Services/RAG & knowledge systems
Capability
RAG & knowledge systems
Grounded answers from your documents, with citations and access control.
Supporting depth for Private Knowledge AI: ingestion, retrieval, permissions, evaluation, and abstention when confidence is low.
What we build
The engineering pieces included under this capability.
Ingestion
Chunking, metadata, and sync from docs, wikis, tickets, and databases.
Retrieval
Hybrid search, reranking, and filters tuned to your corpus.
Citations
Answers tied to sources teams can open and verify.
Permissions
Respect existing roles so answers stay inside data boundaries.
Evaluation
Groundedness checks, regression suites, and abstain policies.
Example use cases
Concrete jobs this capability is built for. Not a full project proposal.
01
Internal knowledge Q&A
Employees ask policy or process questions in plain language and get answers with links to the source documents.
02
Support agent assist
Support staff get grounded steps from product docs and past tickets, instead of searching ten tools by hand.
03
Contract & document search
Find clauses, obligations, or terms across a document set, only showing results the user is allowed to see.
Build path
- 01
Source map
What data, who can see it, and what “good answer” means.
- 02
Retrieval build
Index, rank, cite, and wire into the app or workflow.
- 03
Eval loop
Measure groundedness, fix failures, then harden for production.
Typical stack
Retrieval
Orchestration
Models
Need this in production?
Bring the use case and constraints. We will say if a sprint or pilot fits.