Usable source information
Ingest, clean and parse documents and structured data. Apply OCR where needed and check quality before indexing.
Turn documents, data and disconnected systems into a usable, permission-aware knowledge layer.
Discuss your AI projectWhat the engagement delivers.
Ingest, clean and parse documents and structured data. Apply OCR where needed and check quality before indexing.
Retrieve relevant approved material before composing an answer—a pattern called retrieval-augmented generation, or RAG. Show the supporting sources.
Build APIs, database connections and webhooks with knowledge refresh, versioning, retention and deletion rules.
A colleague asks a policy question. The system searches the documents they may access and presents an answer with the relevant source passages.
Document repositories, CRM, ERP and databases are connected subject to access, export options and provider constraints.
Source permissions must flow through retrieval. Test access boundaries, stale information and conflicting evidence.
Store and process each data class in an agreed environment, with explicit routes for any external model calls.
Source count, formats, document quality, permissions, refresh frequency and deletion requirements influence scope.
Explore your requirementsNot necessarily. Retrieval looks up approved information at request time; fine-tuning changes model behaviour and is a separate decision.
Yes, when the source permissions and identity integration support it. Those boundaries must be designed and tested.
Tell us what you want to build, connect or improve.
We’ll help define the architecture, the delivery and what it takes to run it.