Infrastructure Startups funded by Y Combinator (YC) 2026

Fivetran automates data movement out of, into and across cloud data platforms. We automate the most time-consuming parts of the ELT process from extracts to schema drift handling to transformations, so data engineers can focus on higher-impact projects with total pipeline peace of mind. With 99.9% uptime and self-healing pipelines, Fivetran enables hundreds of leading brands across the globe, including Autodesk, Conagra Brands, JetBlue, Lionsgate, Morgan Stanley, and Ziff Davis, to accelerate data-driven decisions and drive business growth. Fivetran is headquartered in Oakland, California, with offices around the world. 

The AI-native observability platform for fast-moving engineering teams. Backed by tastemakers from the world's top AI companies: Vercel, Graphite, Daytona, Browserbase, LangChain, Mastra, Replit, and more.

Infinity is the world's first cloud-native OS built for a multi-agent, GPU-native future. We stream heavy GPU-accelerated applications like robotics simulators, CAD tools, AI workloads directly in browser tabs with dedicated per-app compute and sub-3-second cold starts. No VMs, no local setup. Just a URL.

Building the communication infrastructure needed for fully autonomous agents

Sandbox infrastructure for AI agents, with full-environment forks and snapshots across files, processes, memory, and databases.

AI companies selling into legacy industries can't go live because their customers' systems of record are Windows desktop apps with no APIs. The only way in is clicking through the UI, and it breaks constantly. Minicor is a platform for building self-healing desktop automations at scale. Speak the automation into existence through your favourite coding agent via our MCP, or to us directly, and get an API endpoint to trigger it. One API call triggers a full desktop workflow on a Windows VM. On-premise, cloud, or Citrix. Video replay, error logging, and scaling built in.

Compression middleware that removes context bloat in milliseconds, lowering costs and improving end-to-end latency. Compression is especially effective across natural language workloads. In a blind LLM arena case study with one of our customers, compressed requests increased user preference, lowered costs, and lifted purchase volume by 5%.

AI SRE agents that automatically learn each customer’s system so they work just like an in-house engineer.

Terminal Use is an orchestration platform for background agents. Purpose-built for agents that use filesystems. Our platform is CLI-first, making it easy for your coding agents to experiment and continuously improve your deployed agents.

Piris Labs offers a full-stack inference service that eliminates the AI data movement bottleneck. By pairing proprietary photonic hardware with a vertically optimized software stack, we minimize the "memory wall" associated with expensive GPUs. This allows us to deliver the same performance as traditional clusters at a fraction of the cost. Our technology improves effective FLOP utilization and reduces latency, finally making the unit economics of trillion-parameter models sustainable. Founded by a team of MIT physicists and Meta AI experts.

Cascade helps companies take their proprietary data and workflows to align models for their use cases, resulting in higher throughput intelligence that works better, faster, and cheaper.

Wayco is building a unified data intelligence layer for medical treatment of legal cases. From the first intake to instant settlement.

We enable AI voice agents to collect payments over the phone through a single API call, handling card processing and PCI compliance across all payment gateways

Your agent processed a refund without looking up the order ID, costing you thousands. You only found out three hours later from a support ticket. Evals, output scoring, and observability can reduce the likelihood of mistakes like these occurring - but there's no solution that inspects and prevents an action as it’s about to execute. Salus does that. We’ve built an API that wraps around your agent and checks its actions at run time, blocking incorrect ones and providing immediate feedback to guide retries. Kevin and Vedant were roommates at Stanford, where they both studied computer science.

Autumn is building the first real-time signal intelligence platform for GTM teams. We monitor posts, commits, blogs, and announcements, surfacing buying signals the moment they appear. Define your ICP and the signals that matter, and we deliver a condensed, real-time feed filtered by intents.

Get your personal OpenClaw instance on the cloud and connected to your Slack or other messaging app in 3 minutes. Pre-installed security features and common skills.

Oximy helps enterprises understand and manage AI usage across their workforce. Used by security, finance, and transformation teams to track adoption, control spend, and manage governance as AI scales.

