UK Water Utility

Zero non-compliant regulatory bulletins. 18 hours saved per week. 3,000+ communications a month, consistently on-brand, without asking a single employee to change how they work.

Energy & Cleantech

GovTech

Client
UK Water Utility
Expertise

AI Development

Full-Stack Engineering

Tech Stack

OpenAI

GCP

Python

Challenge

The problem wasn't the volume — it was the inconsistency. Different writers, different interpretations of compliance guidelines, different registers. In a regulated industry, that has consequences: regulatory risk, reputational exposure, and review cycles that slowed everything down.

Three things made it hard to fix:

  • No single tool could reach everyone. The comms team worked across email, internal portals, and document editors. A standalone web app would get ignored.
  • Generic AI writing tools were useless. A water utility regulator cares about specific phrasing. Off-the-shelf tools couldn't be trained on the organisation's own guidelines.
  • The compliance bar was zero-tolerance. Anything short of 100% compliant output wasn't good enough.

Solution

We built an AI writing co-pilot as a Chrome extension, deployable into any browser-based tool without an IT integration project. The model was trained on this organisation's own compliance guidelines, communication standards, and past approved communications.

The co-pilot does three things:

  • Suggests compliant drafts based on communication type and relevant guidelines
  • Scores existing drafts against the compliance ruleset in real-time
  • Flags deviations with specific guidance on what to change and why

No new portals. No workflow changes. The AI appears in the tools people already use.


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Results

MetricResult
Non-compliant communicationsDropped to zero during pilot
Weekly hours saved per team18
Monthly communications covered3,000+
DeploymentChrome extension — no IT integration required
TimelineDiscovery to live pilot in 8–10 weeks

Writers stopped second-guessing phrasing. Senior reviewers stopped catching the same categories of errors every week. The review cycle shortened because fewer things needed to go back.


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