Faster delivery for engineering and operations technology teams under aviation regulators.
Your engineering and operations technology teams ship faster without loosening a single control. AI agents do the routine work of planning, coding, testing, releasing and watching production, and every step lands in a record your safety, compliance monitoring and audit teams can read.
For engineering, operations technology, security, safety and compliance teams at airlines, airports, maintenance organisations and aerospace suppliers, in the UK, the EU and the US.
Where the hours and the risk go.
The routine engineering work, done inside your boundary.
The airborne software trace, kept current
A design assurance AI agent keeps the trace from each requirement to its code, reviews and tests up to date on every change, ready for your DO-178C process. Every assurance decision and sign-off stays with the people your process names.
Part-IS and NIS incident reporting
Each incident gets a timeline, the evidence and the people on call as it happens, so your incident manager starts the 72-hour report from the facts. Whether to report stays with your people.
Crew tracking and maintenance record services
Alerts on the services behind crew, maintenance and the airport land in the channel that owns them, and the SRE on-call AI agent opens the incident and finds the release behind it. A person approves any rollback.
Airworthiness security reviews
The security review AI agent checks every change for risky patterns, secrets and access changes before a person decides the merge, and keeps a record of each security-relevant change for your DO-326A process.
Evidence for CAA and EASA oversight
Change, incident and access evidence is ready for your compliance monitoring programme and your authority's audits. The compliance evidence AI agent assembles each pack for a person to sign off.
Every change reviewed on another model
A reviewer AI agent on a different AI model checks every change against its acceptance criteria, and a person decides the merge. No AI agent ever approves its own work.
Builds from your approved libraries
Builds use mirrored copies of the open-source packages you approve, inside your boundary, and the dependency AI agent prepares each update as a change for review.
One issue card per problem
AI connects uptime, logs, metrics and traces into one card that names the likely cause beside your release history, so engineers start from an explanation rather than a wall of alerts.
The same week, with JuhJuh.
The on-call engineer works the incident across chat, phone and separate monitoring tools, and the timeline is written up afterwards.
The SRE on-call AI agent opens the incident, finds the release that caused it and sends her a voice note. She approves the rollback with one tap, and the service is healthy by 2:31am, before the first departures.
Engineers gather approvals, builds and release notes by hand from three different tools.
The compliance evidence AI agent assembles the record from the linked ticket, review, approval, build and release, and the head of engineering signs it off.
The trace from requirements to code and tests is rebuilt by hand before the review.
Requirements, code, reviews, tests and builds were linked as the work happened, and the people your design assurance process names make every decision.
Every role gets time back.
A person approves anything consequential.
What your AI agents never do on their own
- Merge a change, deploy to production or roll back. A person decides.
- Approve their own work. A different AI agent on a different model reviews it, and a person approves.
- Make a design assurance decision or sign off a verification or configuration record for airborne software.
- Change production settings, access or secrets, or add a library to your approved list.
- Decide whether to report an incident or an occurrence to an authority. Your incident manager or safety manager decides.
- Sign off evidence for an auditor or an authority.
Self-hosted, connected or air-gapped
JuhJuh runs as your own installation, in your own cloud account or your own data centre, connected or fully air-gapped. Open-weight models from the Mistral, DeepSeek, GLM and Kimi families run inside it, and public model families such as Claude, GPT and Gemini are added only where your rules allow.
When your AI agents run only on your own models, passenger data, flight operations and maintenance records, aircraft and avionics designs and security plans never leave your boundary unless you connect an outside service or approve sending them out. Our engineers install it with you and configure it to the controls your authority and your design assurance process need.
Bring AI into your engineering teams, inside your boundary.
Start with one or two teams, then add the rest when you are ready. That's the juju.
