benign and malignant cases. The dataset should help researchers hone AI’s ability to more accurately and quickly assist diagnosis. In August, data and AI company EXL completed its $310 million acquisition of iMerit.

Mozilla Data Collective
For giving usage control to dataset owners
One of the most prominent controversies around AI concerns compensation of the parties behind the data sources used in its training. While content owners are striking deals with AI giants or blocking bots to pave the way for negotiations, the Mozilla Data Collective takes a more proactive approach. Entities that own datasets can share them under their own terms while retaining ownership and control over how that data is used, including compensation. The collective includes more than 350 organizations sharing over 1,700 curated datasets. This year, Mozilla spun out the Data Collective as an independent entity.

The companies and individuals behind these technologies are among the honorees in Fast Company’s Next Big Things in Tech awards for 2026. Read more about the winners across all categories and the methodology behind the selection process.

Consumer technology is at its best when it’s solving problems that exist outside of the tech world. This year’s honorees include better ways to clean your floors, put on your shoes, hear the conversation around you, and practice music effectively. There’s also a less-intrusive smart lock, a refreshingly simple microwave oven, and—if you’ll allow one solution to a problem caused by technology itself—a way to spare your smartphone screen from prying eyes.

JBL/Harman
For giving guitar practice an AI upgrade
While the modern musician will find no shortage of backing tracks on YouTube for practice purposes, they’re seldom as fun to jam with as the original material. JBL’s BandBox Solo and Trio guitar amplifiers can play music from streaming services over Bluetooth but with AI audio separation that controls the volume of individual instruments. Users can mute a song’s guitar track while playing along themselves, or turn down the vocals and drums to better hear the notes in a tricky solo. Software tools such as LALAL.AI and Moises have long allowed aspiring musicians to create backing tracks from recorded music, but by building this capability directly into the hardware, JBL is adding a new layer of convenience.

Kizik
For making footwear hands-free
For nearly a decade, Kizik has been making shoes you can squeeze your heels into without having to use your hands. But while the company has expanded into new categories such as snow boots, running shoes have always been a major challenge because of the need for a stable fit with no performance compromises. The company finally cracked the problem this year with its Freedom Run line, with a heel design that compresses when you step into it but then snaps into a rigid position that prevents slippage. Tests at Brigham Young University confirmed that the shoe’s heel stability while running is comparable or better than that of leading brands. The company’s parent, HandsFree Labs, is also working with Nike and New Balance and plans to expand into other areas of active footwear, such as hiking and winter sports, with the eventual goal of making every shoe hands-free.

Legato
For using smart eyewear to enhance what you hear
While Big Tech companies like Meta and Google hoover attention with their smart glasses platforms, Legato is building frames for a more practical purpose. Its Legato Frames use on-device AI audio processing to enhance human speech while quieting background noise, serving as a stylish and smarter alternative to traditional hearing aids. The company has a big rival in EssilorLuxottica, whose Nuance Audio glasses serve the same purpose. Still, its team of former Bose engineers figured out how to solve some key problems, such as amplifying the voices of others without unnaturally boosting the wearer’s own voice. Frames remains on a waitlist, though Legato has raised $12 million to help bring the product to market by year-end.

Level Home
For making smart locks look less dumb
Smart locks tend to be eyesores, with bulky enclosures to house all the necessary motors, sensors, and connectivity. With the Level Lock Pro, Level managed to fit all of those components into a smart lock no larger than a standard deadbolt. The company says it’s 62% smaller than traditional smart locks. Corporate parent Assa Abloy laid off most of Level’s staff in June, according to The Verge, but the Swedish lockmaker intends to maintain Level as a separate brand. Even if the Lock Pro ends up being Level’s swan song, here’s hoping it inspires the next generation of rival smart locks to shrink down.