APIs weren't built for agents. Orthogonal fixes that. We enable agentic payments so any agent can instantly discover, access, and pay for hundreds of APIs. No subscriptions, no sales calls, just pay per use. API providers list once and get paid every time an agent calls their API.

Backed by top engineers from OpenAI, EQT Motherbrain, and Palantir to give autonomous AI taste. Our first commercial product is for the literature industry with a focus on school libraries. It captures and analyze unstructured (and pre-Librar unattainable) data using it to more than double reading rates at schools. Fastest growing library tech company in history.

Moda is the reliability & monitoring layer for agents. It surfaces patterns across agent hallucinations, laziness, forgetfulness, and tool call failures. While also providing analytics on user frustration, net promoter score, retention, and churn rates. In the next 10 years, with more AI agents spawning and trying to get PMF, developing an agent that actually works for users is critical. Everyone has access to the same models, thus the ones that win on a product level will be the ones who learn fastest from real usage. Moda is that learning layer.

Compresr provides an API that compresses LLM context without losing what matters. It’s a drop-in for agents and RAG that cuts token costs and improves accuracy.

We are building the world’s largest video library. We've aggregated billions of videos into a searchable index and use agents to find and label the exact datasets a lab needs on demand. If a lab needs 100K hours of cooking videos where someone is holding a pan, with reasoning annotations on top, our agents search the index, extract the matching subset, route it through our labeling pipeline, and deliver a custom dataset in days, not months.

Cumulus Labs is a fast multimodal inference provider, purpose-built for AI teams who want faster performance, lower costs, and zero infrastructure work on fine-tuned & open source models. Most teams today are stuck choosing between bad options. Self-hosting inference means wrestling with configurations and babysitting infrastructure that slows/breaks at scale. Big providers like Fireworks are convenient but extremely expensive and idle GPUs. Cumulus ships Ion, a proprietary inference engine that run LLMs, VLMs, and audio/video gen with high performance and lower cost by specifically optimizing for NVIDIA Grace chips.

Chamber puts your AI infrastructure on autopilot, and saves your machine learning engineers hours of manual effort. Our agents continually monitor, detects failures, provide root-cause analysis, resolve issues, and optimize AI workloads and scale across clouds. It operates like an autonomous infrastructure team, helping save your research and engineers hours each day, and debugging workload performance issues. Your ML teams move faster, infra waste drops, and GPU bottlenecks disappear.

Edge AI is inevitable, but shipping it is painful: every device class behaves differently, runtimes vary, models are huge, and performance collapses under memory/power constraints. RunAnywhere turns that into an enterprise-ready workflow: one SDK to run models on-device, plus a control plane to manage models, enforce policies, and measure outcomes across thousands of devices.

Mantis is a digital twin company that combines LLMs with high-fidelity physics simulations in order to convert rare and difficult-to-access human behavior data into predictive models.

Didit is an all-in-one identity platform that lets humans prove who they are starting with a face scan. It powers the fastest identity verification in the market, fights fraud by default, and unifies all identity checks with simple pay-per-use pricing.

Luel is a sourcing and licensing platform for rights-cleared multimodal training data at scale. We work with frontier AI teams to provide high-quality bespoke data collections and off-the-shelf datasets.

Captain delivers the most accurate file search engine built for AI agents. We’ll index data from the sources folks already use like S3, SharePoint, and Google Drive, and easily scale multimodal, petabyte-level content search. We’re the Snowflake for Unstructured Data. Captain tops the Open-RAG-Benchmark with over 20% higher accuracy than standard RAG pipelines. We achieve this through robust data processing techniques like embedding normalization across modalities, ensuring that representations cluster by semantic content rather than data type.

Castari lets developers deploy AI agents in secure, autoscaling sandboxes with one command. We handle tool/MCP connectors, snapshots, and observability so teams go from prototype to production in hours instead of weeks. Developers focus on building agents, Castari provides the autoscaling sandbox infrastructure to ensure your agents and its tools are secure.

