Artificial Intelligence Startups funded by Y Combinator (YC) 2026

Scale accelerates the development of AI within organizations of any size to deliver critical business insights and operational efficiency. Its data-centric infrastructure platform leverages RLHF (Reinforced Learning with Human Feedback) to help organizations build the strongest AI models that supercharge their business, with customers across industries including Meta, Microsoft, U.S. Army, DoD’s Defense Innovation Unit, Open AI, General Motors, Toyota Research Institute, Brex, Instacart and Flexport.

Checkr builds people infrastructure for the future of work. And we believe everyone should have a fair chance to work. That's why we've designed a faster—and fairer—way to screen job seekers. For more information on our mission and products, visit https://checkr.com.

The next constraint is not intelligence, it is the energy cost of running it. We deploy custom AI models inside energy companies that ingest SCADA data, work orders, and grid topology, operational data no public model has seen, grounded in physics-informed neural networks and differentiable grid simulators. This creates a flywheel: more operator data → better process understanding → more efficient operations → cheaper energy → cheaper AI → more deployment → more data. https://www.youtube.com/watch?v=0uDH6pMn5OE AI compute doubles every 2.2 years. Data center demand grows from 415 to 945 TWh by 2030. Without near-zero energy cost, AI remains limited by human infrastructure. We are the layer that runs AI at zero energy cost. Energy is a $10 trillion market. The infrastructure layer doesn't exist yet. We are building it.

AI made software engineers 100x more productive. We're bringing that same transformation to knowledge workers with the AI desktop.

Lark builds specialized AI agents that automate manual workflows for wholesale distributors. Our agents work with existing ERP systems, learning from each distributor’s historical data and the team’s decisions. Together, these agents can run a distributor’s entire operation.

Build agents that research accounts, find prospects, run campaigns, update your CRM, qualify inbound, and more. Connect them to the systems you already use and let them work alongside your GTM team. Engineer your revenue factory on Frontrunner.

We design and collect audio datasets for training speech models.

We're building the open benchmark for commerce. Builders submit shopping agents. Independent validators run them against problems that change daily. The best agent earns the rewards, and every run becomes training data.

Dreamscale Labs is building the fastest cloud inference platform for robotics. As complex physical AI models become difficult to fit on expensive on-robot GPUs, we let users offload inference to the cloud and serve them with real-time latency. So far, we've hit 40-50% lower latency than existing neoclouds.

Hopper post-trains STT, TTS, and speech LLMs on your production calls, then serves and improves them against your live traffic

Frontier is first to grow biological brains at scale, serving biological neural nets with substrate-level colocation of memory and compute, enabling highly cost effective training of large parameter count models. While academia has traditionally been limited to ~1M neurons in vitro, Frontier has built a pathway to scale to 100M+ neurons by circumventing traditional scaling challenges in biological culture, demonstrating this strategy's functionality by training a biological brain using this scaling primitive to play Frogger. Frontier is now growing exascale compute clusters to produce substrates capable of long-horizon language reasoning while operating at much higher sample efficiencies than traditional architectures, and collocating memory with compute to enable significantly larger parameter counts than would be tractable for training within traditional compute clusters.

Intelligent Cloud for AI workloads

Workers IO verifies your entire system across millions of interleaving, faults, and timings to find the exact conditions that break the software properties you care about. Built for teams where 99.99% uptime is table-stakes.

Redoubt is a commercial insurance agency for small businesses. We believe our customers are our most important business partners, and they deserve our full attention. Machines can already handle the boring parts, the next step is to continually learn from experience.

Nobody's built truly proactive AI, because it requires running inference on your entire life. In the cloud, that's insanely expensive and a privacy nightmare. But not on your own chip. Every night, Sentient's on-device LLM wakes your Mac and understands what's new in your life (email, messages, files, Granola transcripts...), entirely locally, and distills it into a knowledge base. You wake up to your work already prepared: the reply you forgot, drafted from your own context; the subscription you never use renewing tomorrow, caught; the report you promised in the group chat, ready to send. Everything is one click from firing through computer use, and nothing fires until you click. Or click your Mac notch anytime and say "finish this for me." Sidekick takes over the thing you were doing with its own cursor while you move on. On-device inference at this scale was supposed to be impossible: devices too slow, and models too dumb. So we built the stack ourselves: a custom LiteRT-LM fork (KV-cache reuse, speculative decoding, custom k-quants) that runs nightly on 8 GB Macs. The user's hardware does ~90% of the compute, and their own ChatGPT or Claude subscription does the rest, so our marginal cost is ~$0, and our servers store nothing. We soft-launched late July with one Reddit post: top of r/macapps, 2,000+ users in 48 hours, $0 marketing. Free and open source for consumers; the same engine on the work stack (Slack, Granola, Linear, Notion) becomes the enterprise business. Sentient OS raised ~$1M in pre-seed, backed by YC, Afore, and the a16z Speedrun scout fund.

