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 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’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.