Hyperspell (YC F25) gives AI agents memory. It connects to tools like Slack, Gmail, Notion, and Drive so agents can recall, reason, and remember across company knowledge. Developers use Hyperspell’s API to turn disconnected agents into AI coworkers that understand their work. Conor and Manu founded Hyperspell after building their own workplace agent and seeing how limited AI is without memory. They have over 15 years of experience in machine learning and have scaled API-based products to $30M ARR.

AI researchers should be pushing the boundaries of what's possible with new architectures and training methods. Instead, they waste weeks configuring cloud infrastructure, debugging distributed systems, and optimizing their GPU code. We know because we lived it: While training our own models across thousands of GPUs earlier this year, we spent more time fighting our infrastructure than doing actual research. That's why we're building two things. First, Elastic Cloud: a managed platform that automatically finds the cheapest GPUs across all providers, handles spot instance preemption, and cuts compute costs by up to 80%. Second, automatic kernel optimization that makes training code run faster by modeling hardware topology, often beating hand-tuned implementations. The problem is that getting high performance across different hardware is genuinely hard. NVIDIA's CUDA moat exists because writing fast kernels requires deep expertise. Most teams either accept vendor lock-in or hire expensive kernel engineers. Our goal is to break the CUDA moat. The compute bottleneck is the biggest constraint on AI progress. NVIDIA can't manufacture enough GPUs, and their monopoly keeps prices astronomical. Meanwhile, AMD, Google, and Amazon are shipping capable alternative hardware that nobody uses because the software is too hard. We're breaking that moat. If we succeed, anyone will be able to train state-of-the-art models without thinking past their PyTorch code.

Amika is infra to build your software factory. We give your team sandboxed AI coding agents in the cloud: the same infrastructure Ramp, Coinbase, and Stripe built in-house. Kick off work from a web UI, CLI, Slack, or API. Use your preferred coding agent (Claude Code, Codex, etc.). Each agent understands your codebase, runs autonomously, and ships real PRs with live previews of the apps it changed. Use it as your daily driver or plug it into your own code-gen pipeline via API.

Dome makes it easy to build on prediction markets like Polymarket and Kalshi. We provide the developer infrastructure to access, analyze, and build on prediction markets. With our unified API, developers can access live and historical data, including granular datasets not available natively, across multiple platforms at once. Dome makes it simple to trade, embed market data into products, and deploy strategies across multiple platforms through one interface.

S2 is an API for durable streams. We make working with streaming data dead simple and reliable. The more we worked on data systems, the more we felt like there was a missing building block. The seamless experience of object storage simply did not exist for durable streams – so we set out to fix that! S2 reimagines streams as an unlimited and access-controlled web resource. Like if Kafka and S3 had a baby. - Building agents? Use granular streams to persist context in real time, make workflows auditable, and coordinate between agents. - Publishing fast-moving data? Streams support high fanout and can be accessed directly over the internet, so they are a great fit for broadcasting real-time feeds. - Sandboxing? Emit to per-instance streams, and read history or live events just as easily. - Local-first and multiplayer experiences? Propagate updates reliably and efficiently. Stop dealing with clusters, and start streaming.

Brickanta is building the AI-native operating system for construction, starting with the pre-construction workflows that determine the outcome of entire projects: bid analysis, cost estimation, and procurement. Our platform combines state-of-the-art AI with real project data, standards, and construction best practices. This enables construction, contracting, and real estate companies to identify gaps, risks and opportunities earlier, and to produce project and procurement documentation significantly faster and more efficiently.

1. Multi-model Agents SDK: build production-grade tool-calling agents in 5 lines of code using our open-source, vendor-agnostic SDK. Connect multiple models across providers (eg. Opus 4.6 + Gemini 3 Flash + GPT 5.4) within the same agent to optimize your agentic workflow's cost, latency, efficiency, and performance. 2. Agents-as-a-Service (AaaS): serve your agent or service as a hosted endpoint that anyone - including OpenClaw and Claude Code - can call.

The first advertising infrastructure designed specifically for AI apps. Seamlessly integrate contextual brands & products that enhance user experience while generating revenue to pay the inference bills.

