AIOps Startups funded by Y Combinator (YC) 2026

Field technicians are bad at documenting their jobs, which paralyzes the back office. Kebra ends that. We guide technicians in the field and capture the exact job details the back office needs. Before the truck leaves the driveway, Kebra turns every job into complete notes, warranty claims, parts ordered, and follow-up sales opportunities. Over time, every job feeds your Company Brain, so your best technicians’ expertise never leaves the company. Kebra will power the first $100M-a-year field service company with no back office.

Nex automates the messy business and GTM workflows that no tool could handle before, taking real actions across 1000+ integrations. Instead of just chatting, the agent writes code as it works to make workflows deterministic, fast, and cheap to re-run, and delivers real output: a Slack message, an opened PR, or a live structured data table. Built for teams.

Coasty is a computer use agent that does real work inside softwares, companies already run. New web apps, old desktop tools, the legacy systems nobody wants to touch. You hand it a workflow and it owns the outcome. Most agents demo well and break the moment they hit real software. They get 18 steps out of 20 right, misclick once, and everything after is garbage. Coasty catches when it goes off track and fixes itself mid-task instead of starting over. It handles the messy parts, benchmarks never show. Permission dialogs, surprise pop-ups, a modal that steals focus, a page that loads slow. When a vendor pushes an overnight update and moves half the menus, brittle scripts break by morning. Coasty reads the screen instead of recording clicks, so it adapts and keeps going. It also checks its own output and leaves a time-stamped trail you can replay. We won't pretend it gets every task right. Nothing automating this work does. What matters is what happens when something breaks. It catches the mistake, fixes what it can, and flags what it can't so a person can step in. Nothing fails quietly. That's what lets a team trust it on the work where a silent error gets someone fired. We scored 82% on OSWorld, which puts us among the most reliable agents out there. Reliability is the whole product, not a feature.

Cerenovus is a company brain. We aggregate every kind of file a company produces — documents, PDFs, emails, Slack messages, spreadsheets, meeting notes — and convert them into a single markdown knowledge graph with native AI-agent integration. A company's information becomes uniformly readable both by humans and by the AI agents working inside the graph. On top of that foundation, Cerenovus maps the company as a system, drawing connections between the people, processes, and tools that make up real workflows. From that systems map, it infers where operations are inefficient and how to improve them. In practice, this tool will help executives make better decisions. Whenever a leader has to act on a question — how to restructure a team, whether to keep a vendor, or where handoffs between teams are breaking down — Cerenovus will give them an evidence-backed answer in minutes rather than weeks. Today, that work is done by consultants, by internal analysts, or by the executive asking around informally. Each of those approaches is slow, partial, and goes stale the moment it is delivered. Cerenovus produces the same answers faster, at a fraction of the cost, and keeps them live as the company evolves.

The problem: AI has quietly become one of the largest and fastest-growing line items for companies. Spend is scattered across a dozen provider consoles that each show one number at the end of the month and nothing about why it moved. There's no unified view, and no way to trace a dollar back to the customer, feature, team, or even the pull request that caused it. Which customers are unprofitable once you subtract their AI costs? Which feature is quietly burning your Anthropic budget? Is this week's spike a runaway loop or real growth? How much did that AI-written PR actually cost to ship? Today teams reverse-engineer answers by exporting CSVs from each provider and stitching them together in a spreadsheet, and by the time they do, the money is already spent. What SuperPenguin does: SuperPenguin tracks AI spend across 14 providers (OpenAI, Anthropic, Google Gemini, Deepgram, ElevenLabs, AWS Bedrock, Azure, Modal, Cursor, OpenRouter, and more). * Zero-code setup: connect an API key and costs sync automatically with model-level breakdowns, trends, and forecasts * Per-request attribution: add two lines with our Python or TypeScript SDK to tag every AI call by customer, feature, team, or environment (or any other metadata). * AI coding cost per PR: connect Cursor to see engineering spend attributed to each pull request, repo, and developer, so you know what it actually costs to ship. * Alerts on budget thresholds and spend anomalies, delivered to Slack, email, or Discord. Most teams are set up in under five minutes. We help companies see where their AI money goes and whether it's worth it.

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

Kestrel is the AI automation layer for platform engineering teams. Platform teams use Kestrel to automate incident response, cloud provisioning, CI/CD, security, and developer requests across their stack. Kestrel turns natural-language prompts into deterministic, production-ready workflows with 25+ integrations, 140+ pre-built actions, and support for custom HTTP and webhook actions. Developer-first, with a CLI, Python SDK, and MCP server to manage workflows from where platform teams already work.