Allia is the first full-stack, AI-native clinical group for mental health. We bring independent practices into one national clinical group that can deliver, measure, and improve care at scale - 600+ providers (350+ therapists, 200+ nurses & doctors, 30+ psychologists) across 70 sites in 32 states, plus telehealth nationwide. Every clinician runs on a single intelligent system of record. And, that intelligence coupled with scale unlocks what no single practice could achieve alone.

Studio is a simulation lab studying how humans and societies respond to new ideas, and is building the first software models that can accurately predict that response. Instead of creating digital twins of survey respondents, Studio builds live market models of interconnected audience segments from real, traceable consumer-behavior data. Our simulations match live KPI outcomes like revenue and purchase behavior with over 97% accuracy for consumer-facing enterprises, higher than any synthetic panel, simulation lab, or traditional market research.

OpenTag is an AI coworker in your Slack with full context on your company. It answers questions and takes real work off your plate. It also keeps your wiki up to date automatically, so knowledge never goes stale.

Lantern learns what exceptional looks like for your team, pressure-tests the role against the real talent market, then runs the hiring loop: sourcing, inbound applications, interviews, assessments, candidate communication, and offers.

Grocalo (S26) is an AI brain that runs content for creators. We understand their audiences, using video understanding and deep platform analytics to bottle up the taste behind each creator and personalize and distribute content to creator specific audiences. Grocalo generated 2B views and gained 4M followers for our creators in the last 2 months. Some of our clients include Jimmy O. Yang (Comedian, 11M followers), King Bach (72M followers), Leenda Dong (28M followers), Steven He (30M followers), Sheena Melwani (18M followers), and Jeannie Mai (TV host, 6M followers). Content should be personalized and data-driven. We’ve developed the most advanced AI brain replicating viral content for any given audience.

Billions of people need tourist visas to travel the world. We use AI agents to prepare applications, verify documents, secure appointments, and handle the visa process end to end.

Hardware teams burn weeks on procurement. An engineer needs a part. Someone emails five distributors, chases quotes, gets an approval, wires the money, tracks a shipment across three carriers, clears customs, and then nobody knows where the box is or what's actually on the shelf. Waybill runs that entire loop. Send us a part, a spec, or a BOM. We source it, pull quotes, route approvals, pay the supplier, handle freight and customs, track it to your dock, and keep your stock count updated. Take your supply chain for granted. Built by a team that's seen it at LAT Aerospace and WareIQ (YC S20).

Palisade spins up a personal sales agent for every single visitor to your website. Marketplaces like trading card platforms, vintage stores, and short-term rental operators sell more when each customer works with a personal agent that remembers them.

Mochi is an app to watch and create anime microdramas: fast paced shows with a cliffhanger every minute. We produce originals with AI, collaborating with writers from Marvel, Cartoon Network, and Toei Animation, and our users can also create in app too - with over 500 episodes created each day from 3,000+ creators.

PRINCEPS is the first purpose-built insurance company for the trillion-dollar compute buildout. We underwrite SLA, GPU residual value, and outage risk, and price the coverage that unlocks cheaper financing for data centers and neoclouds.

Physical AI — robots and world models — is bottlenecked on one thing: diverse, real-world data at massive scale showing how humans actually do work in the physical world. It was never written down, and you can't buy it, because no one has ever captured it. Only real local experts, the people who do this work every day, can produce data this authentic and valuable. DeepReach builds the network that reaches them. We design and manufacture wearable stereo capture devices, then place them with local data partners who run collection as their own business — in warehouses, workshops, farms, kitchens and repair shops. They own the local relationships; we supply the hardware, the software platform, the quality pipeline and the payments. Anyone can run a data business. That structure is what produces diversity. Instead of thousands of hours inside one environment, we deliver hours spread across thousands of environments — which is what actually makes robot policies generalize. 475 devices in the field and 100+ data partners are live across 7 countries, adding new partners every week. They've collected nearly 150,000 clips in the past three months, with volume roughly doubling month over month. Our data is in production with multiple frontier model and robotics companies, and we're scaling to 10,000+ devices across 50 countries.

