AI code review that knows when to chime in
Unblocked surfaces the context developers and their agents need to generate reliable code, reviews, and answers. We continuously build and maintain context from your code, docs, planning tools, conversations, and runtime signals. This gives your AI tools the team-specific understanding they need to generate code that matches your standards, flag issues that other tools miss in reviews, and answer questions without the scavenger hunt. It's the context layer your AI tools are missing.
Unblocked assembles incident data in seconds by correlating commits, config changes, and Slack activity. Developers can identify whether a bug is real, related to recent changes, or has occurred before—without opening multiple tabs or manually searching across systems.
Unblocked surfaces relevant context automatically during PR review by analyzing team standards, past decisions, and prior art. Reviewers see not just what code does, but whether it fits team conventions, eliminating manual digging through Slack, docs, and commit history.
Unblocked MCP connects Claude, Cursor, Copilot, and other agents to organizational context including Slack conversations, Confluence docs, Jira tickets, and PR history. Agents receive the context needed to make informed decisions and avoid hallucinating or missing critical constraints.
New hires can ask Unblocked questions about the codebase, architecture, and past decisions and receive instant answers with citations to code, PRs, Slack threads, and docs. This reduces interruptions to senior engineers while helping new developers get productive faster.
Unblocked Code Review grounds AI code generation in decision-grade context from your codebase, Slack conversations, docs, and tickets. This allows AI agents like Claude, Cursor, and Copilot to generate mergeable code on the first try by understanding team conventions, architectural patterns, and prior decisions—reducing rework and token waste.