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Mantic is an infrastructure layer designed to remove context retrieval bottlenecks for AI agents. It addresses the limitations of slow vector search, inefficient grep, and wasted tokens by implementing a unique "metadata-first" approach. Instead of reading code or relying on expensive embeddings, Mantic infers intent from structural cues like file paths, names, and dependency graphs. This method allows for sub-300ms context retrieval, significantly outperforming traditional methods and enabling AI agents to access relevant code context deterministically and efficiently.
