DeepSource Review 2026: AI Code Review, Pricing & Limits

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Last verified: October 13, 2026. This is an editorial research review — how we review. Prices and plans change often; confirm on the vendor’s site.

Status update: Harness announced its acquisition of DeepSource on September 9, 2026. DeepSource says the product, integrations and terms are unchanged for now and its capabilities will become part of the Harness platform over time.

DeepSource is a code quality and security platform that reviews every pull request with a mix of static analysis and an AI review agent. It started as a static analysis tool and now describes itself as “The AI Code Review Platform”. Alongside AI review, it covers SAST, secrets detection, dependency scanning, code coverage, infrastructure-as-code checks and automatic fixes, across GitHub, GitLab, Bitbucket and Azure DevOps.

It is aimed at engineering teams that want one tool to act as a merge gate for quality and security, rather than an AI reviewer that only leaves comments. In September 2026, Harness announced it had acquired DeepSource. The company says the product continues to work as before for now and will gradually become part of the Harness platform.

This is an editorial research review based on DeepSource’s pricing page, documentation, changelog, benchmark page and announcements. We did not run our own benchmarks or timed tests.

Quick verdict

DeepSource is a strong fit for teams that want deterministic checks and AI review in one place, with quality gates, coverage and security scanning included. Its hybrid design is meant to keep noise down, and it is free for public open-source repositories. The trade-offs are a higher seat price than review-only bots, AI review billed by processed lines on top of the seat, and some uncertainty about the product’s direction after the Harness acquisition.

Pro: Static analysis with more than 5,000 rules runs before the AI agent, which DeepSource says produces fewer false positives.
Pro: A broad platform: SAST, secrets detection, dependency scanning with reachability, IaC checks, coverage, license compliance and OWASP and SANS reports.
Pro: Supports GitHub, GitLab, Bitbucket and Azure DevOps with no CI configuration.
Pro: Free for public repositories, plus a CLI, MCP server and PR Report Card that AI coding agents can use.
Con: AI Review is metered by processed lines of code, so costs vary with pull request size.
Con: Self-hosting, SSO and bring-your-own-key AI are Enterprise-only.
Con: The headline benchmark is run and published by DeepSource itself.
Con: The Harness acquisition means pricing, branding and packaging may change over time.

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What is DeepSource?

DeepSource was founded in 2019 and is based in San Francisco. You connect a repository from GitHub, GitLab, Bitbucket or Azure DevOps, DeepSource detects the languages, and it starts analyzing pull requests without a CI pipeline or YAML file. It supports more than 30 languages.

In February 2026 it made AI Review run alongside static analysis on every pull request by default, added inline review comments and introduced a PR Report Card. It also retired its old Free plan in favour of an Open Source plan. On September 9, 2026, DeepSource’s founders announced that Harness had acquired the company. They say workspaces, integrations, data residency and terms are unchanged for now, and that customers will get advance notice before changes arrive.

Key features

Hybrid AI Review

DeepSource describes a four-step pipeline. It builds a per-PR syntax tree and project graph, runs its static analyzers, filters likely false positives, and then passes those findings to an AI agent that reviews the relevant code with search tools and a taint-analysis sub-agent. The AI Review engine was rebuilt in April 2026 with new models, and two tiers were introduced: Standard and Advanced, which adds multi-pass analysis for critical changes. Teams can also set AI Review to run only when @deepsourcebot is mentioned.

PR Report Card and quality gates

Each pull request gets a letter grade from A to D across Security, Reliability, Complexity, Hygiene and Coverage, with one suggested focus area. Quality and security gates can block merges that miss your thresholds, and baseline analysis means only newly introduced issues block a pull request.

Autofix

For supported issues, Autofix generates fixes for every occurrence, which you review before applying. On default-branch analysis the fixes arrive as a new pull request; on an existing pull request they are committed to its branch. For vulnerable dependencies, Autofix proposes a version upgrade with a breakage-risk summary and opens a pull request.

