AI Solutions
This is an internal prototype, not commissioned client work. It illustrates our approach; it does not report client outcomes.
Support teams answer the same questions repeatedly, while the answers already exist in help articles and policy documents that customers rarely find.
Help articles are split into passages, embedded and stored in a vector index. For each question, the most relevant passages are retrieved and given to the language model with strict instructions to answer only from them and cite the article. Questions outside the content, or about refunds and account changes, are routed to a person with the conversation attached.
Cleaned and structured the help content, removing outdated articles before indexing.
Built chunking, embedding and retrieval with source references attached to every passage.
Added topic boundaries, refusal behavior and escalation rules for sensitive requests.
Created a test set of real-style questions to measure answer quality and correct escalation before any changes ship.
An internal prototype that classifies incoming property enquiries, asks follow-up questions, and routes qualified leads to the right agent.
An internal prototype that extracts supplier, totals and line items from PDF invoices into structured data for review.
Next step
Tell us about your situation and we'll share how we'd approach it.