Query your documents like a database.
The platform layer beneath document processing. Your schema, your cloud, your rules.
Let's chatOne language. DDL and DML.
You declare the schema. You query the result.
DDL declares the entities and edges that matter to you. Extraction fills them from your documents. DML queries the result. Built, and running live.
-- DDL: you declare the entities and edges. Your shape, not ours.CREATE ONTOLOGY contracts; CREATE ENTITY contracts.Party ( name TEXT KEY, role TEXT ) UNDER contracts.Contract; CREATE EDGE contracts.signed_by ON contracts.Contract REFERENCES contracts.Party LINK BY signatory RESOLVE FUZZY;Switch tabs to walk the flow — declare the schema, extract, then query across edges and search. The real Studio, with example queries.
The engine
The graph is the schema you declared.
Whatever your documents are, you define the shape — entities and the edges between them. Your queries run over that graph. The graph is the engine. SerchaQL is how you use it.
Vendor contracts
Every agreement, its parties, and what renews when.
›SELECT party, renewal_date FROM Contract JOIN Party VIA signed_byOne platform, end to end
It flows in. It flows out.
Connect the tools you already use. Corpuses, ontologies, and extractions do the work in the middle. Your people, agents, and apps draw from it — no five-vendor pipeline to stitch together.
Corpuses
Ontologies
Extractions
Graph
From raw file to structured knowledge
A PDF can't be reasoned about. A clause inside it can.
Sercha pulls the sections, clauses, and obligations out of dense documents and writes them back as first-class entities — each one named and linked to the standard behind it.
What “understanding” actually means
Start with one of your hardest documents.
It finds the parts that matter.
Parties, terms, clauses — the things inside.
And how each one connects to everything it touches.
Always accounted for
Every document in. Every entity built.
Each sync and extraction run is recorded and hash-chained — added, updated, deleted, sealed, failed — and queryable, all inside your own cloud.
Ingestions
documents touched
2,670
Documents added, updated, and deleted per sync
Extractions
runs
94
Pipeline runs writing entities into the graph
What could your business do with Sercha in your hands?
We'll show you what it looks like on your own documents.
Let's chat