RAG & Knowledge Assistants
Your policies, contracts, tickets, and wikis hold the answers your teams need, but finding them wastes hours every week. A retrieval-augmented generation assistant reads your own content and answers questions in plain language, with citations back to the source. It stays current as your documents change and respects who is allowed to see what.
Grounded answers with citations
Rather than relying on a model's memory, we retrieve the most relevant passages from your content and use them to compose an answer that links back to the exact source. This keeps responses grounded in your material, makes them verifiable, and dramatically reduces the confident-but-wrong answers that erode trust in AI tools.
Ingestion, indexing, and freshness
We build pipelines that ingest documents, PDFs, tickets, and database records, split and embed them, and store them in a vector index that updates as content changes. Metadata such as source, date, and department is preserved so answers can be filtered and attributed. Stale content is refreshed automatically so the assistant reflects reality, not last quarter.
Access control and governance
The assistant enforces your permissions so a user only sees answers drawn from documents they are entitled to. We log questions and sources for auditability, add guardrails for sensitive topics, and give you controls to exclude or correct content. This makes the tool safe to roll out across departments rather than a leak waiting to happen.
What You Get
- Document ingestion and embedding pipeline
- Vector search index with metadata
- Cited, grounded answer generation
- Permission-aware access control
- Freshness and re-indexing automation
- Usage and source audit logging
Why Teams Choose Turn Global
- Answers cite their sources for trust
- Respects existing document permissions
- Stays current as your content changes
- Cuts time wasted searching for answers
Ready to Start?
Contact our team and we will send the best implementation plan for your business.