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. 

An open-source toolkit to capture traces, evaluate cheaper models against benchmarks, and ship specialist routes you own. Capture traces from LLM production workflows with a single install that deploys within coding agents you already use. Hosted infrastructure is optional. Evaluate the captured traces and set a benchmark for success. Every future model switch meets or exceeds it in A/B testing. Train and fine-tune a new model on prompts and weights you always own. Start locally and scale into cloud-hosted processes as you see success. Deploy a new model only when the held-out eval is beaten. Serve it wherever you want. Production data feeds back into training and compounds performance over time. Test. Learn. Deploy. Repeat.

Rindler turns any website, including sites without APIs, into a deterministic API that AI agents can reliably use. It handles logins, 2FA, and bot detection, giving agents clean structured data and dependable actions instead of raw HTML, with robust maintenance when sites change. Rindler is agent-agnostic and built on the open MCP standard, so it works with any agent. For operators: get your team out of portals and back to the work that matters. For agent builders: let your agents act on the real web quickly, cheaply, and reliably on every run.

We are building the identity and communication layer for AI agents: giving agents their own email, phone, iMessage, and internet address. Every interaction flows through Inkbox, so agents are enhanced with multi-channel context.

Edviro helps facilities managers at large buildings save on their energy bills. Facilities managers are overwhelmed with dashboards, alarms, and analytics for hundreds of boilers, HVAC units, and heat pumps across their buildings. Edviro continuously monitors and optimizes buildings using energy world models to detect anomalies, simulate interventions, and suggest the best options to the facilities manager. Once the changes occur, we create a comprehensive M&V report to ensure savings show up on the bill. Our tools also allow institutions to maintain detailed service history & equipment logs, and perform maintenance with AR.

Definite builds AI agents that generate the reports banks and financial institutions file with their regulators. Before any number lands in a filing, our verification engine checks it independently. Every line gets recomputed from ledger records and checked against a versioned rulebook, and wrong outputs go back to the agent with the reason, like compiler errors. They don't ship. We met our first year studying computer science at the University of Waterloo, and interned at Meta, Optiver, and BitGo, places where one unverified number in a filing has real consequences. At BitGo, attestations proving customer assets matched the ledger were assembled by hand every period. At Optiver, daily regulatory numbers were rebuilt manually because nothing downstream took them on faith. Today a controller pulls data from the core system into Excel and maps it to the report line by line. By the regulators' own estimate, one quarterly filing takes weeks. The software banks buy for this validates formatting, not truth: a loan mapped to the wrong schedule line passes every check it runs, and an executive personally signs the result. This is hard because verification has to be independent of the model doing the work. Recomputing every number from source records is the only check a regulator or auditor will accept, and it's why DeepSeek v3 with our engine beats GPT-5 on public reporting benchmarks. Every regulated institution files these reports, forever. Whoever proves the numbers owns the layer the filings, the audits, and eventually the books themselves depend on. We build it, and the agents that run on it.

An applied research lab building AI that is 90% cheaper while matching the performance of frontier models. We do this by simulating reality faster and more accurately based on the technology self-driving uses to get near perfect reconstruction fidelity.

Dialogus builds voice agent infrastructure for enterprises. Most companies can demo an AI voice agent, but getting one into production is hard. Enterprise agents need to connect to phone systems, internal tools, databases, CRMs, messaging channels, human escalation flows, monitoring, and compliance processes. Dialogus provides the infrastructure to deploy production-grade voice agents that don’t just talk but complete real workflows. Our platform lets enterprises launch agents that collect information, validate it against internal systems, update records, send follow-up messages, and escalate edge cases to humans.

We write the algorithms to turn brain cells into compute.

We source high quality tasks and data to train the next generation of computer use AI models.

AI agents are starting to act in the real world, but they can't reliably understand it. Geospatial data is complex, fragmented, and unstructured. Ask a model a specific question about a specific place and it guesses. Our API and MCP give agents cited answers about any location. Our mission is to index every inch of the earth, and make it as queryable as the web.

machine0 is a CLI that lets you create, provision, and snapshot cloud VMs. `machine0 new my-vm` spins up a VM with dedicated CPU, RAM, and optional GPUs, plus a static IP and HTTPS endpoint. The tools agents need (e.g. Node, Python, Docker) and the agents themselves (e.g. Claude Code, Codex, OpenClaw, Hermes) come pre-installed. 99.99% VM uptime SLA across four regions. Agent workloads are moving from ephemeral to always-on. A coding agent debugging a complex issue runs 4-8 hours. OpenClaw runs 24/7. machine0 is the environment in which these agents run.

Context.dev gives AI agents structured data from any website through a single API. We help developers build smarter agents & products that depend on accurate, fresh web data. If you need structured data from the internet, you need Context.dev Proud to power agentic products at Mintlify, Super, Vizzy, Klarna, and 280 other companies.

Miso Labs is building the world’s most emotive foundation models for voice. Our goal is to pass the voice Turing test.

RightNow AI is a research lab building GPU infrastructure that lets teams own their AI stack instead of depending on closed-source APIs. Our platform RunInfra takes any HuggingFace model, auto-generates optimized GPU kernels, and deploys it serverlessly with pay-per-token pricing RightNow AI lab: https://rightnowai.co RunInfra platform: https://runinfra.ai.

