Generative AIIllustrative concept
A copilot for the knowledge you already have
An internal knowledge assistant that connects answers to their sources and keeps access boundaries intact.
A support-drafting concept that prepares grounded replies while preserving an agent's final decision.
Illustrative project concept. This describes a proposed approach, not a completed client engagement or measured outcome.
Generative AI
Customer experience
Evaluation / Python / React / Retrieval
Support teams need useful draft responses that follow approved guidance and do not reveal more customer information than the task requires.
A draft-only assistant that retrieves approved knowledge, protects selected customer fields, and presents the source material for agent review.
Illustrative project concept. No live support platform or customer account is connected.
The proposed first release helps an agent prepare a response to a narrow class of support requests. The assistant has no ability to send a reply, issue a refund, or change an account.
Approved knowledge enters the context with source references. Customer details are reduced to the minimum needed for the task, and a reviewer sees the draft before any external action.
Testing covers misleading customer messages, outdated policies, missing evidence, and accidental reuse of information from another conversation.
A pilot would compare reviewed drafts with the existing workflow and inspect the edits that agents make. Those edits help identify missing context and recurring failure patterns.
The first step is to map the user journey, understand the available data, and decide what the smallest useful version should prove. The evaluation plan should cover both task quality and the consequences of a wrong answer.
The interface, application logic, and data access remain separate, making permissions easier to reason about and each part easier to evaluate. The precise infrastructure would be selected during discovery.
For this concept, the design review would address data minimization, source permissions, sensitive-data exposure, output review, and retention. Specific controls and their effectiveness must be verified before any real deployment.
Concept outcome: an evaluation set for policy consistency, factual support, unnecessary data exposure, and agent edit effort.
These are design goals. A real engagement would establish a baseline and measure results during testing and a controlled pilot.
An internal knowledge assistant that connects answers to their sources and keeps access boundaries intact.
A guided workflow for turning sensitive business context into a useful, protected prompt.