Code Fundi

Code Fundi turns a codebase into a searchable, structured map designed to give AI coding agents and human engineers fast, accurate context about a project. Instead of relying on plain text similarity, it distills a repository into a token-optimized map that captures structural dependencies and logic hierarchy, so agents and developers can query code patterns, trace relationships, and get sub-second semantic search results across single or multiple repositories. A "blast-radius guard" maps dependencies between parts of the code so a change's downstream effects can be seen before it ships, which is aimed at reducing regressions in large or unfamiliar codebases. The platform also offers real-time observability into how a codebase evolves over time, and can export training data for teams building or fine-tuning their own coding models. Code Fundi integrates as an extension in VS Code, Cursor, and Windsurf, and exposes its codebase map through MCP (Model Context Protocol) and a cURL-based API, with zero-data-retention as an enterprise privacy option. The product targets teams building AI coding agents, software engineers working in legacy or unfamiliar codebases, technical due-diligence reviewers, and DevRel teams producing documentation. Pricing runs on a credit-based free-to-paid tier structure. One limitation: because retrieval depends on how well the map distillation captures a given codebase's structure, results may vary across different languages or frameworks.