Adaptional is building agentic AI for insurance claims. Claims are 75% of every dollar in the $1T insurance industry -- and one of the most under-optimized areas, still managed by adjusters working hundreds of files by hand. We're changing this with AI claims review agents, already deployed at some of the major P&C carriers. In the future, claims will be powered by an intelligence layer that manages files and escalates actions to human adjusters. Adaptional is building the AI system that will be the foundation for every claims department across P&C insurance.

Okibi is a web app that lets you create AI coworkers using natural language. It's like Lovable for creating AI agents that talk to your internal software Corporate users lose 2 hours every day doing tasks that can be automated with agents But existing agent builders have janky drag and drop UIs that don’t map to what they want exactiy. Okibi lets everyone use natural language to build the exact agent they want.

Alter is a zero-trust identity and access control platform purpose-built for AI agents. It wraps every tool call in strong authentication, fine-grained authorization, and real-time guardrails, so agents can move fast without breaking things. Each request is verified at the parameter level, authorized against granular policies, executed with least-privilege access, and fully audited in real time. Unsafe actions, whether it’s a rogue DROP TABLE or a payment above policy limits, are blocked before they touch production. Behind the scenes, Alter manages credentials, issuing ephemeral, scope-narrowed access for every interaction, then rotating or expiring it in seconds. The result: no long-lived secrets, no blind spots, and no surprises in audit. With Alter, teams can move fast on AI agent initiatives while staying fully compliant with SOC 2, HIPAA, GDPR, and internal security standards. A CISO-ready dashboard delivers real-time visibility, detailed audit logs, and compliance-ready controls, removing silos, eliminating excessive permissions, and providing complete oversight of every agent workflow.

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

Kairos closes the last-mile reliability gap in AI deployments. We bring frontier techniques to companies in critical industries, deploying specialized agents that encode operator expertise and reliably automate their most manual workflows.

We are building the data layer for AI, starting with audio. We start with data collection, curating our own proprietary set of diverse conversational data covering a wide range of languages, dialects and accents. We then leverage human expert audio annotators and our own annotation platform to process audio data for Automatic Speech Recognition. With human level transcription and diarization, our data help push the audio model frontier. Today we have over millions of hours of conversational data, and growing. If you need audio data for training or evaluating your voice models or voice agents, reach out! We offer flexible licensing deals that work for startups and enterprises, with minimal process. Audio data should besimple :)

Paper Instruments post-trains LLMs to accelerate knowledge work.

A fully open-source, performant and actionable ML model training platform

Stillwind builds AI tools for electrical engineers to aide them in the repetitive parts of the process, primarily component search, cross referencing and simple circuitry.

Our CLI makes ML model training effortless - just describe your job, and we handle GPU orchestration and execution at half the cost of major cloud providers.

Lucidic emulates model training without changing model weights. The last decade made models intelligent, but intelligence is not the same as experience. Humans do not get better by memorizing thousands of examples; we build learning systems around ourselves: skills, memories, critique, practice, tools, and guidance. And every person learns differently because every task is different. Lucidic brings that idea to AI agents by training a custom learning system for each agent, so it learns what to remember, what skills to build, when to ask for help, and how to improve from experience. The model provides the intelligence, Lucidic gives it a way to learn.

Hello! 👋 We are a team of former ML engineers, founders, roboticists and ops leads who obsess about data and its impact on safe, reliable AI. We specialize in creating environments and datasets for RL by leveraging our experience in simulation and model training. By the numbers: • Powering 3 of the top 6 global AI labs and multiple Fortune 500 enterprises • Billions of training tokens generated each month, 2x month over month • Exclusive, global network of over 500 domain experts We believe humans are inherently creative, and thrive by pushing the frontier. We are working towards an abundant future--one where everyone has access to infinite intelligence, services and goods. Based in San Francisco, CA. We enjoy good food and good company. -- more info below -- Abundant is building the NVIDIA of training data. AI models rely on two fundamental ingredients: compute and data. NVIDIA, the leader in compute, has a peak market cap of $5T and generated $130B in revenue last year as the need for scaling compute has exploded. We believe the need to scale data is just beginning, as we move beyond SFT and human supervision to RL and Learning from Experience. Our founding team consists of second-time founders, ML engineers and data leads from Waymo, Google, Meta and AWS. Our team has previously collaborated with DeepMind to classify hate speech in YouTube videos, trained SOTA models for self-driving, and scaled data pipelines with thousands of human annotators. Our pioneering work in human computation, synthetic data, imitation learning and RL give us a solid advantage in delivering results to our customers. Why now? Training data is more important and more scarce than ever before. Scaling laws dictate that linear improvement in model performance demands an exponential increase in training data. But there is only one World Wide Web and most of it has already been trained on. The next advances will require new, diverse, and high-quality datasets, making training data more important and scarce than ever before. What happens if we succeed? Abundant will be the core enabler for AGI and beyond. Most of the challenges in model training are already solved. What’s missing is the data necessary to move from general knowledge to domain expertise; from chatbots to agents; and from digital intelligence to physical AI. Ask any AI researcher or roboticist: the core bottleneck to progress is the availability of data, i.e. “abundant data”. Abundant works with the most advanced AI labs and startups, as well as F500 enterprises.