Roborock
For literally bringing robot vacuums to the next level
Climbing stairs has always been a holy grail for robot vacuums. So Roborock naturally made a stir at CES in 2026 with its Saros Rover, a prototype robot vacuum with a pair of retractable wheels on legs. They allow the device to make its way up a staircase, cleaning each step on the way. While Roborock has not shared concrete launch plans, the company says it’s a “real product in development.” And with rival Dreame developing its own stair-climbing concept (albeit one that can’t clean the stairs itself), the race to solve robot vacuums’ multistory problem is well underway.

Samsung
For offering a solution to shoulder surfing
Samsung’s Privacy Display is the first new smartphone feature in years that feels like a truly practical breakthrough. Debuting on the company’s flagship Galaxy S26 Ultra, the feature applies a matrix to the display that narrows the beams of light emitting from each pixel, making the screen harder to read from off-angles. This can prevent strangers from peeking at your phone’s contents in public places such as trains, planes, and elevators. Unlike aftermarket privacy-protecting screen protectors, the Galaxy S26 Ultra lets users toggle the feature on and off or limit it to specific apps. This allows the screen to remain bright and shareable when you’re not worried about who might be looking.

The companies and individuals behind these technologies are among the honorees in Fast Company’s Next Big Things in Tech awards for 2026. Read more about the winners across all categories and the methodology behind the selection process.

Advances in computing aren’t just about faster processors. As these innovations show, progress is driven by everything from the technologies used to transmit data to the systems that ensure data centers get reliable power without overwhelming the grid. If many of them are largely invisible to most of us—well, that’s kind of the point.

Amazon
For skating where the AI puck is going
Announced at AWS re:Invent in December 2025, Trainium3 is Amazon’s newest AI chip. It’s designed to take on not just today’s dominant AI workflows but also to anticipate the needs of emerging ones such as world models. Equipped with up to 144 chips, Amazon’s Trainium3 UltraServer quadruples the compute performance and energy efficiency of its predecessor. Uber is adopting Trainium3 for tasks such as calculating arrival times, and video-generation platform Decart has used it to achieve 4x higher frame throughput and reduce latency by 75%.

Cadence
For teaching AI agents to design processors
Historically, advances in processor design have been propelled by human engineering talent, a resource that’s difficult to scale. Introduced in early 2026, Chip design giant Cadence’s Super Agents take on essential elements of the process such as creating test plans, design node migration, and digital implementation. Already adopted by big names like Nvidia, Qualcomm, and Altera, they offer up to 10x productivity increases across design and verification, according to Cadence.

HP
For building a workstation today for tomorrow’s GPUs
Out of the box, HP’s Z8 Fury G6i desktop workstation can support for up to four powerful Nvidia RTX Pro 6000 GPUs. But the company also looked ahead to future GPUs. The workstation’s optional Max Side Panel expands its case by 1.4 inches and adds cooling fans, allowing tool-free expansion to accommodate larger, hotter GPUs that require more power and would otherwise require the purchase of a new workstation. HP uses recycled plastic, steel, and rare earth materials to build the Z8 Fury G6i and put it through 360,000 hours of reliability testing.

Marvell
For harnessing light to move AI data
No matter how fast an AI system’s GPUs are, it may be held back by the electrical interconnects and copper pathways used to shuttle data in and out. Marvell’s Phototonic Fabric platform replaces them with light-based transport, allowing the same energy footprint to deliver up to three times the performance. The company gained the technology as part of its $3.25 billion acquisition of Celestial AI, announced in December 2025, and has since been engineering products that will support it both as an upgrade to existing AI systems and as a core element of future ones.

ON.energy
For giving AI the uninterruptible power it needs
AI data centers don’t just draw vast amounts of power—they do it in oscillating bursts that stress the electrical grid and cause problems for everyone else on it. After developing an uninterruptible power supply for a Mexico City bakery prone to blackouts, ON.energy realized that its design was also applicable to AI. That led to the AI UPS. In tests at the U.S. Department of Energy’s National Laboratory of the Rockies, it prevented load swings from 30% to 100%, in intervals as fleeting as 10 milliseconds, from impacting the grid.

