DeepSource

Code Quality · #3 of 3 in category · #24 of 27 overall

Static-analysis platform (quality, coverage, secrets) with Autofix and a metered AI Review add-on; free for open-source repos.

Visit DeepSource [↗] See the matrix

[ Where it fits ]

On the documented evidence, DeepSource suits larger orgs willing to buy an enterprise plan for self-hosting.

[ Facts ]

Category: Code Quality
Open source: No — proprietary
Pricing: Free for OSS (unlimited public repos, 1,000 PRs/mo); Team $24/user/mo annual incl. $100/yr AI Review credit; AI review metered $8-15 per 10K LOC; Enterprise custom source ↗
Self-hosted: Enterprise only — Enterprise adds self-hosted and air-gapped deployment plus BYOK (Anthropic, OpenAI, or Gemini keys).
Platforms: GitHub GitLab Bitbucket AD Azure DevOps
Model control: BYOK (Anthropic, OpenAI, Gemini) on Enterprise only; vendor-managed models otherwise
Last verified: 2026-08-11

[ Against the 9 standards ]

Based on public documentation as of 2026-08-11. ✓ documented · ~ partial · ✗ not offered · ? undocumented. Undocumented scores zero — see the methodology.

? Multi-dimensional Context

AI Review context depth not documented in the sources we verified; static analyzers run per-repo.

~ Rule-Centric & Default Quiet

Configurable static analyzers; custom AI review rules not documented.

? Dual-Workflow: Local vs. PR

Local/IDE review surface not covered in the sources we verified.

? Business Logic Validation

Ticket/requirements validation not documented.

? Continuous Learning

Learning from review feedback not documented.

? Sandbox Validation

Sandbox or test-run validation not documented.

~ Economic Transparency

BYOK (Anthropic, OpenAI, Gemini) is Enterprise-only; AI metering ($8-15/10K LOC) hard to map to tokens.

~ Actionability

Autofix generates fixes for static findings; AI Review fix actionability not documented.

? Measurable ROI

ROI/metrics reporting not documented in the sources we verified.

[ Closest alternatives ]

Code Quality Codacy 4/9 Code Quality SonarQube 4/9 AI PR Review Panto 1.5/9 AI PR Review Sourcery 1.5/9

[ In our coverage ]

AI Code Review Statistics (2026): Sourced Data

AI code review statistics for 2026: adoption, trust, review turnaround, AI code volume, and bug-catch benchmarks — every stat linked to a primary source.

AI Code Review vs Static Analysis: 2026 Guide

AI code review vs static analysis compared: determinism vs reasoning, false positives, SAST coverage, cost, and why mature teams run both.

Best AI Code Review Tools (2026): 12 Tools Compared

The best AI code review tools 2026 offers, compared honestly: Kodus, CodeRabbit, Greptile, Copilot and more — context depth, pricing, self-hosting.

Open Source AI Code Review: The Real Options (2026)

Open source AI code review tools compared: Kodus (AGPL), PR-Agent (MIT), and more — real licenses, BYOK costs, and how they stack up against closed SaaS.

[ FAQ ]

Is DeepSource open source?

No. DeepSource is proprietary — you can use it, but you cannot read or fork the review engine.

Can DeepSource be self-hosted?

Enterprise only. Enterprise adds self-hosted and air-gapped deployment plus BYOK (Anthropic, OpenAI, or Gemini keys). Verified against the vendor's own documentation on 2026-08-11.

How much does DeepSource cost?

Free for OSS (unlimited public repos, 1,000 PRs/mo); Team $24/user/mo annual incl. $100/yr AI Review credit; AI review metered $8-15 per 10K LOC; Enterprise custom. Seat price is only part of the bill: DeepSource handles models as byok (anthropic, openai, gemini) on enterprise only; vendor-managed models otherwise, which is what usually decides the real monthly cost.

How does DeepSource score against the 9-pillar AI code review standard?

1.5 out of 9. It fully documents 0 standards, partially documents 3, does not offer 0, and leaves 6 undocumented. The score is coverage of documented capability, not a measure of review quality.

What are the alternatives to DeepSource?

The closest tools in this directory are Codacy, SonarQube, Panto, Sourcery. Each is scored against the same 9 standards, so the matrices are directly comparable.

Evaluating DeepSource?

Run it through the two-week trial protocol before you commit a team to it.

Evaluation guide [↗]