distill

You distill unstructured inbox documents into structured knowledge notes by feeding raw materials into a distillation workflow that outputs markdown files like domain-model.md and business-rules.md. This process preserves original context and enforces traceability mapping to the source documents.

The best way to create an audit-friendly glossary from technical documents is to distill the inbox materials into a structured glossary.md file. This consolidates domain terms and acronyms while maintaining traceability to the original source context and intent.

Yes, you can generate API specifications and tech decision records from RFPs by distilling the source documents. The workflow produces explicit outputs including api-spec.md, tech-decisions.md, and ADRs to capture technology decision rationales and requirements for implementation.

You map non-functional requirements from scattered inbox documents by processing the raw materials through a structured distillation workflow. This consolidates organizational knowledge into a non-functional-requirements.md file, reducing manual workload and preserving the original intent of the source text.

Yes, distilling organizational knowledge requires traceability to source materials to preserve original context and intent. The distillation implementation enforces explicit outputs and traceability mapping, ensuring that generated notes, glossaries, and models remain audit-friendly for review.

Automated domain model design from RFPs targets specific organizational knowledge consolidation needs like entities, attributes, and relationships, but requires explicit source materials. It outputs structured markdown but relies on the quality of inbox inputs to accurately capture domain terms and business rules without manual intervention.