Silicon Quantum Computing
For pioneering quantum-enhanced AI
In October 2025, Australia’s Silicon Quantum Computing launched a quantum-enhanced machine learning system called Watermelon. The first commercially available quantum reservoir computer, it uses quantum technology to spot patterns in datasets that can’t be identified by classical computers. The technology requires the placement of phosphorous atoms in silicon with 0.13 nanometer accuracy and has been validated by partnerships with Telstra, Nvidia, and the Australian Department of Defense.

The companies and individuals behind these technologies are among the honorees in Fast Company’s Next Big Things in Tech awards for 2026. Read more about the winners across all categories and the methodology behind the selection process.

AI is poised to transform virtually everything about online and physical retail, from product exposure and recommendations to consumers even having to complete the transactions for themselves. These honorees are setting the stage for agentic commerce, allowing critical medical supplies to take flight and providing physical retailers with comprehensive intelligence about shopping variables within and beyond the store.

American Express
For putting agents on the checkout line
During the early days of e-commerce, retailers strived to simplify online purchasing for consumers. In the AI era, a new wave of accommodations must be forged to allow frictionless transactions by agents. American Express’s Agentic Commerce Experiences (ACE) toolkit leverages the company’s experience across a range of financial roles and includes a new trust model focused on identity, intent, accountability, and visibility. But Amex is still keeping humans in mind through a new agent purchase-protection program that protects eligible card members from charges resulting from certain AI agent errors. Early-access developer partners have recently signed on to ACE, which could further drive the record card-member purchases the company reported in its most recent quarter.

CVS Health
For making delivery of critical products airborne
While several companies have deployed drones during emergencies and others have piloted broad drone delivery programs, CVS’s Air Response program targets a scenario that falls in the middle: serving patients who need critical supplies such as naloxone, epinephrine, and automated external defibrillators (AEDs). As a retailer serving mass markets, CVS has designed its drone network to operate safely in urban environments. The company is now exploring integration with 911 systems and has announced partnerships with Thales and SkyfireAI as it frees up investment dollars through its exit of the Omnicare long-term-care pharmacy segment.

WVN
For developing holistic retail site intelligence
Physical-store owners have long envied e-retailers that have nearly perfect accounts of the digital pathways purchasers travel through their storefronts. WVN seeks to create a comparable level of market intelligence for brick-and-mortar players. StoreBrain is an AI agent that acts as a persistent AI intelligence layer for physical storefronts, capturing and analyzing not only onsite indicators like transactions, foot traffic, and shelf input but also inputs beyond the store, such as online reviews. The company’s training data also covers demographics, psychographics, economics, and even weather data. The company reports that 93% of stores using its platform report improved conversion. It recently inked a partnership with menswear brand Mugsy, which operates eight physical stores.

The companies and individuals behind these technologies are among the honorees in Fast Company’s Next Big Things in Tech awards for 2026. Read more about the winners across all categories and the methodology behind the selection process.

As the real estate industry struggles with rising interest rates and ballooning material costs—thanks in part to tariffs—innovation is becoming more and more important. New technologies and construction methods are boosting margins for builders and helping to compensate for labor shortages. And in some instances, they’re dramatically reducing building times without sacrificing safety standards.

Augmenta
For reducing waste and augmenting bottom lines
Since late 2025, Augmenta’s AI engine has generated 3D building designs for electrical systems. That dramatically speeds up the design process, as it can take engineers hundreds of hours to manually model those systems. And it’s not just theoretical: Around 100 buildings have taken advantage of the technology so far, with the first, an elementary school, reducing material waste by 15% and cutting design time by 25%, the company says. Those real-world results are saving builders money and letting them automatically adjust plans as design needs change—a frequent occurrence in construction. Up next for the company is the inclusion of mechanical and plumbing system designs, which should further reduce costs for builders.

LightTable
For spotlighting ways to dramatically speed up construction timetables
It normally takes three to six weeks to analyze an architect’s or engineer’s construction drawings for potential errors. Using LightTable’s AI platform, it takes just three to five days. To date, the company says it has reviewed more than 20 million square feet’s worth of documents, representing $10 billion in project costs. As real estate projects get more complicated, this is a technology that could streamline the building process before the first shovel breaks ground.

