Temporal knowledge graph for codebases that captures decision traces, links test failures to code changes, learns co-edit patterns, predicts regression risk, and enforces learned constraints at the edit boundary via a PreToolUse hook.
An intelligent debugging assistant that automates the debugging process by analyzing bugs, injecting HTTP-based debug logs into code across multiple environments (browser, Node.js, mobile, etc.), and iteratively fixing issues based on real-time feedback.
An active, stateful software knowledge graph engine that serves as an 'all-knowing development partner' for AI agents and human developers by modeling software projects into queryable knowledge graphs.
Enables coding agents to query and commit to a research graph that remembers failed experiments, ensuring reproducibility and preventing redundant work.
Provides AI coding agents with persistent memory by recording sessions and normalizing them into a searchable knowledge graph, then delivering relevant context at the start of the next session.
