Structure extraction
Early access is open.Check availability →
Synthesize any source into structure.
The order was always in your sources.
Compile
Review
Ship
Three steps from any source to a path you can follow.
Architecture specPDF
Escalation runbookDOCX
Research papersPDF
3 sources indexed
Step 01
Drop in your docs, exactly as they are.
PDF, Markdown, DOCX, Notion, Confluence. No reformatting needed.
Apply for accessAuth model
root
Access policy
layer 2
Incident recovery
layer 2
Escalation flow
output
4 dependencies mapped
Step 02
See the structure. Confirm it before you follow it.
See every dependency as it's mapped. Inspect connections and source links before you commit to a learning path.
Apply for accessReading path
dependency-ordered
Synthesis bundle
cross-source
Contradiction log
conflict map
3 outputs ready
Step 03
Get a path you can follow from the first source you add.
Learning path, synthesis bundle, or AI context — from one source-linked structure.
Apply for accessWhat it does
Four capabilities. No overlap.
What it does
Four capabilities. No overlap.
Structure extraction
Canvas Review
Contradiction Detection
AI Context Bundles (coming soon)
Why this works
You can’t navigate what you can’t see.
Map the order, source, and dependencies before you start reading — or you’re guessing at which pieces to trust.
Common questions
Core questions, answered directly.
Anything text-based today: PDFs, docs, Notion pages, web links, code repos. Video, audio, and API feeds are coming. The synthesis engine works on any source you can point it at.
Those tools answer questions about your sources. SILKLEARN synthesizes the structure of your sources. It doesn't wait for you to ask — it runs at ingest, maps what depends on what, and flags where sources contradict each other. The output is a path that persists, not an answer that disappears.
A dependency-ordered path through your sources, a visual graph of what connects to what, and a list of contradictions detected across your material — so you know what to read first, what to question, and what order actually matters.
Anyone synthesizing knowledge from multiple sources — researchers reconciling conflicting papers, developers onboarding to an unfamiliar codebase, consultants distilling client materials, or solo learners who need a path, not a pile. Individual-first by design.
Yes — MCP integration is in progress. Any AI agent will be able to call the synthesis engine directly, get back a structured dependency map, and use it as clean context for downstream reasoning. This is what RaaS (Results-as-a-Service) means: the output works for humans AND agents.
The platform is individual-first — built for the person doing the synthesis, not the org buying seats. Canvas (the visual review layer) supports sharing and collaboration, but the core product is yours to run alone. Enterprise (private cloud deployment) is coming.
Early access
The structure is already there.
Apply if you're working from a stack of sources with no clear path.
Source-linked paths, not generic summaries.
Reviewed before you commit to it.