nao Labs | Y Combinator
Spring 2025 batch; open-source analytics agent builder ('cursor for data').
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Memo snapshot · May 20, 2026, 6:03 PM
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nao Open-source analytics agent builder.
Raised $500K across 1 funding round. Latest: $500K Pre-seed (Jun 2025). Investors: Y Combinator. (High).
Seed (YC)
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Funding
Raised $500K across 1 funding round. Latest: $500K Pre-seed (Jun 2025). Investors: Y Combinator. (High).
Hiring
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29 product/news‑styled row(s); headline risk without filings (High).
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Spring 2025 batch; open-source analytics agent builder ('cursor for data').
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nao Labs | Y Combinator
Wed, May 20, 06:03 PM · confidence 88%high quality
https://www.ycombinator.com/companies/nao-labsTeam
About / company · Mon, May 11, 09:47 AM · confidence 90%high quality
https://getnao.io/company/team/Company
About / company · Mon, May 11, 09:47 AM · confidence 90%high quality
https://getnao.io/company/Newest first · 36 event(s)
Open-source analytics agent builder.
Spring 2025 batch; open-source analytics agent builder ('cursor for data').
Source: About / company
Meet the team building nao and shaping context engineering for analytics agents.
Source: About / company
Learn about nao, the team behind it, and the principles driving context engineering for analytics agents.
Source: Careers
nao is the analytics agent builder for context engineering. Build, evaluate, and deploy reliable analytics agents with your own data stack.
Source: Blog / news
Open source isn't a marketing strategy. It's the only way to build trust in analytics agents — and the only way context engineering matures as a discipline.
Source: Blog / news
A step-by-step guide to set up an AI analytics Microsoft Teams bot with an open source framework so your team can chat with data directly in Teams.
Source: Blog / news
A practical step-by-step guide to set up an AI analytics Slack bot with an open source framework so your team can chat with data directly in Slack.
Source: Blog / news
We tested MetricFlow semantic layers against a plain rules.md file to measure the real impact on analytics agent reliability, cost, and speed. Here's what the data says.
Source: Blog / news
We're open sourcing nao — an analytics agent framework built on context engineering. Here's our vision for what comes after black-box BI.
Source: Blog / news
A practical comparison of the 5 best open source analytics agents in 2026 — nao, Agno Dash, LangChain, LibreChat, and Vercel's knowledge agent template.
Source: Blog / news
Analytics agents won't scale without a proper context stack. Here's why context engineering needs its own open framework — and what that framework looks like.
Source: Blog / news
Why natural language interfaces are displacing traditional BI dashboards - and how to prepare your data warehouse for this shift
Source: Blog / news
Five open-source skills that set up your nao project, write its rules, build its test suite, audit it, and add a semantic layer. Install with `nao skills add getnao/nao`.
Source: Blog / news
A practical case study on how context engineering, dbt documentation, and data-model fixes improved an analytics agent from 45% to 86% reliability.
Source: Blog / news
Stories turn a chat with your data into a shareable, editable, versioned report. Watch the launch demo and read how it works.
Source: Blog / news
How to go from the semantic layer answering no questions to 82% reliability on a wide business range - 4 steps with real benchmark data.
Source: Blog / news
A practical guide to data modeling for AI agents, with clear rules to optimize for precision, reliability, and better chat-with-data performance.
Source: Blog / news
A summary of 3 context engineering studies on analytics agents: what actually moves reliability, whether a semantic layer is worth it, and how to set up a testing and monitoring framework.
Source: Blog / news
A practical 7-step guide for data teams to build a context stack that improves analytics agent reliability, speed, and cost control.
Source: Blog / news
Learn Git essentials for data professionals, including practical workflows and how AI can help automate version control for SQL, Python, and data projects
Source: Blog / news
A practical 5-step setup guide to deploy an analytics agent on dbt MCP with nao, from choosing the right MCP to rolling out chat with data across your company.
Source: Blog / news
Complete step-by-step guide to setting up dbt, creating your first models, and leveraging AI to accelerate your data transformation workflow
Source: Blog / news
A comprehensive guide to choosing the right data stack for your company's stage and data maturity.
Source: Blog / news
We tested schema, data sampling, profiling, dbt repos, and rules.md to find which context pieces actually improve analytics agent reliability. Here's what the data says.