Security scanning

The platform includes SAST, secrets detection that DeepSource says covers more than 165 providers, dependency scanning with reachability analysis (extended to Java Maven projects in July 2026), Terraform and CloudFormation checks, license compliance and OWASP Top 10 and SANS Top 25 reports.

Tools for AI coding agents

The DeepSource CLI lets agents such as Claude Code and Cursor pull issues, metrics and vulnerabilities as JSON, and an installable skill works with many agents. A hosted MCP server, launched in April 2026, gives agents 30 tools for reading review findings, report cards, vulnerabilities and metrics.

Who should use DeepSource

DeepSource suits teams that want a single quality and security gate on every pull request, especially if they currently run separate static analysis, secrets and dependency tools. It is also a good fit for Azure DevOps shops, open-source maintainers with public repositories, and teams that want AI coding agents to fix issues against a structured grade.

Who should skip it

Skip DeepSource if you only want a lightweight AI comment bot at the lowest price, if you need SSO or self-hosting without an enterprise contract, or if the Harness ownership change makes long-term planning harder for you.

Strengths and limitations

Strengths

Signal over noise. Static findings seed and constrain the AI review, which DeepSource says makes results consistent enough to use as a CI gate.
Breadth. Quality, security, coverage and AI review in one product can replace several separate tools.
Git platform coverage. Native support for all four major hosted Git platforms, with no CI setup.
Built for agent workflows. The Report Card, CLI and MCP server give coding agents structured feedback they can act on.
Data commitments. DeepSource’s privacy policy says code is not used for training without opt-in and that its AI providers are contractually barred from retaining code. It reports SOC 2 Type II and GDPR compliance.

Limitations

Two-part cost. A $24 to $30 seat price plus metered AI Review makes DeepSource more expensive and less predictable than flat-price reviewers. Auto top-up and rollover credits help, but heavy users should model their monthly volume.
Vendor-run benchmark. DeepSource reports the top F1 score (84.51%) on the OpenSSF CVE Benchmark, but it ran the test itself, the benchmark covers JavaScript and TypeScript only, and tool setups differed. It publishes its methodology and raw data, which helps, but treat it as a vendor claim.
Enterprise gating. SSO, self-hosting and bring-your-own-key AI all require Enterprise.
Ownership change. After the Harness acquisition, DeepSource says its capabilities will become part of the Harness platform over time. Buyers signing long contracts should ask about roadmap and pricing commitments.
Limited IDE presence. DeepSource works mainly in pull requests, the dashboard, the CLI and MCP. We found no current documentation for a dedicated IDE extension.

Pricing (as of October 2026)

Plan	Price	What you get
Open Source	$0	Unlimited public repositories and members, 1,000 reviewed pull requests and 1,000 formatting runs a month, static analysis, SAST, IaC and coverage. AI Review and Autofix are pay-as-you-go. No private repositories, dependency scanning or license compliance.
Team	$24/user/month billed yearly, or $30 billed monthly	Unlimited repositories, pull request reviews and formatting runs, $10 a month of AI Review credit per user ($100 a year on annual plans), 3 dependency-scanning targets, monorepo support, audit logs, API, webhooks and priority support.
Enterprise	Custom	Everything in Team plus self-hosted deployment, Enterprise Cloud, bring-your-own-key AI Review (Anthropic, OpenAI or Google Gemini), SSO, SLA, manual invoicing and a dedicated account manager.

AI Review usage beyond the included credit costs $8 per 10,000 processed lines on Standard and $15 per 10,000 on Advanced, and processed lines include surrounding context the agent reads, not only the diff. Extra dependency-scanning targets are $8 a month each. Seats are counted as unique committers with Administrator or Member roles. The Team plan has a 14-day trial with up to $50 in AI Review credit and no credit card. Pricing changes regularly, so confirm the current details on DeepSource’s pricing page. See DeepSource pricing

Prices verified on October 13, 2026 against the official DeepSource pricing page. Plans change often — confirm on the vendor’s page before you buy.

Use cases

DeepSource combines static analysis, security scanning and AI review, so it fits teams that want a merge gate rather than only review comments. These scenarios are based on DeepSource’s documentation and the research behind our review, not on hands-on testing.

