What we build
RAG pipelines
Ingestion, chunking, embedding, hybrid retrieval and reranking over your documents, catalogs and databases.
Knowledge backoffice
A workspace where your team edits, uploads, reindexes and curates knowledge without developer intervention.
Permissioned access
Retrieval scoped to users, roles, organizations and business units across multitenant deployments.
Evaluation & observability
Regression suites, citation checks and quality/cost metrics run on every prompt, model or data change.
How we keep answers grounded
- Hybrid retrieval: vector search plus keyword and structured filters
- Citations attached to every generated answer
- Automatic reindexing of documents, transcripts and operational data
- Guardrails that prevent off-topic or out-of-permission retrieval
- Evaluation harnesses over real business cases
Evidence in production
Frequently asked questions
What is enterprise RAG?
Retrieval-augmented generation grounds a large language model in your own knowledge. Instead of answering from memory, the model retrieves relevant documents and data, then answers with citations to the sources it used.
How do you keep company knowledge up to date?
We build pipelines that reindex your documents and operational data automatically, and an operational backoffice that lets your team edit, upload and refresh knowledge without a developer.
How are permissions enforced?
Retrieval respects your organization's access rules and multitenant boundaries, so each user or business unit only sees the knowledge it is allowed to see.
How do you reduce hallucinations?
Through citations, hybrid retrieval (vector + keyword + filters), reranking, and evaluation suites that check answer quality against real business cases on every change.
Can it run on AWS and Amazon Bedrock?
Yes. Develo engineers on AWS and uses Amazon Bedrock knowledge bases and models so data controls and guardrails stay inside your cloud tenancy.
Related
Ground your AI in your own knowledge
Tell us what your people search for every day. We'll map the sources, permissions and a RAG architecture that answers from your data.
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