Deepsource
AI code review platform that combines 5,000+ static analysis rules with an AI review agent on every pull request.
Choose DeepSource when PR-native review must cover quality and security at once, and your AI assistants are writing code faster than a human can audit. The 5,000+ rule engine holds false positives down, Autofix™ removes the grunt work, and the PR Report Card gives agents structured feedback. Budget for the AI Review meter: Team is $24 per user/month billed yearly with $100 in annual AI Review credits per user, then $8 or $15 per 10K processed LOC. If you already run Semgrep or CodeRabbit, compare before switching — and factor in the undisclosed Harness acquisition terms.
Verified 2d ago · liveness 87/100 · cite: rightaichoice.com/tools/deepsource
- Teams whose AI coding assistants produce a large share of merged code
- Engineering orgs that want deterministic quality gates alongside AI review
- Companies that need OWASP Top 10 and SANS Top 25 mapped reports for audits
- Fast-moving startups reviewing many PRs daily
- Solo developers who need AI Review on private repos without per-LOC metering
- Teams requiring self-hosted or airgapped deployment but unwilling to move to Enterprise
- Organizations already standardized on SonarQube, Checkmarx, or Veracode
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Skip DeepSource if you need self-hosted or BYOK deployment but will not buy Enterprise, or if your review stack is already standardized on SonarQube or Checkmarx and you would be running two overlapping tools.
AI Review runs on a meter: after the $100 annual credit included per user, you pay $8 per 10K processed LOC (Standard) or $15 per 10K (Advanced), and large repos reviewed on every PR burn through it quickly.
Team at $24 per user/month billed yearly suits a 5–50 engineer org that wants PR-native review plus security scanning in one tool. Cheaper than Checkmarx or Veracode enterprise contracts and comparable to SonarQube's commercial tiers, but the per-LOC AI Review meter can push a heavy 20-engineer team past what CodeRabbit's flat seat pricing would cost. Budget the AI Review overage before committing, not after.
In short
Deepsource — AI code review platform that combines 5,000+ static analysis rules with an AI review agent on every pull request. Best for Teams whose AI coding assistants produce a large share of merged code, Engineering orgs that want deterministic quality gates alongside AI review, Companies that need OWASP Top 10 and SANS Top 25 mapped reports for audits. Free to start; paid plans from $24/user/mo.
No head-to-head comparison for Deepsource yet — the alternatives below are the closest matches we list.
What's new in Deepsource
Checked 2 days agoAcross the latest 5 updates: 3 feature updates, 1 pricing change and 1 news mention.
DeepSource is joining Harness
DeepSource announced it is joining Harness, the CI/CD and software delivery platform. Terms of the deal were not disclosed, so post-close pricing and roadmap are unconfirmed.
Reachability analysis for Java
SCA now runs reachability analysis on Java Maven projects, marking each dependency vulnerability Reachable or Unreachable at the bytecode level and showing the call path from your code into the vulnerable package.
AI Review on more programming languages
AI Review expanded to ten languages without a DeepSource static analyzer: Dart, Elixir, Apex, Groovy, Objective-C, VB.NET, PowerShell, Lua, Erlang, and Perl.
OSS vulnerability scanning for monorepos
SCA now reports per-sub-repository dependency results in monorepos, using each sub-project's own lock file or manifest, including npm, yarn, pnpm, bun, uv, and cargo workspaces.
Standard and Advanced AI Review tiers
AI Review split into Standard at $8 per 10K processed LOC and Advanced at $15 per 10K processed LOC, with Advanced adding multi-pass analysis and extended reasoning for critical changes.
What people actually say about Deepsource — is it worth it?
We ran a structured research pass across product reviews, community discussions, and post-purchase forum threads to surface the patterns vendors won't publish themselves. Below: the recurring strengths, the hidden costs people mention most, and the cohort that consistently regrets adopting this tool.
14 mentions across 3 sources (Hacker News, YouTube, Product Hunt), 12 more we could not attribute · researched Oct 15, 2026.
Weighted by the 26 posts each of 3 sources contributed.
