Reinforcement Learning Startups funded by Y Combinator (YC) 2026

We build specialized LLMs for your business’s specific workflows and use cases, then continuously hone them against your success metrics, capturing your proprietary know-how in the model so it gets more valuable and harder to copy as you grow.

GrazeMate builds autonomous drones that herd cattle. On command, our drones fly to a paddock, position themselves around the mob, and move them where they need to go. What used to take a full day of helicopters, motorbikes, and horses now runs on a schedule. We work with some of the largest cattle ranches in the world. While the drones are herding, they're also estimating animal weights, measuring grass biomass, monitoring water levels, and flagging sick animals. We're building physical AI that lets a grazier manage thousands of head across millions of acres from their phone.

Haladir is the operational AI layer for logistics. We unify data across WMS, TMS, OMS, etc., deploy event-driven agents with execution authority, embed solver-grade optimization into 3PL and distributor operations, and produce RL environments for frontier AI labs. We help logistics operators embed observed AI at every level of the supply chain, helping make insights and deliver results. Today's AI brought intelligence. The next frontier is judgement. We define operational superintelligence as AI that consistently makes maximally-optimal operational decisions in complex environments. The first component is speed: continuous decisions that take operations managers and OR analysts weeks to make, in seconds. The second is reliability: every decision is guaranteed to satisfy operational constraints. The third is scope: optimize across thousands of constraints no human or team could possibly reason about.

Cortex AI builds the world’s most diverse and large-scale real-world workplace robot & egocentric dataset — where the physical world becomes the next training and evaluation set for embodied AI. We power frontier labs developing robotics foundation models and general-purpose robots by providing the data they need: 1️⃣ Egocentric Data — real-workplace human video with hand/body pose, depth, and subtask labels. 2️⃣ Robot Data — trajectories collected from manipulators and humanoids in real industry settings. 3️⃣ Human-in-the-Loop Rollouts & Evals — real-world deployments with remote operators who recover robots when they fail, capturing data that feeds back into training and continuously improves models. Additionally, through the Cortex Marketplace, workplaces get paid to host data-collection and evaluation sessions, while labs access the in-the-wild data that truly matters. This draws on Lucas’s previous experience as co-founder of Carousell, a C2C marketplace that scaled to a $1B+ valuation.

We work with frontier AI labs to help train their agents to become AI research scientists

Topological is developing physics-based foundation models for CAD optimization. We help hardware teams iterate at the same speed that software teams do. Our technology is accelerating the engineering workflow with AI and scales design and optimization to identify the ideal designs for complex problems given their physical constraints with enhanced speed and performance. Our first model, UToP-v1, is a SOTA topology optimization model that understands physics, geometry, and manufacturability. It can generate the most efficient design given a problem’s physical requirements. It has <5% compliance error and is 1930x faster than current methods. We're reimagining mechanical engineering and computational design with precision spatial AI.

Idler builds reinforcement learning environments that teach AI models to code at expert human levels. We create training environments based on real-world coding scenarios that prepare models for the complex challenges they'll face in production.

Janus automates AI evaluations by using high-fidelity simulation environments, catching failures in reasoning, compliance, tool usage, and performance. The resulting datasets benchmark products and feed post-training loops to continuously improve performance over time.

Aviro builds RL environments for long-horizon tool use across ML research, live web, and enterprise knowledge work. We partner with frontier labs and Fortune 100 companies to train models as high-stakes operators and perform research-grade work.

Built to advance human taste to the frontier, TypeOS is the best way to write with AI.

We're creating reinforcement learning environments for training frontier models.

Powering frontier AI labs with real world MCP environments and complex, long-horizon agentic tool-use data.

Freesolo works with companies to encode user-trajectory knowledge into specialized models that outperform the state of the art at much lower latency and cost.

HUD (YC W25) is developing agentic evals and RL environments for Computer Use Agents (CUAs) that browse the web for frontier AI labs. Our CUA Evals framework is the first comprehensive evaluation tool for CUAs. People don't actually know if AI agents are working reliably. To make AI agents work in the real world, we need detailed evals for a huge range of tasks. We're backed by Y Combinator, and work closely with frontier AI labs to provide agent evaluation and training infrastructure at scale.

At Agentin AI, we build Agents that move data and take actions across enterprise systems, like Salesforce, NetSuite and SAP. These agents are difficult to build because each enterprise heavily customizes their systems but we solved that by training our Agents to learn and adapt from failures, applying reinforcement learning techniques we developed.

TrainLoop makes it effortless for developers to supercharge LLM performance through reinforcement learning.

Osmosis helps companies use reinforcement learning to fine-tune open source models that outperform foundation models.

Choose a coding agent harness, model, and task dataset and optimize context and prompts to get the best performance for long-horizon tasks

We work on benchmarking and improving the long-horizon capabilities of AI Agents. We build out specialised environments to improve the long-horizon capabilities of browser and computer use agents.

Always-on AI agents for 1-1 personalization at scale

Velos helps non-technical operations teams automate complex, manual back-office tasks with AI workers instead of overseas teams. Unlike traditional robotic process automation (RPA) platforms like UiPath, Velos automations use machine learning to reliably handle ambiguities in their tasks, eliminating the need for an army of maintenance engineers and consultants to build and maintain your automations. We're automating the repetitive work people hate to do.

Founded in 2022, Atmeto was started as a place to develop and apply machine learning to solve the world's biggest problem—climate change. Our current priority is getting the grid to run on 100% clean energy, which is currently limited by battery storage (specifically, the algorithms that control them). We're redefining these algorithms to unlock gigawatts of untapped energy storage capacity, enabling the grid to run on more clean energy from wind and solar.

rct AI is providing AI solutions to the game industry and building the true Metaverse with AI generated content. By using cutting-edge technologies, especially deep learning and reinforcement learning, rct AI creates a truly dynamic and intelligent user experience both on the consumers’ side and production’s side. The founding team ever built a company, Raventech together and helped make it acquired by Baidu (NASDAQ:BIDU) in 2017.

Sepal is a data research company on a mission to advance human knowledge and capabilities through safe AI. We partner with the world’s leading AI labs and enterprises to help their models get better at the tasks people actually want them to do. We’ve built a Cloud-Native Agent Dataset Factory which turns the process of generating evaluation and training data from manual, inconsistent, and labor-intensive into something automated, standardized, and scalable. Sepal AI was founded in 2024 by engineers and operators from Vercel and Turing. We went through Y Combinator, raised several million dollars from leading investors, and already count multiple Fortune 500s and top AI research labs as paying customers.

Resonance hyper-personalizes MarTech campaign content and automatically refreshes and stores high performing content for re-use.