Extraction

Extract Knowledge

Pull code, proofs, and structured outputs from conversations into reusable knowledge assets.

Extract Knowledge

Pull reusable outputs from conversations and documents — code blocks, mathematical proofs, summaries, and structured excerpts — and store them as indexed, searchable knowledge assets. Stop losing the valuable parts of AI conversations.


Core Capabilities

Identify Isolate Index
Automatically detect extractable outputs in conversation content. Pull outputs cleanly from surrounding context with full provenance. Store extracted outputs in a searchable library for reuse.

The Problem

"The best insights are buried in chat"

A 300-message AI conversation might contain 5 genuinely reusable code blocks, 2 important insights, and 1 critical architectural decision. The rest is iteration, refinement, and small talk. Manual extraction doesn't scale.

"Copy-paste is lossy"

When you copy a code block from a conversation into a file, you lose the reasoning that produced it, the alternative approaches that were rejected, and the context that makes it understandable six months later.

"I keep re-solving the same problems"

Without extraction, the same questions get asked and re-answered across sessions. Knowledge doesn't accumulate — it dissipates.


How Keimenon Approaches This

1. Automatic Detection

Keimenon identifies extractable content in parsed conversations — code blocks by language markers, proofs by logical structure, summaries by position and formatting.

2. Context-Preserving Extraction

Extracted outputs carry provenance — which conversation, which message, what surrounding context. The extraction links back to the original, not just the isolated snippet.

3. Verification Pipeline

Extracted outputs flow into the Verification Workspace for human review before they're marked as trusted knowledge assets.

4. Reuse Infrastructure

Indexed outputs are searchable, taggable, and embeddable. Reference them in new conversations, include them in publications, or deploy them in codebases.


Products for Knowledge Extraction

Extraction Studio

Extract Store Reuse
Identify and isolate reusable outputs from any source. Index into a searchable, tagged snippet library. Reference and re-deploy across projects and publications.

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Verification Workspace

Verify Trace Inspect
Check outputs against original source material. Follow the extraction chain to its origin. Side-by-side context view with source evidence.

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Related Solutions

Related Use Cases

  • For Developers — Extract code, patterns, and decisions from AI sessions
  • For Researchers — Isolate proofs, findings, and structured data
  • For Students — Extract key concepts and summaries from study material

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