TerraFirma
For bypassing labor shortages through autonomy
Founded by former SpaceX engineers, TerraFirma sees similarities between building rocket ships and building infrastructure. The company uses autonomous technology that lets a single worker operate multiple excavators, bulldozers, loaders, and other vehicles simultaneously. That doesn’t require designing new construction equipment: Retrofit kits can be installed on existing machines in under five hours to automate them. It’s a technology the company hopes to use off-world as humanity looks to build a presence on Mars, and the idea is catching on fast. TerraFirma has already seen commercial demand from data centers, industrial sites, and residential developments. And the company has generated more revenue year-to-date than it raised across all seed financing.

Willow
For spotting problems before they happen—and saving millions in the process
Equipment failures can be a major cash drain for building operators. Willow’s technology uses AI to detect and anticipate building equipment failures before they happen, proactively alerting management systems to the problem. And it’s generating big savings for its commercial clients. To date, the company says it has saved Walmart $1.4 million by preventing more than 800 failures and Georgia Southern University more than $1 million. Its technology is already being used in 38 countries, putting it on a strong growth trajectory. The real-world effect is that infrastructure such as airports, hospitals, and other facilities can anticipate and repair problems ahead of time rather than reacting to breakdowns.

The companies and individuals behind these technologies are among the honorees in Fast Company’s Next Big Things in Tech awards for 2026. Read more about the winners across all categories and the methodology behind the selection process.

The metaverse hype bubble may have burst, but that doesn’t mean immersive computing is yesterday’s news. Technologies such as spatial computing and VR are changing how products are designed, where entertainment can happen, and what kind of medical care is available in remote maritime situations.

Dassault Systèmes
For putting Apple Vision Pro to work
Organizations of all kinds are eager to create digital twins of their most crucial real-world products, processes, and spaces. 3D-design software giant Dassault Systèmes’ 3DLive turns Apple’s Vision Pro headset into an intuitive, precise way to engage with these simulations. Customers have adopted it for applications ranging from engineering new EVs to testing surgical instruments. An aerospace company used the platform to bring participants on three continents together to review an aircraft’s interior, cutting approval time in half and saving $450,000 in travel costs.

Excurio
For breaking through VR’s boundaries
Shared VR experiences in public spaces have been held back by challenges such as scaling up the number of people supported by an environment and allowing different participants to explore varying worlds. Paris-based Excurio’s LBXR Pulse lets museums, cultural institutions, entertainment venues, and other organizations deploy VR to up to 130 users simultaneously in multiple concurrent experiences. It’s in use at 25 venues in 17 countries, with big-name content partners such as the Musée d’Orsay and Harvard University’s Giza Project.

Veyond Metaverse
For using XR to bring healthcare to the sea
More than 2 million people are seafarers or work on offshore rigs. Veyond Metaverse’s OceanMD lets them receive telehealth services from onshore medical professionals wearing mixed-reality headsets. Unlike most mixed-reality platforms, which assume the availability of high-speed internet, OceanMD is designed to operate at just 100 kbps, allowing it to run over the slow satellite access available at sea. Pilot programs are underway in West Africa and Brazil offshore operations, and in May 2026, international SOS company Medaire secured a five-year exclusive agreement to use the technology for global civilian aviation.

The companies and individuals behind these technologies are among the honorees in Fast Company’s Next Big Things in Tech awards for 2026. Read more about the winners across all categories and the methodology behind the selection process.

2026 may have been the year when AI stopped getting brownie points simply for being amazing. What’s impressive now is AI that performs useful tasks. All the better if it does it quietly, cleverly, and in areas that help humans focus on the work that we still do best. These honorees check off all those boxes, in areas ranging from workplace productivity to medical safety.