TovenAI builds a platform of AI agents that handle manual, data-intensive work for compliance teams at institutional trading firms, with six agents currently live. Our customers range from specialist firms to large global institutions, with our agents supporting multiple compliance workflows at a top-10 institutional brokerage. With prebuilt connectors to more than 30 systems—including Bloomberg, Cloud9, and NICE Actimize—firms can onboard to our platform and evaluate results using their own data in less than a week.

Our first model, Atom 1, pre-trained on the internets video, and fine tuned for physics. It has been action conditioned, so you can simulate robot actions within it. This lets Robot Labs train their robots using GPUs instead of relying on human collected manual data that is slow and expensive. In unseen and hard to replicate environments, this is the only path to getting ANY training data.

Tenor enables domain experts to build, run, and scale AI-native service businesses. The next generation of successful white-collar service businesses will be built and scaled around AI from the ground up. These companies need more than capable AI models. They need a company data layer, governed workflows that AI can execute, and harnesses that continuously improve based on outcomes and decision checkpoints. Tenor is building this infrastructure so millions of AI-native businesses don’t have to build it themselves.

Simulithic continuously uses your production product like your real users do. We learn representative user journeys and run agents across different devices, browsers, account states, and environments to find failures that traditional automated tests miss. When something breaks, we reproduce it and alert engineering before they hear about it from a customer.

Mosaic gives teams and their coding agents shared memory across every session, so everyone can understand what happened, why decisions were made, and pick up where someone else left off. We started as a real-time coding environment where multiple people and their agents can work together live. It went viral, defined the multiplayer AI category, and inspired frontier labs like Anthropic. Together, we’re building the infrastructure for people and agents to share context and work together.

Erinys provides the technology, intake, back office, and client acquisition needed to launch and scale an AI-native law firm. Lawyers own their firms and make every legal decision; Erinys handles everything around them.

VIM connects to the entire cell: PLCs, robots, CNC machines, sensors. When a cell faults, VIM finds the cause, stages the fix, and the operator approves with one click. When a part drifts, VIM catches it seconds after the cut, inside the machine, and recommends the correction. Recovery drops from 30 minutes to under two, saving more than $15,000 per fault in large factories.

Audun automates debt collection.

Qlo builds AI agents to run commercial insurance underwriting. We start by fully automating the operational work around risk decisions, become the system of record, and earn autonomy workflow by workflow toward the autonomous AI underwriter. We’re rebuilding underwriting infrastructure from the ground up so human underwriters and AI agents can share the same accounts, rules, documents, permissions, and workflow state.  We believe every commercial insurance program will eventually be built and operated end to end by AI agents on Qlo.

We are building robots that can work autonomously in existing wet labs. Unlike traditional lab automation, which requires dedicated equipment and fixed workflows, our robot moves between workstations, manipulates existing scientific equipment, transports lab materials, and executes experiments using the same lab infrastructure as a human technician. We make the robots easy to manage through natural interfaces like Slack, email, and phone. Our goal is to make deploying robots in wet labs as easy as onboarding a new employee, and to accelerate scientific research!

Developers don't run one coding agent anymore. They run fleets of them — for hours, sometimes days — across laptops, servers, and sandboxes. Keeping track of that work is the new bottleneck: which agent is blocked, which one finished, which terminal is it in, and why did everything die when the laptop closed. Herdr is the open-source home for that work. A background server owns the agents' terminal sessions on each machine, so the work survives disconnects, closed lids, and dropped SSH. Herdr detects each agent and turns the chaos into an attention queue — working, blocked, done, across every project — so you look only when an agent needs you. Every client is just a view: the bundled terminal UI, SSH from another machine, your phone. Close one, open another; the work never stops. Software can drive it too: a CLI, a socket API, and a plugin marketplace that passed 500 community plugins in its first month. The runtime is Apache-2.0 and stays open. Four months after launch: 25k GitHub stars, 340k downloads.

An agent is LLM + harness: We work purely on that second component. We do research and engineering to produce the most capable and efficient harness. Our harness has 20k stars on , and has $1m/month of inference spend

An AI platform that connects commercial debt advisors with mandate matching private credit funds.

Click builds useful services that meet users right inside ChatGPT and Claude. We're starting with a research service that provides external context that the built-in web search misses - like data from professional & social platforms, marketplaces, financials, and more. It makes research on people & companies even deeper with specialized, source-backed context beyond built-in web search, while enabling new tasks like comparing live flight fares right inside the chat.

