Built for how teams actually work.
Engineering onboarding. Research synthesis. AI context preparation. One knowledge graph engine, three workflows.
Engineering onboarding
New engineers spend weeks figuring out the codebase. Upload architecture docs, READMEs, runbooks, and decision records. SILKLEARN compiles them into a knowledge graph — structure visible, gaps named, contradictions flagged before they cost anyone a week.
Research synthesis
Multiple papers, conflicting findings, no clear synthesis. Upload your sources. SILKLEARN compiles them into a knowledge graph — foundations mapped, contradictions preserved, gaps named — so you build on structure, not on the wrong assumption.
AI context preparation
AI agents need structured context, not raw documents. Feed any sources into SILKLEARN. It compiles a deterministic, source-anchored context bank your agent can reason across — every claim traced to its source, contradictions preserved.
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 the compiled structure instead of guessing.
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. MCP integration ships soon.
Learn moreHow it works.
Three steps. Structure first, every time.
Add your sources
PDFs, Markdown, DOCX, plain text. Drop them in as-is.
The engine compiles the structure
Dependencies mapped, contradictions preserved, gaps named — every claim source-anchored.
Share it your way
Private, with your team, or a public read-only link. Your understanding, your call.