Scenario: Secure Intelligence over a Large Technical Archive

How we would approach an organization that wants AI answers from hundreds of thousands of internal documents without exposing them.

Illustrative scenario. It describes how CCTI would approach this type of problem; it is not a report of a past engagement.

The situation

An industrial company holds manuals, patents and sensor logs it cannot send to external AI services. Simple retrieval tools give fragmented answers; long-context models are costly and hard to control.

How we would approach it

Stage 1 (Opportunity & Concept): define the questions that actually matter to engineers and the cost of a wrong answer. Stage 3 (Feasibility & Validation): build a small hybrid RAG-RLM pipeline on private infrastructure and measure it against a set of questions with known answers, before any scale-up.

What the client would receive: an architecture decision backed by measured accuracy, cost and data-boundary checks — or the evidence that the approach is not worth it for their case.