Services
Enterprise Search & Knowledge
Unlock institutional knowledge with secure, source-grounded retrieval across your organization.
The business challenge
Critical knowledge is scattered across documents, systems, and inboxes. Employees struggle to find accurate, current answers – and generic AI tools can invent them.
A general-purpose assistant pointed at company data will answer confidently whether or not the answer is supported. For an organization, the failure is worse than an unanswered question: a plausible, well-written, wrong answer is difficult to detect and easy to act on.
There is a second problem underneath it. Most knowledge stores contain contradictory material – superseded policies, drafts that were never deleted, decisions later reversed. Retrieval that ignores recency and permission will surface all of it with equal confidence.
What Golden Tefnut provides
We build retrieval that is grounded in your own sources, respects who is allowed to see what, and shows its working.
- Enterprise knowledge retrieval using retrieval-augmented generation (RAG).
- Secure search with document ingestion and permission-aware access.
- Source-grounded answers with citations.
- Auditability and monitoring.
How We Work
A practical sequence
How the engagement runs
The first phase is unglamorous and decisive: establishing which sources are authoritative. A retrieval system inherits the quality of what it indexes, so the inventory stage is where most of the eventual accuracy is determined – well before any model is involved.
Answers carry citations back to the source document. This is not an interface nicety. It is the mechanism that lets someone verify an answer in seconds rather than trusting it, and it is what makes the system usable for decisions that carry weight.
Permission-aware retrieval is enforced at query time against your existing access rules. A user asking a question sees only what that user could already open directly, which means the search layer does not become an accidental way around your access controls.
Expected Outcomes
Business results that matter
Faster, more accurate answers
Source-grounded responses employees can trust
Knowledge access that scales with the organization
Frequently Asked Questions
Common questions
How is this different from the AI search built into our existing tools?
Scope and grounding. Built-in search generally covers one product's own content; this retrieves across the sources you designate as authoritative, cites them, and enforces your permissions at query time.
Can employees use it to see documents they should not have access to?
No. Permissions are enforced during retrieval, so results are filtered to what that specific user is already entitled to open.
What happens when two documents contradict each other?
The system surfaces the conflict and cites both, rather than picking one. Resolving which is authoritative is a knowledge-ownership decision, not one the retrieval layer should make.
Does our data go to a third-party model provider?
That is an explicit architectural decision made with you during design, driven by your data-handling requirements, and documented as part of the governance review.
Let’s Build
Ready to Transform Your Business With AI?
Let’s identify the highest-value AI opportunities in your organization and build a practical path from strategy to execution.
Or email us at [email protected]