CircleCI is a Build and Deploy company founded in 2011 and based in San Francisco, United States. It has raised $315.5M in total funding, most recently a Series F in 2021 at a $1.7B valuation.
| Date | Stage | Amount | Valuation | Lead investors |
|---|---|---|---|---|
| May 11, 2021 | Series F | $100M | $1.7B | Greenspring Associates |
| Apr 7, 2020 | Series E | $100M | — |
| IVP, Sapphire Ventures |
| Jul 23, 2019 | Series D | $56M | — | Owl Rock Capital Partners, NextEquity Partners |
| Jan 17, 2018 | Series C | $31M | — | Top Tier Capital Partners |
| May 16, 2016 | Series B | $18M | $60M | Scale Venture Partners |
| Feb 7, 2014 | Series A | $6M | — | DFJ Ventures |
| Feb 25, 2013 | Seed | $1.5M | — | — |
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The flagship continuous integration and delivery platform that automates build, test, and deployment pipelines for software teams. It supports multiple execution environments (Docker, macOS, Linux, Windows), offers autoscaling, security scanning, and integrations with major VCS providers like GitHub and Bitbucket. Differentiates with blazing-fast build times, parallel execution, and reusable configuration snippets called Orbs that let teams standardize their pipeline patterns across projects.
An AI-powered validation agent that autonomously analyzes CI failures, intelligently splits test suites for parallel execution, and debugs pipeline issues in real time. Chunk integrates directly into a team's CircleCI workflows to reduce build times and mean-time-to-resolution, making it especially useful for engineering teams adopting AI-assisted coding who need automated guardrails to validate every code change at speed.
A Model Context Protocol (MCP) server that exposes CircleCI pipelines and build data to AI coding agents. It allows AI tools like Cursor, Copilot, and custom agents to query pipeline status, trigger builds, and retrieve logs without leaving the IDE. This deep integration bridges the gap between AI code generation and production-ready validation, enabling fully automated build-and-test loops driven by AI coding assistants.
A set of pre-configured, optimized compute environments including Docker containers, Linux VMs, macOS, and Windows images designed specifically for CI/CD workloads. They come with popular languages, frameworks, and tools pre-installed, reducing pipeline setup time from hours to minutes. The environments auto-scale based on demand and include resource classes tailored to everything from lightweight unit tests to memory-intensive integration suites.
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