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Use cases

Research synthesis and knowledge paths from any source.

The structure is already implicit in the material. Your sources reference each other, assume prior concepts, and quietly contradict each other — but none of them tell you which one to read first. That order isn't missing. It's just not visible yet.

Best fit

This is where it pays off before you spend hours reading in the wrong order.

Twenty sources, no obvious starting point
They contradict each other and neither flags it
You finish one, realize you needed another first
The structure exists — it's just invisible

Workflow fit

Start where missing context is already costing something.

Use case 1

You joined a codebase. The docs exist. The reading order doesn't.

Upload the architecture docs, READMEs, runbooks, and decision records. SILKLEARN maps the dependency order so you know what to read first instead of guessing.

Use case 2

You're working across multiple sources. They quietly disagree on the foundations.

Upload the papers, reports, and sources you're working across. SILKLEARN maps which findings depend on which foundations, and surfaces where your sources contradict each other.

Use case 3

You're building AI workflows. Your agents need structured knowledge, not a retrieval guess.

Feed any sources into SILKLEARN. It maps the dependency structure and hands your agent a context bundle it can actually reason across — ordered, reviewed, and linked to source.

Next step

Pick one workflow. Run it through. See what your sources actually contain.