Your development cycle with an AI team inside. Your people decide.
Your people set the task, accept the result and ship. The AI team does the work in between and has a second model check it.
The cycle
Three lanes, one task
- Idea and priority
- Task in the tracker
- Review
- Merge and release
- Requirements check
- Code in a branch
- Tests and PR
- Second model
- Instructions vN+1
Unclear tasks go back with questions. Rework after your reviewer counts as human cost.
- Run telemetry
- Testing new models
- Proposal to you
Faster at the same price, or more tasks for the same AI budget. The model only changes with your consent.
Where to start
One role or a whole team
A whole team on one stream
Bugs, product changes, tech debt. Every task goes from the backlog to a reviewed PR.
One role in your team
For example, only QA, or only a second-model review before your tech lead.
Developers keep their tools: Cursor, Claude Code, VS Code, Codex. Architecture and product decisions stay with people.
Your domain, your rules
AI follows your standards instead of working around them
We set it up with your experts while preparing the repository. We bring the method, your people bring the domain knowledge.
Your libraries first
Internal components from your artifact repository are used before anything new is written.
Your security rules
Authorization, GDPR and secure coding standards are part of the instructions at every step.
Rules for every stack
Java, .NET, frontend: versioned rules approved by your tech leads.
Isolated runs
Each task runs in a disposable environment with no access outside the repository.
Jira, YouTrack, MS Planner or any tracker with an API · GitHub, GitLab · your own AI agents via MCP. Per board column: process it or not, which model, which instruction version.
Where are you now?
Seven steps of AI in development
Every company goes through steps 1–3 on its own. We went through 4–6 on our own products, and KYFlow gives them to you from day one.
- 1Personal
People use AI on their own, without a company subscription
- 2Subscription
Company Claude Code, Codex or Cursor for developers
- 3Report
The effect shows per person, but it does not scale
- 4Orchestrator
Central control of development and quality
- 5Quality and cost
Every task done by AI is assessed
- 6Picking the best
Vendor, model and instructions chosen by data
- 7Estimate upfront
Cost of tasks and sprints before work starts
See your own numbers before any decision
We will use your task history to estimate how many tasks the AI team can take on and what that is worth per year.