AI transformation that made it into production.
Production AI now supports multiple business operations across our portfolio. The evidence below separates verified system facts from transparent savings models, so decision-makers can see both the operational result and the assumptions behind each financial estimate.
What changed, what controls it and what we can prove.
These systems operate across multiple businesses in our portfolio. System facts are verified; financial figures below are transparent planning models until a client baseline and post-launch analytics establish measured ROI.
A grounded chatbot deployed for real business use
The production assistant searches 27 approved website documents, sends only the top three matches to the model and refuses unsupported claims. It has passed live grounded-answer and out-of-scope refusal tests, while credentials stay server-side and human contact remains available.
A command centre for nine websites
Health, security, publishing, SEO and scheduled-work evidence is normalised into one read-only dashboard. Red states stay red until the source evidence passes; visibility does not grant production authority.
A guarded content production pipeline
A script-first preflight binds one approved brief to one site. Research and writing remain judgement-led; deterministic postflight owns quality gates, import, public verification, receipts and cadence.
What routine-question automation can be worth.
Illustrative, not claimed client savings: 250 routine enquiries per month at six staff minutes each equals 25 hours released monthly. At a fully loaded £18 per hour, that is £450 per month or £5,400 per year. Replace the enquiry volume, handling time and labour cost with your measured baseline during the pilot.
Faster service without pretending every question is simple.
The assistant handles immediate knowledge retrieval, not every customer decision. Complex, sensitive or unsupported questions still move to a person.
Immediate first response
Customers can receive a grounded answer at any hour instead of waiting for the shared inbox to reopen.
Less repeated handling
Common product, service and policy questions stop consuming the same staff time again and again.
More consistent answers
Responses come from the same approved knowledge set, with refusal and human handoff when evidence is insufficient.
A measurable operating loop
Question volume, resolution, escalation and failure categories can be reviewed to improve both the assistant and the underlying content.
See the internal RAG AI knowledge-assistant model.
Explore how the same grounded retrieval pattern can reduce internal search time, interruptions and duplicated work while keeping company knowledge permissioned.
Bring us the bottleneck. We will map the safest useful next step.
Tell us what repeats, where it gets stuck and which systems are involved. We will reply within four UK working hours with the questions needed to scope a practical pilot.
Recent Comments