Find information in your business documents
Manuals, contracts, and procedures may be scattered across multiple repositories. Retrieval-augmented generation combines relevant passages from those sources with a language model to help answer questions about the material.
Allogic assesses and builds these systems around available sources, access permissions, and business quality criteria. RAG does not eliminate model errors; answers need evaluation before and during operation.
What the project must address
- Document sources and update routines.
- Access controls aligned with user permissions.
- Information retrieval and references to consulted documents.
- Handling questions without sufficient supporting evidence.
- A set of representative questions and expected answers for evaluation.
- Privacy, providers, and hosting and API running costs.
When it is useful
RAG is an option when the team needs information from a document base and can define how to verify an answer. Traditional search or a system integration may work better for exact queries against structured data.
How we start
An AI assessment identifies sources, users, restrictions, and the questions the system must answer. Model and infrastructure choices follow that assessment and may involve third-party services under their own licences.
Investment depends on integrations, volume, privacy, and operational support. The introductory call establishes context without requiring confidential documents.