Alembic
For proving how decisions turn into outcomes
Alembic’s “causal engine” uses a proprietary AI system to help enterprises understand the real effects of actions they take. The platform can analyze thousands of variables simultaneously–everything from broadcast and digital advertising spend to macroeconomic shifts to executive public appearances–and map them to specific outcomes, or to the lack of an outcome. Nvidia was Alembic’s first enterprise customer, and its CEO Jensen Huang has publicly praised the platform, whose other big customers include Mars and Delta Airlines. In November 2025, Alembic closed a $145 million Series B led by Accenture (which now offers Alembic’s causal-AI analysis to its consulting clients) and Prysm Capital, valuing the company at approximately $645 million.

Canva
For giving us AI-powered design that doesn’t suck
We all have that design in our heads that we can’t quite generate ourselves. Canva’s AI 2.0, released earlier this year, allows you to turn ideas into reality without really needing to know your way around design software. The tool is powered by the company’s Canva Design Model, and might allow you to whip up a campaign with just a few instructions and then refine it with ease—something that’s notoriously hard to accomplish with general-purpose AIs such as ChatGPT. More than 400 designs are created in Canva AI every second.

Credo AI
For helping enterprises jump-start AI governance
Credo AI’s popular AI governance platform now offers the Govern AI Assistant (GAIA), which helps enterprises more easily manage AI models and tools. (A Credo AI study found that while 60% of organizations now deploy AI across multiple departments or company-wide, only 4% are governing those deployments across the organization.) The assistant is pre-loaded with Credo AI’s governance libraries, years of enterprise deployment experience, and global regulatory frameworks such as the EU AI Act and NIST AI RMF. Users upload a product brief or project plan, and GAIA generates use case descriptions, recommends metadata, drafts questionnaire responses, identifies risk scenarios, and maps controls to those risks.

DeepL
For overcoming language barriers in real time
In April 2026, DeepL unveiled real-time voice-to-voice translation as part of its DeepL Voice translation product. A user can now speak naturally in their own language, while another user immediately hears the meaning spoken aloud in theirs, enabling live conversation across languages without waiting for captions or interpreters. Pioneer, Aramark, Avendra International, and the European consultancy Inetum have all begun using DeepL Voice, DeepL says. The company doubled down on real-time voice this year when it completed its acquisition of Mixhalo, which specializes in ultra-low latency audio that’s been used to power live events for thousands of simultaneous participants. DeepL aims to leverage the technology to enable real-time translation for larger groups such as conferences with thousands of attendees and hundreds of speakers. 

Genspark
For giving productivity an agentic edge
Once an AI search engine, Genspark has become an AI agent platform. Its AI Workspace offers a wide array of tools, including a full AI office suite, an image generator, and specialized AI agents. Under the hood, an orchestration engine that calls on about 70 AI models, depending on the nature and requirements of the task at hand. A persistent AI assistant, Genspark Claw, can complete long-running multi-step workflows asynchronously, accessing browsers, files, and enterprise tools such as Microsoft Office 365. With more than 5,000 enterprises now using the platform, the company says its business raced to $250 million in annualized revenue in the spring of 2026.

Hanwha
For operating data centers with more autonomy
Data centers use an enormous amount of power, so much that they’ve now become politically polarizing. To help mitigate that problem, Hanwha, the South Korean conglomerate, has developed an Energy Management System that acts as an uber-smart manager of all the electricity that runs through one of these facilities. Using a cadre of large language models and other machine learning systems, it can monitor a data center’s telemetry, alarms, and fault detection systems. Then it studies what might be causing an issue, and how to respond. In April 2026, Prime Group, one of the largest private real estate investors, adopted the technology for a nationwide deployment of edge data centers.

Odyssey
For making simulated physics interactive
Language models ignited the generative AI revolution, but the real world runs on physics, not text. Odyssey’s world models learn from visual observation of real-world activity and generate video that responds to a user’s actions, making them useful in simulations, gaming, and robotics. The company’s latest model, Odyssey-2 Max, advances the interactivity, stability, and fidelity of its earlier models; the company says it earned the highest physics score among publicly evaluated world models on the VBench 2 benchmark (58.52, up from 49.67 in the prior generation). Perhaps the best proof of the company’s potential is its list of backers, which include AI luminaries Jeff Dean, Elad Gil, and Garry Tan. It’s also backed by NVIDIA’s venture arm.

