Advanced RAG Solutions
Retrieval systems that connect language models to your documents, databases, and domain knowledge with traceable sources and access controls.
What is included
What this work covers
Each engagement is scoped to the problem at hand, so the shape of the work varies. These are the parts that are always accounted for.
- Data ingestion and knowledge indexing
- Hybrid search and reranking
- Retrieval quality evaluation
- Guardrails and access controls
Fit
Who this is not for
Not a fit if you need a generic chatbot with no private data — a SaaS tool will be cheaper and faster.
Questions
What clients ask about this work
- What is a custom RAG solution?
- Retrieval-augmented generation, or RAG, lets a language model find relevant information in approved business sources before it answers. A custom system adapts ingestion, retrieval, permissions, citations, and evaluation to your data and workflow.
- How do you manage accuracy and access?
- We test retrieval and answer quality against representative questions, return source references where the product needs them, and apply the same access rules as the underlying data. Higher-risk workflows can include review and approval steps.
- What data do you need from us to start?
- Access to the sources people already trust, who may see what, and a set of representative questions. We scope ingestion, permissions, and evaluation from that, with no data migration upfront.
Other services
Where this connects
Most engagements touch more than one of these. The others are worth a look if this is close to your problem.
Generative AI Products
Task-focused assistants and workflow tools designed around the way your team already works.
AI Product Engineering
Product strategy, UX, architecture, and software delivery for AI-enabled products.
Contact
Bring us the problem, not a finished specification
Describe the workflow, the information involved, and where the current approach falls short. We will help define a practical first release.