cognos-pipeline

To transform raw meeting notes into atomic knowledge notes, you can process them through a 6-phase pipeline (Record, Reduce, Relate, Reflect, Reweave, Review) that breaks down complex information into granular, linked notes.

An information processing pipeline for knowledge management orchestrates sequential phases to convert raw, unstructured input into organized, interconnected notes, ensuring no insight is lost and all information is processed systematically.

You can automatically link new insights to an existing knowledge graph by passing information through the Relate and Reweave phases, which synthesize overarching themes and update older notes with new context.

Yes, you can process any unstructured text input through this pipeline to create structured, linked notes, as it manages sequential agent execution and artifact passing to build a robust knowledge graph.

The pipeline does not require external dependencies, relying instead on filesystem artifact passing, logs, and queue files to manage state tracking and ensure deterministic information processing.

Filesystem-based state tracking in a knowledge pipeline relies on local logs and queue files for sequential agent execution, meaning it is designed for deterministic processing rather than distributed or concurrent operations.