Source: Blog / news
A practical 7-step guide for data teams to design, organize, and test skills that improve analytics agent reliability and chat-with-data outcomes.
Source: Blog / news
A complete guide to building reliable AI agents for data analytics - from context engineering to production deployment
Source: Blog / news
A practical 7-step framework to build your in-house analytics agent fully with open source tooling, from context engineering to evaluation and rollout.
Source: Blog / news
A practical guide to choose the best option for you to deploy an analytics agent.
Source: Blog / news
A step-by-step guide to evaluating your analytics agent's reliability using nao's built-in unit test framework — from writing your first test to running the visual dashboard.
Source: Blog / news
A practical 5-step guide to turning your team into an AI-first data team with context engineering, open source analytics, and chat with data workflows.
Source: Blog / news
We benchmarked 20 analytics agent solutions — from warehouse-native tools to AI-native BI and open-source agents — on accuracy, cost, context depth, and data team UX. Here's the full breakdown.
Source: Blog / news
Recap of the first meetup dedicated to agentic analytics: 4 data teams from Gorgias, Malt, GetAround, and The Working Company share what they've actually built, what worked, and what didn't.
Source: Blog / news
Guides, benchmarks, and product thinking on analytics agents, context engineering, dbt, and modern data workflows.
Source: About / company
nao is the analytics agent builder for context engineering. Build, evaluate, and deploy reliable analytics agents with your own data stack.
Open-source core project.
1 row(s)
Open-source analytics agent builder.
https://getnao.io/3 row(s)
Source name: About / company
Meet the team building nao and shaping context engineering for analytics agents.
https://getnao.io/company/team/Source name: About / company
Learn about nao, the team behind it, and the principles driving context engineering for analytics agents.
https://getnao.io/company/Source name: About / company
nao is the analytics agent builder for context engineering. Build, evaluate, and deploy reliable analytics agents with your own data stack.
https://getnao.io/about1 row(s)
Spring 2025 batch; open-source analytics agent builder ('cursor for data').
https://www.ycombinator.com/companies/nao-labs1 row(s)
Source name: Careers
nao is the analytics agent builder for context engineering. Build, evaluate, and deploy reliable analytics agents with your own data stack.
https://getnao.io/careers1 row(s)
Open-source core project.
https://github.com/getnao/nao29 row(s)
Source name: Blog / news
Open source isn't a marketing strategy. It's the only way to build trust in analytics agents — and the only way context engineering matures as a discipline.
https://getnao.io/blog/why-open-source-analytics-agent/Source name: Blog / news
A step-by-step guide to set up an AI analytics Microsoft Teams bot with an open source framework so your team can chat with data directly in Teams.
https://getnao.io/blog/setup-ai-analytics-teams-bot-open-source/Source name: Blog / news
A practical step-by-step guide to set up an AI analytics Slack bot with an open source framework so your team can chat with data directly in Slack.
https://getnao.io/blog/setup-ai-analytics-slack-bot-open-source/Source name: Blog / news
We tested MetricFlow semantic layers against a plain rules.md file to measure the real impact on analytics agent reliability, cost, and speed. Here's what the data says.
https://getnao.io/blog/semantic-layer-impact-analytics-agent/Source name: Blog / news
We're open sourcing nao — an analytics agent framework built on context engineering. Here's our vision for what comes after black-box BI.
https://getnao.io/blog/open-source-analytics-agent-launch/Source name: Blog / news
A practical comparison of the 5 best open source analytics agents in 2026 — nao, Agno Dash, LangChain, LibreChat, and Vercel's knowledge agent template.
https://getnao.io/blog/open-source-analytics-agent-builder-playbook/Source name: Blog / news
Analytics agents won't scale without a proper context stack. Here's why context engineering needs its own open framework — and what that framework looks like.
https://getnao.io/blog/open-framework-context-engineering/Source name: Blog / news
Why natural language interfaces are displacing traditional BI dashboards - and how to prepare your data warehouse for this shift
https://getnao.io/blog/natural-language-replacing-bi-dashboards/Source name: Blog / news
Five open-source skills that set up your nao project, write its rules, build its test suite, audit it, and add a semantic layer. Install with `nao skills add getnao/nao`.