Truth Systems provides a compliance agent to govern the use of generative AI. It translates operational policies into intelligent, real-time guardrails that monitor every AI interaction. This empowers companies to proactively block non-compliant actions and align access to AI tools with user competency. By eliminating the risks and operational blind spots associated with uncontrolled AI adoption, our platform enables enterprises to fully leverage the technology's potential without compromising security. We are establishing the new standard for AI governance, building a future where every professional can innovate safely and confidently.

Kernel is crazy fast, open source infra for AI agents to access the internet 🧠🕸️ - Built on unikernels for crazy fast cold starts and low resource usage - Sub-150ms cold starts on managed headful browsers - Built-in stealth mode with residential proxies and automatic CAPTCHA solving - Full observability: session recording, live view, and full logs - Persistent sessions that maintain cookies and auth across invocations - Native support for all browser and computer use frameworks - SOC 2 compliant and HIPAA-ready Trusted by Cash App, Rye, and 1000+ others. Backed by Accel & Y Combinator (S25).

DeepAware builds an AI-driven automation system for GPU-intensive data centers. Our reinforcement-learning scheduler, real-time market integration, and unified dashboard slice energy waste by up to 30%. Coming soon: autonomous “robot-hand” inspections and maintenance to enable 24/7 operations with minimal staff. More info: https://deepawareai.com/ Jobs/Internship: https://www.deepawareai.com/careers

Manufact provides open-source dev tools and infrastructure for MCP to help dev teams quickly build and deploy MCP Servers for AI agents & MCP Apps for ChatGPT and Claude. We developed the mcp-use SDK, which has over 5M downloads and 9,000 GitHub stars, and is used by 20% of the US 500. Create MCP servers/apps in minutes, connect your GitHub repo, and make them immediately available to AI agents and ChatGPT.

Pangolin is an open-source, identity-based remote access platform built on WireGuard that enables secure, seamless connectivity to private and public resources.

You built the demo in a weekend. Now you need auth, a prod-grade database, real-time events, AI observability, cron jobs, email, monitoring… and you needed them yesterday. We spent a decade at our previous startup, building a platform while scaling to millions of users and customers like Meta & Netflix. Now we put that into an open-source framework, so others wouldn’t have to do the same from scratch. Modelence is a batteries-included production ready platform for agentic development that abstracts away boilerplate so you can just focus on building your product logic and deploy it to production without worrying about infrastructure. Shipping production apps is much harder than building a prototype that runs locally and 95% of all production apps share the same building blocks. We did a massive amount of work on our previous platforms that was not specific to our product, and we’ve created Modelence to abstract that away: - Authentication - Database setup - Hosting / CDN - AI integration (LLM observability, prompts) - Real-time events - Cron jobs - Email service - Monitoring - Analytics - Admin dashboards Andrej Karpathy recently posted about this same exact problem: https://x.com/karpathy/status/1905051558783418370 and explained it further in his YC AI Startup School talk: https://youtu.be/LCEmiRjPEtQ?feature=shared&t=1940

Luminal builds an ML framework and compiler that generates GPU code. Our stack 10x's model speed while simplifying deployment and cutting idle GPU costs Github: https://github.com/luminal-ai/luminal Discord: https://discord.gg/APjuwHAbGy

AgentMail is the email inbox API for AI agents. It gives agents their own email inboxes, like Gmail does for humans.

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.

Aravolta provides a single pane of glass software for data centers to increase uptime, reduce costs, and improve performance. A single utility node onboards every asset within an hour and detects hardware failures, hotspots, and other issues. It also generates reports on important metrics like Power Usage Effectiveness (PUE), energy metering, resource utilization, and much more.

ParaQuery is a fully-managed GPU-accelerated Spark solution providing double the performance at half the cost compared to solutions like Databricks and BigQuery. It is fully Spark-compatible, cloud agnostic, and has seamless integrations everywhere, all without vendor lock-in. ParaQuery makes it trivial to run large SQL and Spark workloads efficiently and serverlessly, without any data migrations.