Every merge approved. Every release traceable. Every incident on record. All inside your company's own boundary.
Your engineering teams ship faster without loosening a single control. AI agents plan, code, test, release and watch production, and every step lands in a record your risk, compliance and audit teams can read.
For IT, OT, engineering, security and operations teams at electricity, gas and water network operators, generators and suppliers, in the UK, the EU and North America.
Where the hours and the risk go.
Speed of AI, with the controls your regulators expect.
AI inside the boundary
Open-weight models run in your cloud or data centre, so code, prompts and network details stay put. Run a connected installation for IT and an air-gapped one inside your operational network for OT.
One record from ticket to release
The ticket, acceptance criteria, code review, approvals, build, image digest and release are linked. Anyone can follow a production change back to the request.
Incident timelines for tight clocks
Your incident manager starts from a timeline already written, for the one-hour NERC CIP-008 report, the 24-hour NIS2 early warning and the 72-hour UK NIS notification.
Approved library copies
Builds use mirrored copies of the open-source packages you approve, inside your boundary. Adding a new library or source stays with a person.
Evidence packs on request
The compliance evidence AI agent assembles the record for a control, a period or a release, for NERC CIP, NIS2, the CAF and IEC 62443, and a person signs it off.
Beside your control systems, not inside
Your teams plan, build, review, release and watch the software around your control systems. AI agents reach only the systems you connect, through the routes your zone rules allow.
Issue cards, not noise
Logs, metrics and traces become one card per problem that names the likely cause, beside the release behind it and its rollback plan.
A second review on another model
A reviewer AI agent on a different model checks every change against its acceptance criteria. A person decides the merge.
The same week, with JuhJuh.
Alerts arrive from separate tools, the on-call engineer pieces together what changed, and the timeline is written afterwards from memory.
The SRE on-call AI agent opens the incident, finds the release that caused it and alerts the on-call engineer. One tap approves the rollback, and the service is healthy by 2:31am.
They rebuild the night from chat, phone notes and spreadsheets while the reporting clock runs.
They read the timeline in the incident channel, decide it doesn't need reporting, and the decision is recorded with their names.
Someone spends days pulling tickets, approvals and release notes from three tools.
The compliance evidence AI agent assembles the record, and the head of engineering signs it off the same afternoon.
Every role gets time back.
A person approves anything consequential.
What your AI agents never do on their own
- Merge a change, or approve their own work. A different AI agent on a different model reviews it, and a person decides.
- Deploy to production or roll back without a person's approval.
- Change production settings, access or secrets. They prepare the facts for the person who decides.
- Reach a system you haven't connected, such as a control system.
- Add a library, an image source or an outside service to your approved list.
- Decide whether to report an incident to a regulator. That stays with your incident manager.
Self-hosted, with separate IT and OT installations
JuhJuh runs as your own installation in your own cloud account or your own data centre, including inside your operational network. Run a connected installation for your IT teams and an air-gapped one for OT engineering, each with its own data, AI models and record.
Open-weight models from the Mistral, DeepSeek, GLM and Kimi families run inside. When your AI agents run only on your own models, your network topology, control system configurations and customers' data never leave the boundary unless you connect or approve it. Air-gapped means no way out at all.
Bring AI inside your boundary.
Start with one or two teams, and add the rest when you're ready. That's the juju.