https://getnao.io/blog/launching-nao-skills/Source name: Blog / news
A practical case study on how context engineering, dbt documentation, and data-model fixes improved an analytics agent from 45% to 86% reliability.
https://getnao.io/blog/improve-analytics-agent-reliability-steps/Source name: Blog / news
Stories turn a chat with your data into a shareable, editable, versioned report. Watch the launch demo and read how it works.
https://getnao.io/blog/how-to-turn-chat-with-data-into-shareable-stories/Source name: Blog / news
How to go from the semantic layer answering no questions to 82% reliability on a wide business range - 4 steps with real benchmark data.
https://getnao.io/blog/how-to-make-semantic-layer-work-for-analytics-agents/Source name: Blog / news
A practical guide to data modeling for AI agents, with clear rules to optimize for precision, reliability, and better chat-with-data performance.
https://getnao.io/blog/how-to-do-data-modeling-for-ai-agents/Source name: Blog / news
A summary of 3 context engineering studies on analytics agents: what actually moves reliability, whether a semantic layer is worth it, and how to set up a testing and monitoring framework.
https://getnao.io/blog/how-to-do-context-engineering-for-data-teams/Source name: Blog / news
A practical 7-step guide for data teams to build a context stack that improves analytics agent reliability, speed, and cost control.
https://getnao.io/blog/how-to-build-context-stack-for-agentic-analytics/Source name: Blog / news
Learn Git essentials for data professionals, including practical workflows and how AI can help automate version control for SQL, Python, and data projects
https://getnao.io/blog/git-basics-for-data-professionals/Source name: Blog / news
A practical 5-step setup guide to deploy an analytics agent on dbt MCP with nao, from choosing the right MCP to rolling out chat with data across your company.
https://getnao.io/blog/deploy-analytics-agent-dbt-mcp-steps/Source name: Blog / news
Complete step-by-step guide to setting up dbt, creating your first models, and leveraging AI to accelerate your data transformation workflow
https://getnao.io/blog/dbt-setup-guide/Source name: Blog / news
A comprehensive guide to choosing the right data stack for your company's stage and data maturity.
https://getnao.io/blog/data-stack-guide/Source name: Blog / news
We tested schema, data sampling, profiling, dbt repos, and rules.md to find which context pieces actually improve analytics agent reliability. Here's what the data says.
https://getnao.io/blog/context-impact-analytics-agent/Source name: Blog / news
A practical 7-step guide for data teams to design, organize, and test skills that improve analytics agent reliability and chat-with-data outcomes.
https://getnao.io/blog/claude-skills-for-agentic-analytics/Source name: Blog / news
A complete guide to building reliable AI agents for data analytics - from context engineering to production deployment
https://getnao.io/blog/build-production-ready-ai-agents/Source name: Blog / news
A practical 7-step framework to build your in-house analytics agent fully with open source tooling, from context engineering to evaluation and rollout.
https://getnao.io/blog/build-open-source-analytics-agent-text-to-sql/Source name: Blog / news
A practical guide to choose the best option for you to deploy an analytics agent.
https://getnao.io/blog/best-analytics-agent-for-data-team/Source name: Blog / news
A step-by-step guide to evaluating your analytics agent's reliability using nao's built-in unit test framework — from writing your first test to running the visual dashboard.
https://getnao.io/blog/analytics-agent-benchmark-context-stack/Source name: Blog / news
A practical 5-step guide to turning your team into an AI-first data team with context engineering, open source analytics, and chat with data workflows.
https://getnao.io/blog/ai-first-data-team-steps/Source name: Blog / news
We benchmarked 20 analytics agent solutions — from warehouse-native tools to AI-native BI and open-source agents — on accuracy, cost, context depth, and data team UX. Here's the full breakdown.
https://getnao.io/blog/ai-data-agents-compared/Source name: Blog / news
Recap of the first meetup dedicated to agentic analytics: 4 data teams from Gorgias, Malt, GetAround, and The Working Company share what they've actually built, what worked, and what didn't.
https://getnao.io/blog/agentic-analytics-meetup-paris/Source name: Blog / news
Guides, benchmarks, and product thinking on analytics agents, context engineering, dbt, and modern data workflows.
https://getnao.io/blog/Sign in as an active team member to view private notes, watchlist controls, transcript evidence, and interaction history.