Data pipeline
Source connectors, cleaning, chunking, metadata and controlled index refresh.
02 / RAG SYSTEMSAnswers grounded in enterprise knowledge
Answers grounded in enterprise knowledge
with verifiable sources.
We build RAG systems that find relevant passages in internal documents, enforce access rights and show the supporting sources with every answer.
01 / WHEN IT FITSUse cases that need
Use cases that need
an engineering approach
- 01
Employees spend too much time searching documents
- 02
Answers must link to primary sources
- 03
Documents change regularly and have different access levels
- 04
Several enterprise systems need one search point
02 / DELIVERABLESWhat is included
What is included
in the outcome
Retrieval
Full-text, vector and hybrid search with reranking.
Access control
Role-aware filtering before context reaches the model.
Evaluation
Reference questions, retrieval and answer metrics, error logs and regression tests.
03 / PROCESSFrom a hypothesis
From a hypothesis
to a verifiable system
- 01
Inventory
Identify sources, formats, owners, update frequency and access rules.
- 02
Reference set
Collect real questions and verified sources with domain experts.
- 03
Retrieval prototype
Test chunking, embeddings, retrieval and reranking strategies.
- 04
Answer generation
Configure citations, refusal behavior and safety rules.
- 05
Integration
Connect the UI, identity, monitoring and knowledge refresh process.
04 / QUESTIONS
The essentials
Does RAG eliminate hallucinations?
It reduces risk and makes answers verifiable, but does not guarantee accuracy. Citations, confidence thresholds and regular evaluation remain necessary.
How quickly do new documents appear?
Refresh can be event-driven or scheduled, depending on the business requirement.
Can existing access rights be preserved?
Yes. Permissions must be enforced during retrieval so neither the user nor the model receives unavailable passages.
05 / START A PROJECTStart with the task,
Start with the task,
data and outcome
In the first meeting we will review the use case, constraints and a realistic path to a measurable prototype.
Discuss a project ↗