Table of Contents
Unblocked Code Review
AI code review that sees your context, not just your diff. Unblocked draws on context from your whole repo, Slack, Jira, docs, PR history, and more. Every comment moves the conversation forward with cited sources. The result: high-signal comments you’ll actually want to implement.
Key Features
- Deep context engine: Ingests code, Slack conversations, Jira tickets, documentation (Notion/Confluence), and full PR history to understand why code was written.
- High-signal PR comments: Flags logic errors, race conditions, and security risks with an understanding of your specific business logic.
- CI failure analysis: Automatically analyzes build logs and suggests actionable fixes directly in the PR.
- Conversational PR chat: Developers can tag
@unblockedin comments to ask deep questions or request iterations on suggested code. - Context-aware summaries: Generates PR descriptions that link to related work and past team discussions.
- Cited sources: Every AI recommendation includes citations to the specific slack thread, doc, or code snippet it learned from.
- Customizable rules: Define team-specific review guidelines and feedback strictness.
- Broad integration support: Works with GitHub, GitLab, and Bitbucket.
How It Works
Teams connect Unblocked to their version control systems, Slack workspace, issue trackers (Jira/Linear), and documentation. Unblocked continuously syncs to build a semantic knowledge graph of your team’s code, decisions, and architectural patterns. When a developer opens a PR, Unblocked analyzes the diff not just against syntax rules, but against this deep historical context. It surfaces relevant past discussions, identifies inconsistencies with agreed-upon architecture, and posts in-line comments. If CI fails, it diagnoses the error logs and proposes fixes. Developers can interact with the AI directly in the PR threads to refine the code before merging.
Use Cases
- Context-rich code review: Catching subtle logic bugs that linters miss.
- CI/CD debugging: Instantly resolving build failures without digging through raw logs.
- Onboarding: Helping new devs understand the “why” behind legacy code without pestering seniors.
- Reducing review latency: Giving immediate, actionable feedback before a human reviewer steps in.
- Knowledge capture: Turning implicit Slack decisions into explicit code review context.
Pros and Cons
- Pros: Context-aware beyond just code diffs (knows what you discussed in Slack); Citations build trust by showing sources; Actionable CI fixes save significant debugging time; Integrates with major Git platforms; SOC 2 compliant security; Built by a veteran team from tech giants.
- Cons: Requires granting access to sensitive internal data (Slack/Docs) for full value; Initial setup involves connecting multiple data sources; May generate noise if the underlying documentation is outdated; Pricing models for enterprise can be opaque; “High-signal” promise depends heavily on the quality of your existing written context.
Pricing
- Free Trial: Available (typically 14-21 days, check site for current offer).
- Business: Paid per-user monthly subscription (e.g., ~$19/user/mo).
- Enterprise: Custom pricing for SSO, on-prem support, and advanced security.
How Does It Compare?
Unblocked Code Review competes in a rapidly evolving market of AI developer tools. Here is how it stands out:
- CodeRabbit: The market leader in AI code reviews. CodeRabbit is excellent at catching bugs and summarizing PRs based on the code context. Unblocked differentiates by pulling in external context (Slack discussions, Jira specs) to catch errors where the code is valid but the logic contradicts a business requirement decided in a chat.
- GitHub Copilot: Now offers PR summaries and some review features. Copilot is deeply integrated into the editor but often lacks the broader “organizational memory” of past decisions made outside of GitHub. Unblocked acts as this missing memory layer.
- Greptile: Similar to Unblocked, Greptile focuses heavily on “understanding the entire codebase” for Q&A. Unblocked focuses more specifically on the active workflow of the Pull Request, injecting that understanding directly into the review process.
- Ellipsis: Another strong contender that can “fix” code autonomously. Unblocked emphasizes the “Human-in-the-loop” aspect by citing sources and facilitating a conversation, rather than just silently pushing commits.
Final Thoughts
Unblocked Code Review addresses the biggest gap in current AI coding tools: Context. While other tools look at the code you wrote today, Unblocked looks at the decision you made last month in Slack that explains why you wrote it that way. For teams that suffer from “knowledge silos” or have complex business logic scattered across tickets and chats, Unblocked provides a unique “archaeological” layer to code review that standard linters or simple LLM wrappers cannot match. It transforms code review from a syntax check into a knowledge-sharing event.