Built for how teams actually work.
Engineering onboarding. Research synthesis. AI context preparation. One graph engine, three workflows.
Engineering onboarding
New engineers spend weeks figuring out the codebase. Upload architecture docs, READMEs, runbooks, and decision records. SILKLEARN reads across everything and surfaces the dependency order — so they know what to read first instead of guessing.
Research synthesis
Multiple papers, conflicting findings, no clear synthesis. Upload your sources. SILKLEARN maps which findings depend on which foundations and surfaces where sources contradict each other — before you build on the wrong assumption.
AI context preparation
AI agents need structured context, not raw documents. Feed any sources into SILKLEARN. It maps the dependency structure and hands your agent clean, source-grounded context it can actually reason across — ordered, reviewed, linked to source.
Built for how teams
actually work with knowledge.
Three workflows. One graph engine.
Engineering onboarding
Upload architecture docs, READMEs, runbooks, and decision records. SILKLEARN builds a graph of your codebase knowledge — so new engineers can explore and query instead of guessing what to read first.
Learn moreResearch synthesis
Upload papers, reports, and sources across a topic. SILKLEARN surfaces dependencies between findings and flags contradictions automatically — before you build on the wrong foundation.
Learn moreAI context preparation
Feed any sources into SILKLEARN. Your AI agents get structured, source-grounded context from the graph — not a retrieval guess. Consumable via MCP.
Learn moreHow it works.
Three steps. No manual structuring.
Add your sources
PDFs, docs, Notion, code, web links. Drop them in as-is.
SILKLEARN finds the structure
It reads across everything, surfaces connections, and flags contradictions.
Use it your way
Get a path. Get a map. Feed your AI. The structure is yours.