Don't just grep. Query patterns, logic, and the blast radius of every change across your indexed library, or from hundreds of codebases. Sub-second semantic retrieval for human engineers and AI.
Popular queries:
When agents edit a file, they rarely know what else depends on it. This blind spot causes silent regressions, breaks production, and forces teams to add manual review gates.
Map every file, function, and dependency before the edit ships, and stop AI-caused outages before they happen.

How we turn raw codebases into a blast-radius-aware map in minutes.
Paste a URL or connect GitHub. We automatically ingest your repo, map the dependency graph, and clean the boilerplate.

We convert massive codebases into a token-optimized, searchable map ready for your agents' context windows.

Run high-speed queries and deploy agents with a grounded map. Plug this context anywhere via MCP, or API.

Raw code hides the blast radius. Code Fundi maps the signal.

We map code structure and flow, not just text. See every file that breaks before your agent edits it.
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Automatically convert entire repos into a token-optimized, structure-aware map. Perfect for RAG, documentation, and prompt engineering.
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Execute sub-second queries across multiple public repos simultaneously. Find the needle in the dependency graph.
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Stay informed as your codebase evolves, so human teams and agents never lose track of what changed or what it affects.
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The primary API for parallel agent teams. Scale your infrastructure to handle QA, documentation, and complex refactoring.
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Generate high-quality datasets directly from your codebases for custom model fine-tuning and post-training.
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See how CodeFundi works for your use case firsthand.
What teams say about Code Fundi.
βCodeFundi is modelling its system on how real engineering teams work.β
TechCabal
βThis is a good one for developers. Definitely adding Code Fundi to the list of tools to watch out for.β
Team at The AI Colony
βI have used more than a few LLM coding tools, and none of them came even close to the quality of code that this pumps out. Code is almost without exception correct and runs first time.....installation is simple and this kills the other AI coders still in the water.β
Senior Engineer
βCodeFundi is modelling its system on how real engineering teams work.β
TechCabal
βThis is a good one for developers. Definitely adding Code Fundi to the list of tools to watch out for.β
Team at The AI Colony
βI have used more than a few LLM coding tools, and none of them came even close to the quality of code that this pumps out. Code is almost without exception correct and runs first time.....installation is simple and this kills the other AI coders still in the water.β
Senior Engineer
βI have been using it on @trypearai and it's incredible.β
Developer
βBest LLM out there. Very concise and easy to use.β
Founder
βVery useful AI assistant I endorse.β
Web Developer
βI have been using it on @trypearai and it's incredible.β
Developer
βBest LLM out there. Very concise and easy to use.β
Founder
βVery useful AI assistant I endorse.β
Web Developer
βCodeFundi is modelling its system on how real engineering teams work.β
TechCabal
| Capabilities | CodeFundi | TryNia | Context7 | Supermemory | Copilot |
|---|---|---|---|---|---|
Blast-Radius Guard Visualizes the blast radius and downstream effects of code changes across services, before the edit ships. | |||||
Codebase Map Distillation Strips 50% of boilerplate noise into a logic-dense, token-optimized codebase map. | |||||
Structural Dependency Mapping Understands logic hierarchy and what breaks downstream, not just text-based similarity. | |||||
Multi-Repo Search Query patterns across multiple public repos with semantic and grep retrieval. | |||||
Native Developer and Agent Integration Built-in Cursor, VS Code and MCP for Claude/Agentic tool use. | |||||
Deterministic, Grounded RAG Eliminates LLM 'drifting' by grounding every response in verified line-number context and the blast radius of every change. | |||||
Training Data Factory Export file-by-file logic and patterns into fine-tuning datasets for custom LLMs. | |||||
Zero-Data Retention (ZDR) Enterprise-grade privacy; proprietary code is never used for training public models. |