Arbital lets you trade perps, memes, stocks, and run market-making strategies from one place. In our first 7 months, 2,700 traders have traded $1.35B in volume through Arbital, and we're now doing $435M/month. We're building towards a social, mobile-first trading app that brings tokenized equities, crypto, and perps to everyone.

Agent FM is a desktop app that gives engineers one group chat to hear and steer their coding agents. Instead of manually bouncing between different claude code and codex sessions, and combing through walls of text to monitor agents, engineers just tune in to Agent FM. Agents share important progress updates, blockers, assumptions, and decisions in the group chat. Engineers get live text and audio updates and respond right from the chat.

Models are trained on the entire internet, but most of what happens on Earth is never written down. We turn those signals into training data so labs can make models better at science

Omanta is a personalized research lab for patients who have exhausted standard options, want to prepare proactively for recurrence, or are living with an unresolved diagnosis. We direct the full operational infrastructure, personnel, expertise, and technology of a large research program toward understanding and addressing the challenges of individual patients across oncology, rare disease, and undiagnosed conditions. For clinicians, we act as a collaborative partner, providing a living roadmap for ongoing patient care built on a rigorous and evolving scientific evidence base. We fully operationalize patient-specific research programs, covering tissue logistics, diagnostic follow-up, data integration, multiomic analysis, therapeutic strategy development, and more. Omanta brings context and clarity to complex cases, helping clinicians see more of the scientific picture as they decide how best to care for their patients.

We builds foundational AI models for chemistry. Almost nothing you buy is a single chemical. Products like datacenter coolant, GPU thermal paste, paint, and glue are formulations, which are mixtures of around ten ingredients each, and demand for them has grown quickly because of AI and EVs. Designing a new formulation is essentially a search problem, because there are more possible mixtures than anyone could ever test, and none of them can be predicted in advance. As a result, bringing a single formulation to market today takes three to five years of trial and error in a lab. Our models predict how a mixture will behave far faster than the standard methods used today, which lets us design new formulations in weeks rather than years, at a fraction of the cost. To prove this, we used them to invent three chemicals that never existed before, including a PFAS-free coolant for datacenters, and we have since synthesized and patented all three. We are already working with some of the largest manufacturers to design formulations for them, and we are building our own lab to generate the data that will train our next models.

IMPACT builds autonomous interceptor drones that ship in sealed containers. The box sits at the site it protects, data centers, power grids, airports, bases, with no crew on the pad. When sensors cue a hostile drone, an interceptor pierces its own frangible lid, launches, and rams the target, guided by onboard vision that keeps working when GPS is jammed. Legacy effectors cost $1M+ per shot against $30k threats; ours cost less than the threat and scale with the swarm, the same class of interceptor already downing Shahed drones over Ukraine. Sites subscribe to protection instead of buying missiles, hardware, reloads and monitoring included: Air Defense as a Service. 180M+ USD in signed letters of intent.

The next billion software users are AI agents, yet agents still can't act on their own: every paid tool they need runs through a human making accounts, managing API keys, and guessing which provider is best. We are the capability marketplace built for agents: one MCP and one balance through which agents find, pay for, and use APIs, data, skills, other agents, and software at runtime, with every request routed to the best provider based on benchmarks from real tasks and outcome feedback from the agents themselves.

hiloop helps teams train agents for tasks where general models are not good enough. Give us a task, your current agent or model, and an evaluation. hiloop runs an autoresearch campaign across data, SFT and other post-training methods, continual learning, prompts, tools, harnesses, and systems, then returns the best verified improvement. It runs hosted or in your cloud. We provide the research system around models: persistent memory, full experiment lineage, compute orchestration, and statistical verification. We’re starting with agent and model training, continual learning, and optimization. Reach out to us for early access at founders@hiloop.ai.

Executor.sh is an MCP gateway that allows you to sign in once to all of your integrations and use them with any client. We enable you to connect your agents to anything (MCP, GraphQL, OpenAPI) so regardless of what you're trying to connect agents to you're able to. If you're trying to scale agents to access all of your production services, data, etc, you need Executor as a unified management layer.

We use AI agents to manage short-term rental properties by running operations completely autonomously. We cut traditional human management fees in half so owners take home 20% to 30% more revenue. And we operate with near-zero boots-on-the-ground so we can scale nationwide with software margins and at venture speed in a traditionally physical industry.