- +PR-native inline comments and merge gates make fixing issues feel mandatory, not optional
- +Autofix patches ship alongside findings, turning review into a queue-clearing exercise
- +5,000+ deterministic rules back the AI agent, giving it grounding beyond raw LLM output
- +Secrets detection validated against 165+ providers, plus an open-source Narada model
- +OSS scanning with reachability and taint analysis reduces noise versus flat dependency lists
- −All published accuracy benchmarks are vendor-run and haven't been independently reproduced
- −AI Review priced per 10K processed LOC can balloon on large, high-churn monorepos
- −Early Product Hunt feedback flagged missing Ruby, JavaScript, and GitLab support
- −Harness acquisition terms are undisclosed, leaving roadmap and pricing uncertain
- −YouTube comments question whether AI-generated reviews compound AI-generated code problems
- • AI Review is metered per 10K processed LOC and stacks on top of seat-based plans
- • Large monorepos with high PR churn can push AI Review spend well past headline pricing
- • Advanced tier nearly doubles Standard's per-LOC rate for deeper AI analysis
Viability Score
How well maintained and how widely used is Deepsource? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: October 2026
How we score →Key Features
- Inline pull request review backed by 5,000+ deterministic static rules
- AI review agent in Standard ($8/10K processed LOC) and Advanced ($15/10K processed LOC) tiers
- Advanced tier with multi-pass analysis and extended reasoning for critical changes
- Autofix™ verified pre-generated patches for most detected issues
- Pull request gates that block merges when quality checks fail
- PR Report Card graded across security, reliability, complexity, hygiene, and coverage
- Structured feedback formatted for AI coding agents to iterate against
- MCP Server with 30 tools across 8 categories, authenticated via OAuth
- AI Review on ten languages without a static analyzer: Dart, Elixir, Apex, Groovy, Objective-C, VB.NET, PowerShell, Lua, Erlang, Perl
- Secrets detection validated against 165+ providers
- OSS dependency scanning with reachability and taint analysis
- Java Maven reachability marked Reachable or Unreachable at bytecode level with call paths
- Monorepo OSS scanning with per-sub-repository dependency results
- Automated code formatting on every PR
- Code coverage tracking with untested-line visibility and threshold enforcement
About Deepsource
DeepSource reviews your pull requests inside GitHub, GitLab, Bitbucket, or Azure DevOps, combining 5,000+ deterministic static rules with an AI review agent. Comments land inline on the PR: an unsorted itertools.groupby that would cause duplicate payouts, a shell=True command injection in your PDF export, an API key compared with == that leaks to timing attacks — each with an explanation of the risk. Autofix™ ships verified pre-generated patches for most findings, so you clear a queue instead of writing patches. PR gates block merges when checks fail, and the PR Report Card grades every PR across security, reliability, complexity, hygiene, and coverage — structured output you can feed back to a coding agent. Security coverage goes past linting: secrets detection validated against 165+ providers, OSS dependency scanning with reachability and taint analysis (Java Maven dependencies marked Reachable or Unreachable at the bytecode level with call paths, as of July 2026), per-sub-repository results in monorepos, IaC review for Terraform and CloudFormation, license compliance, coverage thresholds, and OWASP Top 10 / SANS Top 25 compliance reports. AI Review also covers ten languages with no DeepSource analyzer (Dart, Elixir, Apex, Groovy, Objective-C, VB.NET, PowerShell, Lua, Erlang, Perl). An MCP Server exposes 30 tools so agents can read findings and open fix PRs. In September 2026 DeepSource announced it is joining Harness; terms were not disclosed.
Behind the Verdict
DeepSource's strongest card is that it is not just an LLM reading diffs. A deterministic rule engine runs alongside the AI agent, so findings are reproducible and reviewable — you can trace a comment back to a named rule, which matters when a security team has to defend a gate. The AI layer sits on top to add the kinds of issues static rules miss in context, and the April 2026 engine rebuild (better agent architecture, new underlying models) pushed it to the top of the OpenSSF CVE Benchmark on all key metrics including F1, per the vendor's own changelog. Treat that benchmark claim as vendor-reported. Autofix™ is the practical differentiator for day-to-day work. Verified, pre-generated patches mean most findings arrive with a fix you can accept rather than a ticket to write. Combined with PR gates that block merges and the five-dimension Report Card, you get a loop: agent writes code, DeepSource grades it, the agent iterates against the grade via the MCP Server (30 tools, OAuth, added April 2026). That loop is the actual product story. Security depth is genuine, not checkbox. Reachability analysis on Java Maven projects marks each dependency vulnerability Reachable or Unreachable at the bytecode level and shows the call path (July 2026), which cuts advisory triage dramatically compared to a raw CVE list. Unknown is reported as unknown rather than silently downgraded to unreachable — the honest choice. Monorepos get per-sub-repository dependency results using each sub-project's lock file (May 2026), including npm, yarn, pnpm, bun, uv, and cargo workspaces. Where it gets expensive: AI Review is metered on processed LOC. Team includes $100 in annual credits per user, then $8 per 10K processed LOC on Standard or $15 per 10K on Advanced. A large repository reviewed on every PR burns credit fast, and the Advanced tier is deliberately priced nearly double for multi-pass analysis on critical changes. The free Open Source tier is generous for public repos but caps PR reviews and formatting at 1,000 per month and excludes OSS vulnerability scanning and license compliance. Where it does not fit: teams that need self-hosted, airgapped, or BYOK deployment are pushed to Enterprise with custom pricing — no published number. Anyone already standardized on SonarQube, Checkmarx, or Veracode has little reason to run two review stacks. And the September 2026 Harness announcement, with terms undisclosed, is a real planning risk: roadmap direction, pricing, and contract terms after the deal closes are unknown. For a three-year commitment, that uncertainty is worth naming in your procurement notes.