Replit
For taking on the heavy lifting of vibe coding
Unlike many AI coding platforms, Replit has kept its focus on enabling users to vibe-code their way through whole software development projects. The company’s newest assistant, Agent 4, allows non-coders to direct the AI in plain language to design, build, and ship software. Replit handles the hosting, databases, authentication, and monitoring, and offers more than 100 integrations with services from companies such as Databricks, Stripe, Slack, and Microsoft. A user can produce a web app, a mobile app for iOS and Android, a slide deck for an investor pitch, and a launch video—all from a single project. More than 50 million people use Replit, and 85% of Fortune 500 companies now build with it, the company says.

SAS
For developing simulation that powers sterilization
SAS, the global data company, is designing high-fidelity digital twins of environments such as operating rooms. Using Epic Games’s Unreal Engine, the same technology that powers immersive video games, SAS can simulate essential details such as the specialized sterilization procedures that need to go exactly right to keep patients safe. Today, the system is used to help refine the work at Sterilcentral, a facility in Denmark charged with cleaning thousands of instruments used in surgeries.

Tensor Auto
For self-driving cars that belong to . . . you
Unlike Waymo and other autonomous-vehicle companies focused on the robotaxi business, Tensor Auto is building a self-driving car that you can actually own, armed with powerful lidar sensing systems and an onboard supercomputer that can listen to verbal commands. The core of the system is the Tensor World Model, which uses prompts to simulate all sorts of physical conditions that a car might encounter. These kinds of simulations form the basis of Tensor’s brains, but they could be applied to other physical AI, too. The company has already won a Level 4 DMV testing certification in California.

Vexcel
For teaching AI to understand the world from above
Vexcel, an aerial imagery company, is training AI to understand everything on the ground from a bird’s-eye view. Its Vexcel Intelligence system can scan satellite imagery for complex descriptions, such as a set-back Victorian house or farmland growing a specific type of crop. The company is working with Google Maps and helping with disaster-response assessment, including after a tornado in Oklahoma and a fire in Georgia.

Within
For building organizational brainpower
Many enterprise AI deployments fail to pay for themselves because they automate workflows that are inconsequential or that the company doesn’t really use. Within (formerly Klarity) focuses on helping businesses understand how their people actually work, creating an operational context graph (aka “Company Brain”) and tapping that knowledge to design, build, and manage context-rich agents. The company says it saved its 93 customers (which include OpenAI, Salesforce, ServiceNow, and Uber) $53.9 million in consulting fees during 2025. Within has raised more than $91 million in total funding from investors such as NFDG, Elad Gil, and Y Combinator.

Yutori
For teaching AI to surf the web like a pro
Yutori develops web-using AI agents. The company trained its Navigator n1.5 model on both simulated and real site interactions to reliably handle a broad set of web tasks. More recently, the company released Navigator n2, a 27-billion-parameter computer-use model designed for operating full desktop environments. Yutori says that its customers (such as Meta) are now making more than 100 million API calls to its models every month, and that its agents are interacting with “several hundred thousand” merchant websites daily. The company’s cofounders, Dhruv Batra and Devi Parikh, led high-profile AI development teams at Meta, while other Yutori researchers came from leadership roles at Google DeepMind, Tesla, and Apple.

The companies and individuals behind these technologies are among the honorees in Fast Company’s Next Big Things in Tech awards for 2026. Read more about the winners across all categories and the methodology behind the selection process.

Capcom saw tremendous success with the launch of Resident Evil Requiem earlier this year. The survival horror game has already sold more than 8.5 million copies, bringing in revenue topping $500 million and reigniting interest in the 30-year-old franchise.

