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Government

Every merge approved. Every release traceable. Every incident on record. All inside your department's own boundary.

Your digital teams deliver public services faster without loosening a single control. AI agents do the routine work of planning, coding, testing, releasing and watching your live systems, and every step lands in a record your security, information risk and audit teams can read.

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For digital, engineering, platform, security and information risk teams in central government departments, agencies, devolved administrations and local government, in the UK, the US and the EU.

Why it slips today

Where the hours and the risk go.

38%
Of incidents hit public administration
In ENISA's 2025 threat landscape, public administration was the most targeted sector, with 38% of the incidents it analysed.
228
Legacy systems reported by UK departments
In January 2025 the National Audit Office reported at least 228 legacy systems, 28% of them rated red for risk.
282
Generative AI uses at 11 US agencies
The GAO found in 2025 that generative AI uses rose about ninefold in a year, from 32 to 282.
Engineers use AI tools on their laptops that nobody approved, and code and citizen data go to outside AI services.
Changes are approved in one tool, built in another and deployed from a third.
Evidence is gathered by hand before every audit and assurance review.
Incidents are worked across chat, phone and spreadsheets while the reporting clock runs.
Use cases

Public services, shipped inside your boundary.

One installation per classification

OFFICIAL work, including OFFICIAL-SENSITIVE, runs in one installation. Work at SECRET and above gets its own air-gapped installation, so it never crosses a boundary inside the software.

Citizen records and unannounced policy kept inside

Citizen records, policy work before it is announced and ministerial advice stay in projects open only to the people who need them. When your AI agents run only on your own models, nothing leaves your boundary.

Evidence for GovAssure, CAF, Service Standard, FISMA

Access, change, monitoring and incident records are ready as evidence for GovAssure and the Cyber Assessment Framework, your service assessments and your FISMA authorisation. The compliance evidence AI agent assembles each pack, and a person signs it off.

AI agents prepare facts, never decide

Your AI agents prepare the facts for the caseworker who decides a citizen's case, claim or entitlement. They never make that decision, and connect to case systems only as your rules allow.

Legacy service work

Our engineers connect your case management and legacy systems through their APIs. Changes to old services then go through the same tickets, review and release as new ones.

Shared government platforms

In a connected installation, your services reach GOV.UK Notify, GOV.UK Pay, GOV.UK One Login or Login.gov through their APIs, with the same review and release as every other change.

Incidents with the timeline already written

AI connects logs, metrics and traces into one issue card per problem, beside the release that caused it. Your incident manager starts the CISA or NIS2 reporting clock from the facts.

Every merge decided by a person

A reviewer AI agent on a different AI model checks every change against its acceptance criteria. A person decides the merge, and an AI agent never approves its own work.

Before and after

The same week, with JuhJuh.

SituationAt 2:10am the online claims service starts failing, two days before a payment date.
Before

Alerts arrive from separate monitoring tools, and the incident is worked across chat, phone and spreadsheets before anyone finds the release behind it.

After

The SRE on-call AI agent opens the incident, finds the release that caused it and sends the on-call engineer a voice note. She approves the rollback with one tap, and the service is healthy by 2:31am.

SituationA policy lead files a change to the claims eligibility rules that hasn't been announced yet.
Before

Engineers reach for AI tools on their laptops, and unannounced policy leaves the department's control.

After

The ticket sits in a project open only to the people working on it, and every AI agent on it runs on the department's own models. The spec AI agent writes the spec, and the service owner approves it.

SituationThe assurance lead asks for every change to the claims service last quarter, for the annual GovAssure review.
Before

Someone spends days gathering tickets, approvals and release notes by hand.

After

The compliance evidence AI agent assembles the record in #assurance, and the head of engineering signs it off.

Who it is for

Every role gets time back.

Chief digital and information officerFaster delivery across every team, with one standard and one record.
Chief information security officerAI kept inside your boundary unless your rules allow a public model, access through your own sign-in and a record of every action.
Senior information risk ownerEvery AI model, access change and release on record, with evidence ready for your assurance reviews.
Authorising officialThe records your assessors draw on, ready for your system's authorisation to operate.
Service ownersServices for the public delivered in smaller, safer releases, with your service standard written into every change.
Data protection officerCitizen records kept in your installation unless you choose to let them out, access by role and a record of who did what.
Head of engineeringEvery change built to the same standard, whoever or whatever wrote it.
Software engineersTickets turned into reviewed, tested changes, with your time spent on design and judgement.
Internal audit and assuranceChange, incident and access evidence ready when you ask for it.
Control and where it runs

A person approves anything consequential.

What your AI agents never do on their own

  • Make a decision about a citizen's case, claim or entitlement. The caseworker decides.
  • Merge a change or approve their own work. A different AI agent reviews it, and a person decides.
  • Deploy to production or roll back without a person's approval.
  • Decide whether to report an incident to a national cyber security authority or a data protection regulator.
  • Sign off evidence for an assessor, an auditor or an authorising official.
  • Use an AI model your rules haven't approved, or send anything outside the organisation beyond approved answers.

Self-hosted, one installation per classification

JuhJuh runs as your department's own installation. OFFICIAL work can run in a connected installation in your own cloud account, and work at SECRET and above gets its own air-gapped installation with no connection to the public internet, on your own models only.

Open-weight models from the Mistral, DeepSeek, GLM and Kimi families run inside your boundary, and public model families such as Claude, GPT and Gemini are added only where your rules allow. Nothing leaves unless you connect an outside service, approve a website or approve sending it out. Our engineers install it with you, with access only as your vetting or clearance rules allow.

Bring AI into your department.

Start with one or two teams, inside your own boundary, with every decision kept with your people. That's the juju.

Talk to us See how it works

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