Replacing several separate scanners with one gate

A platform team runs a linter, a secrets scanner, a dependency scanner and a coverage tool, each with its own dashboard. DeepSource covers static analysis, SAST, secrets detection, dependency scanning with reachability, IaC checks and coverage, and its quality gates can block merges that miss thresholds. In our assessment, this is where DeepSource offers the most value. Dependency scanning includes a limited number of targets on Team, with extra targets billed monthly.

Giving coding agents a structured target

A team that writes much of its code with Claude Code or Cursor wants agents to fix their own issues before a human looks. The DeepSource CLI and MCP server let agents read findings, vulnerabilities and the PR Report Card grade, and Autofix can generate fixes for supported issues. AI Review is metered by processed lines, so heavy agent use raises costs.

Code review on Azure DevOps

An enterprise team on Azure DevOps finds that several AI reviewers do not support it. DeepSource lists native Azure DevOps support with inline review comments and no CI configuration. SSO and self-hosting still require the Enterprise plan.

Quality checks for a public open-source project

Maintainers of a public library want automated static analysis and coverage on contributors’ pull requests at no cost. DeepSource’s Open Source plan is free for public repositories with unlimited members and a monthly cap on reviewed pull requests. AI Review and Autofix are pay-as-you-go on that plan, and private repositories are not included.

Alternatives

SonarQube: an established code quality and security platform with self-managed and cloud options.
CodeRabbit: an AI-first PR reviewer that also supports Azure DevOps.
Bito: AI review in pull requests, IDEs and the CLI, with bundled linters and lower-tier self-hosting.
Greptile: an AI reviewer built on a graph of your whole codebase.

Final verdict

DeepSource combines a mature static analysis engine with AI review, which makes it one of the more trustworthy options for gating merges rather than just commenting on them. Free use for public repositories and broad Git platform support are clear advantages. The metered AI pricing, Enterprise-only SSO and the post-acquisition roadmap deserve a careful look, but the 14-day Team trial is an easy way to see how it handles your own pull requests.

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FAQ

Is DeepSource free?

It is free for public open-source repositories through the Open Source plan, which includes static analysis and coverage with a monthly cap on reviewed pull requests. Private repositories need the paid Team or Enterprise plan, and AI Review is billed by processed lines of code on every plan. The Team plan has a 14-day trial with bundled AI Review credit and no credit card required.

Did Harness acquire DeepSource?

Yes. DeepSource’s founders announced on September 9, 2026 that Harness had acquired the company. DeepSource says workspaces, integrations, data residency and terms are unchanged for now, that its capabilities will become part of the Harness platform over time, and that customers will get advance notice of changes.

Is my code used to train AI models?

DeepSource’s privacy policy says it does not use customer code to train AI models unless you opt in through account settings, and that its third-party AI providers are contractually required not to retain code after processing. Enterprise customers can bring their own Anthropic, OpenAI or Google Gemini keys so inference runs on their own infrastructure.

Which Git platforms and languages does DeepSource support?

DeepSource supports GitHub, GitLab, Bitbucket and Azure DevOps, and connects without CI configuration. It says it supports more than 30 languages, including Python, Java, Go, JavaScript, TypeScript, C#, Rust, Kotlin and Swift. Check its analyzer directory for the depth of support for your stack.

How does DeepSource’s AI Review pricing work?

Team seats include a monthly AI Review credit per user, pooled across the team. Usage beyond that is billed per 10,000 processed lines at Standard or Advanced rates, and processed lines include context the agent reads beyond the diff. Unused credit rolls over, and auto top-up is optional. See DeepSource’s pricing page for current rates.

DeepSource vs SonarQube: which should I choose?

Both are code quality and security platforms with quality gates. In our assessment, DeepSource suits teams that want AI review, Autofix and agent tooling built into the pull request flow, while SonarQube suits organisations that want a long-established platform with self-managed options. Compare both on your own repositories before committing.

DeepSource Review (2026): Static Analysis Meets AI Code Review