Resident Evil Requiem, like any AAA game, took a long time to make, with a development cycle spanning six years and including a reboot midway through production. To maintain momentum, Capcom has revealed plans to incorporate artificial intelligence into its game development process.

The project is called REX, programmer Satoshi Ishida revealed at a tech conference over the weekend. At its core, six separate programs will help integrate AI and machine learning into the RE Engine, the increasingly long-in-the-tooth proprietary game engine that powers Capcom’s biggest titles.

The goal, Ishida said, is to create a “game engine of the AI generation.”

To be clear, Capcom isn’t planning to have AI develop creative elements for its games, such as game assets. Instead, the project reflects a broader problem facing the industry: Game development cycles are getting longer, and Capcom hopes AI can streamline parts of the process. That includes elements like quality assurance testing and other development efficiencies.

Capcom is hardly alone in incorporating AI into its workflow. Several other publishers have done so in recent years. Electronic Arts CEO Andrew Wilson said in April that AI technology has augmented jobs at the company rather than replaced them.

“I saw some data recently, I think, now almost all—like 85%—of our quality assurance [work] is done with some kind of machine learning or AI-driven algorithm,” he said.

And Strauss Zelnick, CEO of Take-Two Interactive Software, said his company is exploring what advantages AI can offer.

“Anything that allows us to do a better job—quicker and cheaper—we’re interested,” he told Fast Company at the Entertainment Software Association’s Interactive Innovation Conference earlier this year. “What we are beginning to see is mundane work that can easily be replaced by technology is indeed being replaced [and] people turn their attention to higher-value tasks.”

Capcom’s AI tools will do much the same. One system, for instance, could animate groups of objects or characters together rather than having those animations run individually in real time. Another, according to Capcom’s presentation, would convert game-mechanics ideas into a standardized programming language. Since RE Engine is used by developers in several countries, that common language could also help speed up development.

Capcom did not respond to a request for further comment about the REX project, but it addressed its stance on AI during a shareholders meeting in March, making clear it was interested in the technology but did not plan to use it to replace the human creative force behind its games.

“We will not implement assets generated by AI into our games,” the company said. “However, we plan to proactively use it as a contributing technology to improve the efficiency and productivity of the game development process. To this end, we are currently exploring ways to implement it in various areas, including graphics, sound, and programming.”

This isn’t Capcom’s first experiment with AI. In January 2025, it created a prototype “idea generation” system alongside Google that used generative AI to help brainstorm ideas.

“One of the most time-consuming and labor-intensive aspects of game development is brainstorming ideas to create the game’s world,” Kazuki Abe, technical director at Capcom, said at the time. “For example, if there’s a television in the game’s environment, we can’t just use an existing product. We need to come up with the shape, manufacturer’s logo, and other details ourselves.”

The companies said the system lowered the cost of brainstorming, helping improve margins. But as the video game industry continues to undergo a painful contraction, with many studios cutting staff, almost any use of AI is likely to create tension among game makers.

As AI advances and becomes capable of doing more, executives may eventually reconsider whether some positions are necessary. Zelnick acknowledges that possibility, though he argues that properly implementing the technology can instead eliminate low-value work.

“I have an obligation to run an efficient enterprise,” Zelnick said. “We have not seen any opportunity to reduce head count because of AI. What we have seen is an opportunity to stop wasting time on things that don’t create value.”

Apple’s Vision Pro was never going to be a big success right out of the gate. It wasn’t just the eye-watering $3,499 price—it was the headset’s reliance on highly advanced, low-yield OLED display panels from Sony, which could reportedly only be produced in quantities of under a million a year.

There was never a scenario in which the Vision Pro could have turned into the next iPhone—or even the next Apple Watch—overnight. Apple knew this when it released the product, but thought it was worth getting the platform out into the wild anyway.

That said, the company can’t be too pleased with the Vision Pro’s reception. Content for the headset has slowed to a trickle, and at no point since launch has it been difficult to find one in stock. A niche product designed to stoke excitement among early adopters and developers is one thing, but there’s little evidence that it’s succeeded even on that level.