Hyrex is a task orchestration framework that uses PostgreSQL (or Hyrex Cloud) as a durable task queue. Define tasks in Python or TypeScript, send them to be processed asynchronously, and let Hyrex handle the rest. Hyrex tasks are COLD: Controllable, Observable, Large-Scale, and Durable!

Leading enterprises use Callback to manage complicated, real-world workflows. We integrate with your systems, not the other way around. Our platform serves as an auditable and permissioned system of record for your operations.

Sage is a HIPAA compliant, AI-native communication platform that makes home care agency client-intake handling smarter, faster, and more reliable. Teams that use Sage can save over 100 minutes of busywork per prospect, freeing up their teams to manage a larger, faster growing business.

Laminar is open-source observability for AI agents. Trace complex workflows, replay and debug agent runs, and detect anomalies across trajectories at scale.

Domu automates debt-collection calls, texts, and emails for financial services and healthcare. We work with some of the largest financial institutions in the world and win by doing what nobody else is willing to do. We are hiring :)

Elevate is bringing AI to private equity-backed roll-ups. For example, one of our customers is Guardian Restoration Partners, which is backed by Alpine Investors, the leading roll-up focused private equity firm. In three months, we integrated 10 acquisitions and enabled them to pilot AI agents built on top of our data warehouse. We know this problem personally. Before Elevate, Scott was a Vice President at a $15B private equity firm where he was leading a roll-up. Steve and Jeff are both software engineers with backgrounds across finance, big tech, and start-ups. The founding team has been friends for over a decade from their Duke undergraduate days.

Pipeshift helps engineering teams run real-time inference in production. We offer optimized runtimes to meet latency/throughput SLAs, paired with infrastructure orchestration that auto-scales and routes workloads across clusters and regions at cost-effective rates.

Maitai makes building reliable AI applications easy. We autocorrect faulty model output in real-time and automatically fine-tune models that learn from their mistakes. This means our customers get more reliable results immediately, and over time, they gain custom models built specifically for their application that only get better and faster. You wouldn’t hire an employee who doesn’t learn from their mistakes—so why use a model that doesn’t? Maitai is here to deliver the next generation of reliable AI inference.

Most AI products hand you a coworker on day one and hope you trust it. Sauna is the coworker you raise: it starts by learning how you work, earns autonomy task by task, and ends up running hours of work on its own while you keep taste, review, and the final say. Wordware is the ~20-person team behind it, backed by Spark Capital, Felicis, and Y Combinator with a $30M seed, the largest in YC history. We build from a San Francisco office in the shadow of the Golden Gate Bridge, and we work absurdly hard because we can see and feel the outcome every day.

Respan (formerly Keywords AI) gives teams a unified control plane to trace and evaluate agent behavior without guesswork, automatically surface issues, and fix what breaks faster. Respan connects production observability, automated and human-in-the-loop evaluations, and an adaptive AI gateway to close the loop between detection, decision, and action - so agents improve continuously in production. Respan is trusted by 100+ AI startups and enterprise teams. Today, the platform process 1B+ logs and 2T+ tokens every month, supporting more than 6.5M end users.

Automorphic has invented a way to infuse knowledge into LLMs via fine-tuning (surpassing context window limitations), enabling developers to rapidly iterate on and successively improve custom models cheaply and efficiently.

LLMs are incredibly powerful, but latency, cost, and unpredictable outputs have made productionizing LLM features challenging. Baserun is a testing and observability platform that helps AI teams streamline their development cycle from identifying an issue to evaluating their solution, so that teams ship faster with confidence.

