Tutorials
Step-by-step guides for building common document intelligence workflows.
Each tutorial walks through one endpoint end to end, with copy-pasteable examples. New to retrieval-augmented generation? Start with From documents to answers to learn the concepts and pick the right endpoint. Otherwise, jump straight to Uploading & managing files, then Searching documents.
Build a searchable knowledge base
Ingest documents once, then query them. A persistent, indexed corpus you can search or ask questions over.
Uploading & managing files
Upload documents into Context212 so they become searchable in seconds, plus tagging, metadata, listing, and filtering.
Searching documents
Find the most relevant passages with a natural-language query, with scoping, reranking, and vision-mode search.
Asking questions
Get a grounded, LLM-generated answer with the sources it used, returned synchronously or streamed token by token.
Classify and organise documents
Two layers that compose: partition files into workspaces and group them with tags. Pick the simplest one that solves your problem.
Workspaces
Hard containers that isolate a team's, customer's, or tenant's documents. The only layer that's also a permission boundary, via workspace-scoped API keys.
Tags
Flat, reusable labels that group documents into collections, even across workspaces.
Ontology
Typed concepts and relations so you can filter documents by what they're connected to.
Ontology overview
Adopt a schema, link documents into a graph, then filter Search and Ask with relation.
Define an ontology
Templates, concept types, and relation types.
Filter with relations
The relation DSL for Search and Ask.
Process documents on the fly
Convert or extract from a document in a single call. Nothing is stored, useful for feeding your own pipeline.