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That’s not to say anything bad about the Vision Pro’s quality—visionOS is a thoughtfully designed operating system, and the hardware remains class-leading in many ways. But if Apple’s vision for spatial computing is ever going to take off, a few things need to happen. The headset needs to get smaller, it needs to be more comfortable to wear, and it needs to be much cheaper.

The Meta alternative

Enter Meta, which last week announced a product that would seem to tick all three boxes. The Meta VR Glasses are designed to do many of the same things as the Vision Pro, but in a lighter, more glasses-like form factor that costs only about a third of the price of Apple’s device—they’ll go on sale for $1,299 next year, while the Vision Pro starts at $3,699.

How did Meta do it? One cost-cutting measure is the VR Glasses’ OLED panels.

The Vision Pro’s dual 4K displays were expensive even by the standards of the rest of the hardware, which was as high-end as you’d expect of Apple. One Omdia estimate put the two internal Sony micro-OLED panels at $228 each. Add the much-ridiculed external OLED screen, which shows a low-resolution representation of the wearer’s eyes, and the estimated display bill came to around $530—or 35% of the total component cost. 

It’s important to remember that a bill of materials doesn’t tell you everything that goes into the sticker price you see on shelves. But in this case, it could well indicate how much Apple was spending on its display panels before accounting for chips, sensors, or anything else.

Meta says the VR Glasses have 2,412 x 2,288 pixels per eye, which is about half as much as the Vision Pro—it’s a total of around 11 million pixels versus 23 million. But in terms of sharpness, the two headsets are closer than you might think. Meta is quoting a figure of 37 pixels per degree, which is actually higher than the Vision Pro’s.

The catch here is that the field of view is smaller, at around 70 degrees horizontally compared with roughly 100 degrees for the Vision Pro. These figures can be fuzzy and differ between users, but the difference between the two is pretty stark.

In my experience with various augmented reality glasses, however, the field of view is not quite as critical in that form factor as it would be in a VR headset designed to immerse you in a virtual world. I often use the Xreal One glasses, for example, which have an even smaller 50-degree field of view, and the picture stretches out close to the edge of the glasses themselves. It’s not really something you think about when you’re watching a movie.

Meta does say that it will offer an optional accessory to block out peripheral vision, and in that configuration, the VR Glasses are likely to be less immersive than the Quest 3 or Vision Pro. But as a way to achieve the same kind of AR experience as the Vision Pro, while letting you see the world around you in a radically smaller and lighter design that weighs just 100 grams, it feels like a worthy trade-off—especially since the panels are so much cheaper and likely available in greater volume. Impressions I’ve heard from early testers have been universally positive.

Other advantages

Another way Meta has reduced the size and weight is by moving computing components to the tethered “puck,” which in the Vision Pro solely houses the battery. That felt like an odd decision by Apple even at the time of the Vision Pro’s release—after all, the majority of space inside an iPhone is already taken up by its battery. If you’re going to have a cable running down to a separate breakout box anyway, it would surely be prudent to make the most of it and lighten the load on the user’s head. 

Apple also didn’t want to compromise when it came to the Vision Pro’s controllers, or lack thereof. The operating system is entirely built around intuitive gesture controls, in a typically Apple move. But it did mean that the Vision Pro was on the back foot when it came to gaming support, and the later addition of support for the controllers from the PlayStation VR2—itself not exactly a roaring success of a device—hasn’t really moved the needle.

The Meta VR Glasses also won’t ship with controllers in the box, but they have two key advantages: compatibility with the huge library of Quest games and with Quest 3 controllers. That means anyone who buys the glasses and does want to play games on them won’t be short of things to do on launch day.

Of course, even the Quest 3—by some distance the most popular VR headset to date—is still far from a mass-market success, and there’s no guarantee that Meta will fare any better with the VR Glasses. But from a design and technology perspective, it’s shocking just how more viable of a product they already appear to be than the Vision Pro. 

Apple is going to have to go back to the drawing board with visionOS, and Meta may well have just shown the way forward.

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