One workspace. Every team.
The same agents, approvals and audit trail, set up for the work your team does. Pick your team and see how JuhJuh works for you.
One standard on every change. Every cost on the record.
JuhJuh writes your engineering standard down once and applies it to every ticket, whether a person or an agent does the work and whichever model it runs on. Every AI call is costed to the token, and every change passes five safety gates before production.
One written standard
Templates by ticket type, rules that cascade through five levels, the brand voice and the design system reach every run. Engineering practices lock when the spec is approved, so nobody drops them halfway through.
5 rule levels on every runCosted to the token
Every reply and every run is priced to the token and attributed to the channel and the agent. Insights shows AI cost next to throughput, cycle time and run success rate.
Cost per run, per agent, per channelFive safety gates
Each ticket gets its own isolated branch, and main is untouched until a person merges. After every step, JuhJuh checks the code inside a running copy of your services that mirrors production, then runs your tests and fixes what fails, before your pipeline and code review see it. A second agent on a different model reviews each change, and a person decides every merge.
5 safety gates before productionAn audit trail of every action
Every run records which agent and model did each stage and what it cost. Every state change is logged with who made it and why. Reviewing quality means reading one rule set, not forty people's habits.
Who, which model, what it costPermissions and regions
Permissions have four levels. An agent can only do what the person behind it is allowed to do, and guests get no agent powers. Declared regions decide which models may run at all. Start on our hosted service, and self-host in your own cloud account or premises, connected or air-gapped, when your rules call for it.
Hosted, or inside your boundarySwitch models, keep the bar
Pin Claude, GPT, Gemini, Mistral, DeepSeek, GLM or Kimi per agent, always on the latest models. Changing models doesn't change the standard, and failover never moves you to a pricier model.
7 model families, one standardYou pull card statements, estimate usage per developer and build a spreadsheet nobody trusts.
Every reply and run is already priced to the token and attributed to its channel and agent. Insights shows AI cost next to throughput and cycle time. The CFO gets numbers from the source, not an estimate.
You explain that people use AI tools in their editors and code goes through normal review. You can't show which changes an AI wrote.
You show the record: which agent and model did each stage, the second-model review, who merged it, whether the pipeline passed and what it cost. Every state change is logged with who made it and why.
Same standard. Every change. Whoever wrote it.
Five safety gates, costs to the token, and an audit trail of every action.
On our service, or inside your own boundary.
Most teams start on JuhJuh's hosted service. There is nothing to install, your teams are working within days, and we run, update and support it. A team that needs more control, or must keep sensitive data inside, self-hosts JuhJuh instead.
Hosted by JuhJuh
Sign in and connect your tools. We keep the service running, updated and supported, so your people spend their time on their own work.
Your organization gets a workspace of its own, and each organization sees only its own data. When an AI agent works, the prompts and files it needs go only to the AI model companies you allow, only to do the work, inside the regions you declare.
Self-hosted, inside your boundary
In your own cloud account (AWS, Google Cloud, Microsoft Azure or DigitalOcean) or on your own premises, connected or air-gapped, with open-weight models from the Mistral, DeepSeek, GLM and Kimi families running inside. Our engineers install it and tune it to your compliance obligations.
Your sensitive information, trade secrets and know-how never leave your boundary unless you connect an outside service or chat app, approve a website for your AI agents or approve sending them out. While your AI agents run only on your own models, no AI company receives them or trains a model on them.
Start hosted and move when you're ready: our engineers move your workspace across. Some companies run both, the hosted service for most teams and a self-hosted installation for the systems that must stay inside, and each installation is kept separate.
Go deeper into the platform.
All features
Chat, agents, Plan & Work, Views, Charms, the knowledge base and voice, in one workspace.
OpenSecurity
Approvals before anything consequential, four permission levels, and an audit trail of every agent action.
OpenAI agents
Colleagues that remember every person they work with and work within a budget they can't overspend.
OpenSame standard. Every change. Whoever wrote it.
Five safety gates, costs to the token, and an audit trail of every action.