CoAsync by Cognitio Labs is the AI back office for product quality compliance teams. We help mission-critical food manufacturers automate repetitive, document-intensive workflows. We started with Certificates of Analysis (COAs), one of the many workflows quality teams manage before products can ship. Today, this work is still performed manually across PDFs, emails, spreadsheets, and disconnected ERP systems. Other documents we help quality teams respond to 24x7 include supplier audit questionnaires, production schedules, lab reports & changes in product specifications and quality records. CoAsync automates the workflow by: Reading supplier documents Extracting laboratory data Validating product specifications Applying compliance requirements Drafting compliant COAs Organizing audit-ready documentation Results from one of our initial deployments with a mid-market food processor: 85% less QA administrative work 4× more COAs processed per shift 1-2 hours saved per document New product onboarding in under one day COAs are just the beginning. Our vision is to build the AI back office for product quality and compliance across regulated industries by automating the many document-intensive workflows manufacturers manage every day. Backed by Y Combinator and leading investors. Founder Diva Avaya Sharma has presented example AI workflows for product quality and compliance through the World Economic Forum Centre for Advanced Manufacturing and Supply Chains' SmartStart initiative and at the International Telecommunication Union's AI for Good Global Summit, organized in partnership with the United Nations. Know a company shipping food & product urgently? Help them get started with their own document workflows at https://cognitioiq.com

LiteLLM is an open-source LLM Gateway with 18K+ stars on GitHub and trusted by companies like Rocket Money, Samsara, Lemonade, and Adobe. LiteLLM provides an open source Python SDK and Python FastAPI Server that allows calling 100+ LLM APIs (Bedrock, Azure, OpenAI, VertexAI, Cohere, Anthropic) in the OpenAI format We have raised a $1.6M seed round from Y Combinator, Gravity Fund and Pioneer Fund

PoplarML lets you deploy any machine learning model to a fleet of GPUs as a ready-to-use and scalable API endpoint with one command.

Middleware is a full-stack cloud observability platform. We allow the dev and ops teams to debug the issue faster by bringing all the metrics, logs, traces, and events to a single unified timeline and train data to AI so it can give better insight into infrastructure and application. - Single command installation to collect all the metrics, logs, traces, and events. - AI-based anomaly and error detection - GPT 4-based error resolution - Support Infrastructure monitoring, Logs, APM, Kubernetes Monitoring, Synthetic Monitoring, RUM, Custom dashboard, and Alerts. - Full-stack observability, observe any stack at any scale. We are at Middleware and wanted to make cloud observability faster, cheaper, and better.

NuMind is a tool for data scientists, data analysts, but also software engineers to create custom NLP models. For example, a recruiting company uses NuMind to find which job offers best match a given resume. Etienne (CEO) was head of Machine Learning at Wolfram Research, and Samuel (CTO) co-founded Make.org (8M users). NuMind originated from our own frustration when developing NLP models. Leveraging large language models similar to GPT-3, NuMind allows to complete NLP projects at least 10x faster than before. We launched a private beta August 2 and had 9 paying customers one month later.

LanceDB is a new open-source vector database that can support low-latency billion-scale vector search on a single node. Built around a new columnar data format, LanceDB makes it incredibly easy to build applications for generative AI, recsys, search engines, content moderation, and more.

Query Vary is a no-code tool for building LLM-powered automation. Example use cases include extracting information from a sales call transcript and piping it into a CRM, creating a Slack bot trained on product documentation, or transforming Google forms into fully formatted reports. Input Software --> LLM --> Output Software Our extensive toolset to make each workflow reliable sets Query Vary apart. Book a demo: https://calendar.app.google/6oxEvZA2k4kK6dBa8

🚀 Lumina💧 (YC W22) is a fast growing job platform in Southeast Asia with 1.5 million workers, helping 30k companies recruit and optimize at scale. 🤖 We are now expanding globally with Lumibot, a bespoke AI+human-powered automation service. We help companies automate mundane, repetitive processes with AI and human-in-the-loop catering for various use cases in data ops and complex workflows. This allows your business to focus on your core and grow faster, better and cheaper. 👌Our AI-powered automation start with USD 13/hour, supplemented with human-in-the-loop at USD 2-6/hour. Our services are managed based on SLAs by dedicated service managers under a prepaid credit system without arduous contracts for optimum flexibility. No minimum commitment with fully-refundable deposit from as low as USD 500^. 🛠️ We currently support the following use cases: 1) operations support 2) revenue operations support 3) web and social media management 4) email management 5) content moderation 6) AI training and verification 7) AI text humanization 8) custom process automation ... with more to come ... 👥️️ Lumibot (by Lumina) is backed by Y-Combinator, Monk's Hill Ventures, Alpha JWC, Goodwater Capital, SWC Global and January Capital. More information about us: * 💬 WA: https://wa.me/message/SEMGBRM22MDYK1 * 📅 CAL: https://usemotion.com/meet/aswin-andrison/global * 🌐 WEB: https://www.lumibot.com ^ Reach out to us on special deals ONLY for YC companies!

