A context bank for world understanding.
A deterministic engine turns scattered sources into knowledge graphs — contradictions preserved, gaps named. Structure your understanding, and share it your way — privately, with your team, or via a public link.
your understanding of any knowledge space
it with your team, or publish a read-only link
how others structured the same space
How 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.
Who it's for.
Engineering teams
Onboard new members faster. See the structure of your architecture docs and runbooks — dependencies mapped, gaps named.
Researchers
Synthesize across conflicting papers. Surface contradictions before you build on the wrong finding.
AI developers
Give your agents structured context, not retrieval guesses. Clean, source-grounded knowledge — MCP integration ships soon.
Understanding, structured and shared.
See the structure
Drop in your sources. The engine compiles the knowledge space — dependencies mapped, gaps named, every claim source-anchored.
Contradictions preserved
When sources disagree, nothing gets averaged away. Competing claims stay visible, branched, and reviewable.
Share and build on
Share a canvas privately, with your team, or via a public read-only link. Every claim keeps its source — the structure is yours to build on.
Deterministic, always
Structure, provenance, and trust are deterministic — no hallucinated synthesis, unapproved claims are never served as truth. Content extraction is a reviewed draft.
Questions you'll
actually have
What is a context bank?
A shared reservoir of structured understanding. You contribute your structure, you draw on others, and the bank grows for everyone.
What if my sources disagree?
SILKLEARN preserves the contradiction instead of averaging it away. Competing claims stay visible and branched — you decide, with the evidence in front of you.
How is this different from ChatGPT?
ChatGPT generates answers — stochastically. SILKLEARN compiles structure — deterministically. Every claim source-anchored, nothing served as truth without approval.
Do I need to reformat my documents?
No. PDFs, Markdown, DOCX, plain text — drop them in as-is.
Can AI agents use it?
Yes. Every output is consumable via MCP — your agent gets structured context, not a retrieval guess. MCP integration ships soon; join the waitlist.