DeepSource
Static analysis with a sub-5% false positive rate, plus AI code review and autofix on every PR.
About
DeepSource is a code analysis platform founded in 2019 that pairs a deterministic rule engine (5,000+ analyzers across Python, JS/TS, Go, Java, Rust, and more) with LLM-powered review. Every pull request gets a structured report card across five dimensions — Security, Reliability, Complexity, Hygiene, Coverage — and Autofix AI generates context-aware fixes from imports and surrounding code. Its headline claim is a sub-5% false positive rate, achieved by filtering findings through explicit and implicit signals before they reach you.
The honest picture: the good stuff (AI review, Autofix, security scanning, dashboards) sits behind the $24/user/month Team plan; the free tier covers individuals with basic static analysis. DeepSource does not support Azure DevOps, and its pricing was restructured upward in early 2026 as it repositioned as a premium AI platform. Still one of the lowest-noise review tools available if your budget stretches.
What it can do
- 5,000+ analyzers with sub-5% false positive rate
- AI review report card on every PR
- Autofix AI generating working fixes
- Code health dashboards and coverage tracking
- OWASP Top 10 and SANS Top 25 security checks
Setup
Connect your GitHub, GitLab, or Bitbucket repo and add a .deepsource.toml enabling analyzers. Analysis starts on every commit and PR — setup takes under 10 minutes.
Prerequisites
A GitHub, GitLab, or Bitbucket repository; Team plan for AI review features.
Use cases
Works with
Trust score — 8/10
Scored 8/10 (verified tier, metrics-v1). Evidence: Verified via vendor site/docs/GitHub and reputable coverage, wave 49; Trending score 76/100 from researcher assessment.
Sources
Every fact above was checked against these sources. Where a claim comes from the provider and couldn't be independently verified, the text says so.