AI and automation

Support assistant with retrieval controls

A retrieval-augmented support assistant that answers from approved content, cites sources, captures leads and hands off to a human when appropriate.

Context

A service business needed to reduce repetitive support handling while keeping answers aligned with approved content.

The assistant had to avoid unsupported answers, make source material traceable and route out-of-scope requests to a person.

Approved content, server-side credentials, logging and human handoff were required from the start.

A general chatbot would not meet the operational risk profile. Retrieval needed to be constrained to vetted sources.

The system includes document ingestion, embeddings, retrieval, a constrained answer layer, webhook-based lead capture and an admin review log.

Retrieval-augmented generation was selected so content updates could be reflected without retraining, with citations included in generated answers.

The backend handles ingestion, retrieval, answer construction, source citation, lead capture and conversation review.

Lead capture was connected to the team workflow so qualified requests arrived in existing channels.

Keys remain server-side, model scope is limited to approved material and logged conversations can be reviewed.

Out-of-scope and edge-case prompts were used to verify refusal, handoff and citation behaviour.

The assistant was launched behind the existing site with monitoring for answer quality and lead handling.

Routine questions are handled through approved content and qualified enquiries are routed to the team. Verified figures are available under NDA.

The value of an AI support feature depends on retrieval scope, citations, logging, review and handoff design.

Client names are withheld. Detailed references are available on request where confidentiality allows.

Need a similar system reviewed?