Coding agents in the cloud don't work for majority of teams who require native capabilities; they lack XCode for iOS, Emulator for Android, Unity for game development teams. We are on a mission to cloudify every local development utility so that regardless of where it runs, your agent can compose an ideal set of capabilities on the fly so you don't need to run it on your laptop. Today, we provide remote services such as XCode, iOS & Android simulators to enable coding agents running in any sandbox to be able to build and iterate over mobile apps, too. Replit, Rork, Momentic, Minitap and more agent companies have built mobile development and testing experiences on Limrun platform. Coconote (Quizlet), SorceJobs (W25) and more companies with mobile apps use Limrun with their cloud agents, merging PRs without having to check out the code locally.

Wato gives AI agents shared memory, reusable workflows, connected tools, and living artifacts so work compounds across a team instead of disappearing into chat threads. Teams use Wato to give every agent access to trusted company context and turn useful runs into knowledge the next agent can build on.

The $2T global telecom industry was built for humans. Agents can't act in the real world today because without a phone number, they lack identity. AgentPhone gives every AI agent its own phone number to reach people and businesses through messages and calls.

Expanse unlocks wasted GPU capacity. We recover idle compute through three capabilities: resource prediction (right-sizing job submissions before they reach the scheduler), optimisation suggestions (code and config changes researchers can apply themselves), and failure prediction (catching jobs that will fail before they consume hours of GPU time). We’re four engineers. We ran HPC and GPU training workloads at the largest quant funds and national supercomputing centres. We faced this problem first hand and the only fix was to over-provision and burn millions. Ismaeel built the first multimodal HPC resource predictor as research at EPCC (Edinburgh’s Parallel Computing Centre), which beat every published baseline. This is the tool we wish we had.

We build distributed compute clusters with the cheapest CPUs and GPUs across Hyperscalers and Neoclouds for AI. Our mission is to bring frontier-grade infrastructure to everyone. We're starting by building large scale high performance computing (HPC) clusters for quantitative trading firms to run parallel simulation workloads such as backtesting. Our technology generalizes to critical AI workloads such as post-training with reinforcement learning, fine-tuning, long-horizon agents with high tool use, and batch inference.

Kugel is an enterprise-ready TTS model, available on-prem, with a focus on 30+ languages and low latency.

One memory for your team's agents. Turn every meeting, Claude session, and Slack chat into context your team and agents share.

drip finds the leads, sends first messages, follows up, and books meetings autonomously. Every conversation syncs for your team.

Modern AI agents can send emails, change code repos, and talk with external APIs. Archal verifies your agent takes the right actions, and opens a fix PR when it doesn't.

Inth helps fast-moving software teams prevent privacy failures before they reach production. Privacy risk no longer lives in policy docs, dashboards, and questionnaires. It lives in code: consent flows, data deletion, vendors, logs, AI systems, and agent-written changes that move user data every day. Inth starts with c15t, an open-source consent and privacy SDK with 3M+ npm downloads, used by teams like Zed, Infisical, and Expo. From there, Inth expands into code-native workflows for consent management, data subject requests, policy enforcement, vendor oversight, and audit-ready evidence. We make privacy governance programmable, observable, and compliant by default.

Clone any postgres DB regardless of size in 6s so agents can test their work

Smol machines solve the problem of "but app works on my machine" by shipping the machine. Smol machine enables devs to ship a lightweight virtual machine with any software, similar to how Electron ships an entire browser with the web app.

Interfaze is an AI model built on a new architecture that merges specialized DNN/CNN models with transformers for tasks that require deterministic output and high consistency like Document intelligence, Object detection, Classification, Audio understanding and more. Interfaze outperforms large lab models like Gemini flash, Claude Sonnet and the GPT-5.4 mini series Architecture paper: https://arxiv.org/abs/2602.04101 Full open benchmarks: https://interfaze.ai/leaderboards

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.

Every computer ever made forces you to do one thing at a time. One cursor. One keyboard. One Hardware. One app in focus. Fifty years. Nobody questioned it. We did. We started over. We built InfinityOS, a fundamentally new computer OS on the cloud from ground up. Infinity runs every app in its own independent computer -- own GPU, own input, own environment. Windows and Linux in the same session. Humans and agents working side by side. No concurrency ceiling. Cold start in seconds. runs on the browser of any device..

Hub is a distributed real-world data infrastructure company that captures the lived richness of human experience, including voice, nuance, and perspective to train the next generation of AI models. Through HubApp, our global network spanning 150+ countries sources high-fidelity, original data that cannot be found on the public web or generated synthetically. We provide a completely automated pipeline coupled with human-in-the-loop validation to deliver production-ready multimodal data to frontier AI labs and Fortune 500 companies.

Building the communication infrastructure needed for fully autonomous agents

Minicor connects AI startups to legacy desktop apps that have no API. Reliably, quickly and at scale. Describe a workflow and get an API endpoint. Each call triggers a self-healing desktop automation on a Windows VM. On-prem, cloud, or Citrix. Build through your coding agent via our MCP. Complete with the observability tools to manage your customer relationship: full video replay of every automation, granular logging, and slack enabled alerts.

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.

Up to 80% of the most advance AI compute chips sits idle because of slow networking. Piris Labs builds photonic based networking solutions to enable fast, scalable, and low cost AI workload execution infrastructure.

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.