Product · Conduit

Context intelligence.
Cryptographic proof.

Conduit is a trust-mediated context broker. It sits between your query and the model, delivering verified context at the right moment — with a cryptographic proof of every source it touches.

RAG Fails. Conduit Delivers.

Same corpus. Same query. Different answer.

Retrieval-Augmented Generation returns whatever fragments its keyword match happens to surface. Conduit returns a grounded, cited answer. The pattern is the point.

Literary query · 1.2 MB corpus "Why does Ahab hunt the whale?"

RAG returns the book's table of contents. Conduit returns the passage describing Ahab's "unabated rage" and "audacious, immitigable, and supernatural revenge."

Moby-Dick Ahab query benchmark
Technical query · 26 MB codebase "How does the tokenizer work?"

RAG returns CONTRIBUTING.md — rules for AI contributors. Conduit returns the actual tokenizer code with inline documentation.

llama.cpp tokenizer benchmark
Abstract query · prose corpus "What is the thematic meaning of the whale?"

RAG returns the book's epigraph section — historical whale quotes by Goldsmith, Burke, and Cook.

Thematic meaning benchmark
Conduit answering the same query Five-point thematic analysis

Each claim tagged [FROM CONTEXT] with provenance. Grounded in direct textual citations from the loaded corpus.

Conduit thematic analysis
Synthesis across distributed passages "What does the doubloon mean to each crew member?"

Seven named characters, each interpretation cited with direct quotes, closing on a Rorschach-test reading of the coin.

Doubloon synthesis

RAG optimizes for keyword density. Conduit optimizes for semantic grounding with cryptographically verifiable provenance. The output isn't just better — it's auditable.

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