SubscriptionFlow is an AI-based customizable revenue management platform that helps SMBs optimize subscription revenue. It monitors user activity to identify customers at risk of churning and automatically alerts the sales team. For example, eLearning/SaaS/Membership businesses require to monitor subscription usage to improve customer retention. Ecommerce/Magazine companies need to see the subscription trends to cross-sell and upsell products/services.

RedBrick AI's mission is to accelerate the adoption of artificial intelligence in radiology by building world-class software infrastructure. Currently, we are focused on helping radiology AI teams prepare high-quality datasets to train their algorithms. Radiology data, such as CT and X-ray scans, is an incredibly important source of truth in healthcare delivery. In fact, over 90% of all healthcare data is medical imagery! However, the global radiology workforce is overburdened. In the UK, for example, only 2% of radiology departments are able to fulfill their reporting requirements, and this trend is reflected worldwide. The acute state of radiology, coupled with the abundance of data, makes the use of AI in radiology a prime candidate. In 2022, $5.6 billion was invested in the development of AI in healthcare! However, a key hindrance to further adoption is the lack of sophisticated tools to build and deploy AI algorithms in clinical environments. This is the problem we’re focused on at RedBrick AI We're a team based out of Bangalore India, and USA. We're backed by leading institutional investors like Y Combinator and Peak XV (formerly Sequoia Capital India).

Rootly is a modern on-call and incident management platform used by top YC companies like Dropbox, Lattice, Webflow, Faire, but also Figma, LinkedIn, NVIDIA and 100s more.

Openlayer is the governance platform for AI applications.

Waydev tracks AI-generated code from commit to production. AI Checkpoints capture which agent wrote each change, tokens consumed, cost per PR, acceptance rate, and whether it actually deployed — so you can compare Copilot, Cursor, and Claude Code on real production outcomes, not vibes. Engineering leaders use Waydev to measure AI adoption by team, monthly spend, and tokens per developer, then tie it back to delivery. The Waydev Agent answers plain-English questions about your AI investment ("which team gets the most ROI from Cursor?"). Built for VPs of Engineering and CTOs at companies running real AI coding budgets. Trusted by Dropbox, American Express, Caterpillar, and PwC. YC W21.

Mystic’s platform allows companies to easily and reliably deploy ML models on our serverless cloud or on their own infrastructure without requiring a team of MLOps engineers. With our Python SDK, data-scientists immediately get an endpoint from their own model, or any open-source models. Once uploaded, our platform handles routing, multi-cloud scaling, caching, GPU optimization and other features to provide the ultimate ML inference platform.

Prolific helps dedicated research teams to collect the very highest-quality human-powered data - at scale - using our simple-to-use platform to target and manage participants from our diverse, vetted participant pool. The truth matters: the best decisions, and biggest discoveries, are built on the highest-quality data. And with the increasing proliferation of AI, access to reliable, diverse data to develop and train AI models has never been more important. Created by researchers for researchers, Prolific was founded to provide a better way for researchers and organisations to get high-quality human data and feedback at scale for important research. Now, more than 30,000 researchers across academia and industry use Prolific to gather definitive human data and feedback from reliable, engaged and fairly-treated participants – with a new study launched every 3 minutes.

Superb AI is a leading computer vision platform and professional services provider that provides enterprise-grade, end-to-end MLOps and DataOps workflows to accelerate the adoption and development of data-centric AI. Through the practical application of AI-based automation, Superb AI helps teams manage the entire ML lifecycle more efficiently, from data annotation to curation, model training, and deployment, while ensuring optimal data accuracy and consistency.

Fountain’s all-in-one high volume hiring platform empowers the world’s leading enterprises to find the right people through smart, fast, and seamless recruiting. Candidates can apply anytime, anywhere in minutes, right from their phone. Automated and customizable processes streamline the candidate experience and save time for recruitment teams so they can scale with growing hiring needs. Advanced analytics provide end-to-end process visibility so managers can make swift, data-driven decisions. Throughout the candidate journey, the openly integrated platform enables companies to find, qualify and convert more applicants. Fountain’s global customers hire over 1.2 million workers annually in 78 countries.

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.