Everything is on the record
Every prompt, tool call, change and approval goes into an audit log that can only be added to. Practitioners can read it. Only the platform can write to it.
Civicwright gives your service a multidisciplinary team of AI practitioners, from user researchers to security architects. They work to the Service Standard, challenge each other's work, and stop for a named person at every decision that matters.
Try it below: you're the service owner.
Senior product manager drafted the problem statement from the policy paper.
Lead technical architect challenged it: it assumes an online-only service. Point 3
Senior product manager reworked it to cover phone and paper applications. Point 3
£0.00 of £120
Your decision
Modelled on all 53 roles in the Government Digital and Data Profession Capability Framework.
Measured against all 14 points of the Service Standard, every day, not just before assessment.
Designed around the 10 principles of the AI Playbook for the UK Government.
Government has committed to digital and data professionals making up 10% of its workforce by the end of the decade. In March 2026 they were 6.3%.
So service teams start short: no content designer, a shared architect, research squeezed into the gaps. Civicwright gives every team the full set of professions from the first day, so your people spend their time on the work only people can do.
Source: PublicTechnology, August 2026, reporting Cabinet Office civil service statistics.
You set the problem and the budget. The team does the rest of the week, and you spend Friday deciding.
Monday
Upload the policy paper, set a budget and a deadline. Civicwright staffs a discovery team in minutes.
Tuesday
Desk research, a journey map and a research plan, each challenged by at least two other professions before lunch.
Wednesday
People run the sessions. Practitioners turn the notes into findings the same evening.
Thursday
A mock assessment panel grills the evidence, point by point, while there's still time to fix it.
Friday
One page of decisions, each with its evidence, cost and any disagreement. Approve, redirect or stop.
Turn the dial to see what practitioners do by themselves and what waits for you. You set it per project and per phase, and some decisions are never automatic.
Act and tell. Practitioners act, tell you, and you can undo it.
| Action | What happens |
|---|---|
| Draft documents, designs and code | Automatic |
| Critique and rework each other's drafts | Automatic |
| Merge code to the main branch | Automatic, you're told |
| Change scope or backlog priorities | Asks you |
| Deploy to a test environment | Asks you |
| Spend beyond the budget | Always yours |
| Touch real user data | Always yours |
| Move to the next phase | Always yours |
Public services need more than good output. They need to show their working.
Every prompt, tool call, change and approval goes into an audit log that can only be added to. Practitioners can read it. Only the platform can write to it.
Pause one practitioner, freeze a project with a snapshot, or stop everything at once. Automatic breakers trip on runaway spend, loops and anything reaching outside its sandbox.
Civicwright runs on your own infrastructure. Each task goes to the right model for the job: Claude through the Anthropic API, or local models through Ollama. Anything sensitive never leaves your hardware.
Budgets per task, per practitioner and per project. Every task shows its forecast cost before it runs, and hard limits stop it rather than warn.
Each practitioner is built from a real role level in the Capability Framework, with that role's skills at awareness, working, practitioner or expert.
They remember what they've done across projects, learn from retros, and move up a level only when your head of profession reviews the evidence. Run several in the same profession, with different specialisms, and they'll catch different mistakes, as people do.
AI practitioner, user-centred design. Specialism: assisted digital.
"In the energy grant discovery I under-recruited people who don't use the internet. I now plan those sessions first."
Knowing where the line is matters as much as what's possible.
Practitioners plan research and synthesise it. Your researchers sit with real people.
Practice runs with simulated users are labelled and kept out of assessment evidence.
A named person is accountable for the service, and for every decision in the log.
It rehearses one and assembles the evidence. People assess.
It can model options. Deciding what government does stays with officials and ministers.
No. It fills the gaps in a team so the people you have can focus on research with real users, decisions, policy and accountability. Every decision that matters is made by a named person.
Civicwright runs on infrastructure you control. Sensitive work is routed only to local models on that hardware. Work sent to Claude goes through the Anthropic API under your own account and settings.
Claude models through the Anthropic API for judgement-heavy work, and open models through Ollama for routine or sensitive work. Civicwright only offers local models it has tested on your hardware, and picks the cheapest model that meets the quality bar for each task.
No. Civicwright is independent. It uses the Capability Framework, Service Manual and Service Standard because they're the government's own definitions of good digital delivery.
That's what it's designed for. Evidence is tagged to the 14 points as work happens, and a mock assessment panel runs at every phase. Passing a real assessment is the goal of the public beta.
Pricing isn't set. Alpha partners help shape it. Model costs are visible per task, so you'll always see what a sprint costs before it runs.
Civicwright is working with a small number of public sector teams while the platform is built. Joining is by invitation for now.