Component Selection
TrendRadarTrend discovery and signal filtering
Crawlee / PlaywrightWeb collection and incremental crawling
RAGFlowParsing, chunking, indexing, and retrieval
LangfuseRetrieval quality, answer quality, and cost traces
AI Knowledge Pipeline
The goal is not deploying a single RAG tool. It is a durable pipeline for signals, ingestion, parsing, retrieval quality, and evaluation.
[ PIPELINE ]
Scenario CaseAI Knowledge Pipeline
From information noise to structured knowledge assets
The goal is not deploying a single RAG tool. It is a durable pipeline for signals, ingestion, parsing, retrieval quality, and evaluation.
Decision Boundaries
- Classify sources first.
- Separate collection, parsing, indexing, and evaluation when volume grows.
- Keep bad cases and retrieval metrics.
Signal discovery
Filter sources by topic, keyword, and value.
Collection
Fetch pages, attachments, transcripts, and structured data.
Parsing
Apply OCR, layout recognition, semantic chunking, and metadata extraction.
Evaluation
Use real questions to test recall, citations, and answer quality.