Retrieve. Ground. Cite
Privy AI is the engine behind Blue Mesh's Enterprise RAG capability. Ask a question and it retrieves the passages that answer it from your indexed data, grounds the reply in what it retrieved, and names the source in the answer: retrieval-augmented generation, low-hallucination and citation-backed. All of it runs in your environment, under access controls you already govern.
An answer you can check beats an answer you must trust
Grounded, cited answers change how a team treats what the machine says. Not because the model got smarter, but because every reply carries its own receipt.
Verification in one step
Every reply names the passage it stands on. A reader who doubts the answer opens the source and settles it there.
- 01.01Source named in the reply
- 01.02Doubt settled at the document
Current when your documents are
The answer comes from the index, not weights fixed at training time. When a policy changes, reindexing changes the next answer. Nothing is retrained.
- 02.01Answers track the corpus
- 02.02No retraining when facts move
A miss you can trace
Grounding constrains the reply to what was retrieved. When an answer still misses, the citation shows what it stood on, so the fix is a document edit.
- 03.01Constrained to retrieved passages
- 03.02Failures point at their source
Retrieval answers from what is written down
That is its power and its limit, and both belong on this page.
The index is the ceiling
Privy cannot answer what nobody wrote down, and a wrong document produces a well-cited wrong answer. The citation is what keeps that failure honest: it shows which source the reply stood on, so you fix the source rather than argue with the output.
Fine-tune for behavior instead
Tone, structure, and the vocabulary of your organization are things retrieval cannot teach a model. That is training work, and BM Oasis is built for it.
Bring the content you already own
Point Privy at the knowledge bases, policies, and records your organization already trusts, and keep them governed the way they are today: role-based access, encryption, and an audit trail on every decision.
It runs where your data lives
Indexing, retrieval, and generation run inside the boundary you deploy into: private cloud, on-premises, air-gapped. What you index stays under the controls it already lives under.
- Governance Civic AI, which that page says runs on this stack: natural language search across decades of legislative and policy archives.
- Policy compliance Internal policies read against standards like GDPR and ISO, with the sections that do not line up flagged for correction.
- Electronic health records The same retrieval shape inside a hospital: a patient's own record gathered into a discharge summary draft a physician finalizes.
- BM Oasis The other half of the choice: fine-tuning on your own data, and a plain account of when training beats retrieval.
Bring a question your team answers from documents
In one session we will index a slice of your own content and put real questions to it, live. You will see what was retrieved, what the answer stood on, and the source named in every reply.