RAG Development Services
Sabentech builds retrieval-augmented systems that let an AI assistant answer questions grounded in your own documents and data, not general web knowledge.
Where this helps.
- 01Internal knowledge spread across documents that are hard to search
- 02An AI assistant giving generic answers instead of ones grounded in your material
- 03A need for answers that cite where the information came from
- 04Sensitive documents that require access control, not open retrieval
What we can build.
Document ingestion
Processing pipelines that bring your documents into a searchable, structured form.
Retrieval systems
Search built to surface the right passages before the model generates a response.
Source-grounded assistants
Answers tied back to the documents they came from, rather than unverified generation.
Permissions & access control
Retrieval that respects who is allowed to see which documents.
How it connects.
Whatever we build connects to the systems already in place: APIs, databases, business software, cloud infrastructure or private infrastructure.
Depending on your constraints, systems can run in the cloud, in a private cloud, or fully on-premise.
How we work.
The same five-stage approach, applied to this type of engagement.
Understand
Design
Build
Deploy
Improve
Tell us what you're trying to build.
Send a short description of the problem and the systems involved. We'll reply with next steps, not a sales deck.