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Real-world workflow fit
Concrete scenarios for the personas Deepsource actually fits — and what changes day-one when you adopt it.
You connect GitHub, DeepSource auto-detects your languages and suggests analyzers, then runs a baseline review on an open PR. You enable PR gates on security and coverage so nothing merges red.
Outcome: Within the first day every PR carries inline findings plus a five-dimension Report Card, and merges block automatically when a security check fails.
You turn on OSS vulnerability scanning and let reachability analysis flag which Java Maven dependencies your code can actually call into, ignoring advisories marked Unreachable.
Outcome: Your triage queue shrinks to exploitable vulnerabilities with call paths you can hand to the owning team, and audit reporting maps straight to OWASP Top 10 and SANS Top 25.
You add the MCP Server with the add-mcp utility, and your agent reads PR findings, queries report card grades, and opens targeted fix PRs via OAuth with no manual token setup.
Outcome: The agent iterates against DeepSource's structured feedback until the PR grade improves, so you review outcomes instead of writing fixes.
Use Cases
- Catch bugs, anti-patterns, and security issues inline on pull requests before merge
- Enforce quality gates so PRs that fail security, coverage, or complexity checks cannot merge
- Scan OSS dependencies and prioritize only vulnerabilities your code can actually reach
- Let AI coding agents pull findings and open fix PRs through the MCP Server
- Track coverage and enforce thresholds so untested code cannot ship
- Produce audit-ready OWASP Top 10 and SANS Top 25 reports
- Review Terraform and CloudFormation for misconfigurations before deployment
- Catch copyleft and restrictive licenses before they create legal exposure
Models Under the Hood
as of 2026-10-16
Limitations
- AI Review is metered on processed LOC: Team includes $100 in annual credits per user, then $8 per 10K processed LOC (Standard) or $15 per 10K processed LOC (Advanced).
- The free Open Source tier caps PR reviews, AI Review, Autofix, and code formatting at 1,000/month and excludes OSS vulnerability scanning and license compliance.
- Self-hosted deployment, BYOK for AI Review, airgapped deployment, SSO, IP restrictions, and security audit logs require Enterprise, priced custom.
- Standard and Advanced split by review depth rather than language, so multi-pass review on critical changes costs nearly twice the standard rate.
- The September 2026 Harness acquisition was announced with terms undisclosed, so post-close roadmap and contract terms are unknown.
- Reachability analysis currently runs on Java Maven projects with a pom.xml; other ecosystems get standard dependency scanning.
as of 2026-10-20
Verification history
We have re-verified Deepsource 18 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
- — re-checked, vendor evidence unchanged
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-checked, vendor evidence unchanged
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-checked, vendor evidence unchanged
Showing the 6 most recent of 18 verification passes.
Free to cite with attribution — this page re-verifies continuously.
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Where the pricing makes sense
The company stage and team size where Deepsource's pricing actually pencils out — and where peers do it cheaper.
Team at $24 per user/month billed yearly suits a 5–50 engineer org that wants PR-native review plus security scanning in one tool. Cheaper than Checkmarx or Veracode enterprise contracts and comparable to SonarQube's commercial tiers, but the per-LOC AI Review meter can push a heavy 20-engineer team past what CodeRabbit's flat seat pricing would cost. Budget the AI Review overage before committing, not after.
Setup time & first value
How long it actually takes to get something useful out of Deepsource — broken out by persona, not the marketing-page minute.
Signup to first review is quick: authorize GitHub, GitLab, Bitbucket, or Azure DevOps, pick a repository and open PR, confirm the auto-detected analyzers, and the baseline review usually completes in a minute or two. Enabling the MCP Server for an agent is a single npx add-mcp command. Reaching steady state — tuned gates, suppressed noise, coverage thresholds, and budgeted AI Review tiers —
Switching to or from Deepsource
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From SonarQube: connect your repos and let DeepSource auto-detect languages, run the first review to build a baseline, then mirror your existing quality gate as a PR gate before switching off the old check.
- →From Semgrep: keep your custom rules where they still apply and use DeepSource's 5,000+ built-in rules for coverage you were writing yourself, then move secrets and dependency scanning over.
- →From CodeRabbit: DeepSource adds deterministic static rules, IaC review, license compliance, and OWASP/SANS reporting on top of AI PR comments, so the gap to close is mostly analyzer configuration.
- ↗To SonarQube: export issue suppression rules and gate thresholds first; SonarQube self-hosted covers the on-prem requirement DeepSource reserves for Enterprise.
- ↗To Semgrep: port custom rules and keep dependency scanning separate, since Semgrep's strength is rule authoring rather than the bundled SCA and license workflow.
Integrations
Resources & Guides
Tutorials & Learning
YouTube returned 6 videos for “Deepsource”, and we withheld 6: 6 could not be judged, because “Deepsource” is a single word that other videos use for other things. We are showing none, because we could not prove any of them are about Deepsource.
Official links
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