Irison knows your product, your process, and who does what. It picks up each piece of work, takes it through every step from spec to production, and brings the right person in at the right moment — in the tools they already use.
Set up in an afternoon · Free while in beta
Maya — the spec for HVAC export is approved and ready for architecture.
I put the spec, the constraints and the open questions in Confluence for you. Nothing else is waiting on you today.
What Irison does
Not a dashboard you check. A teammate that carries the work from one person to the next.
On day one Irison connects to your tickets and your code, reads them, and tells you what it found. Your product, your stack, your conventions, how your team actually works. You just confirm or correct it.
By the time setup ends, it already speaks your product's language — so nothing you say later has to start from scratch.
Irison maps your real process onto nine steps, from spec to running in production. It always knows which step a piece of work is on, who owns that step, and what has to happen next.
No one on your team? That step is marked skipped, not quietly faked.
Most teams now have five AI assistants that have never met. Each one only knows what the person in front of it typed. Irison is one teammate with one memory — so when work moves from the PO to the Architect to the Developer, everything decided earlier moves with it.
There is no second agent to hand over to. That is why nothing drops.
Irison comes to them. The Architect gets a Slack message and writes the design in Confluence. The Developer gets a branch in GitHub with everything already in it. The PO answers in Slack. Only the person who runs the team signs in to the Portal.
No new habit to teach. No tool to get people to adopt. That is why it survives the first sprint.
Ravi — IRI-142 is ready to build.
I created the branch iri-142-hvac-export and put the spec, the architecture and the acceptance criteria in it. Open it in Claude Code and everything is already there.
Irison drafts, gathers and carries. It never writes your code, never runs your tests, never deploys. At the end of every step the person who owns that step reads the result and either approves it or sends it back — and the work does not move until they do.
That is how you get AI speed without AI guesses reaching production.
One screen shows how long work sits at each step, how often it gets sent back, and whether your delivery is speeding up. The delivery numbers come from Jira and GitHub — your own tools — not from counting Irison's own activity.
A focused proof surface, not a wall of charts. It is the answer you need at sprint review.
One teammate, six jobs
The same teammate, showing up differently depending on whose step it is.
Sees the whole board, and whether delivery is getting faster.
Turns an idea into a written spec and ready stories, from chat.
Pulled in only when it is their turn, with the spec already read.
Gets a branch with the full context already in it.
Tests against the original acceptance criteria, not a guess.
Knows what is ready to go out and what is still blocked.
Why this is needed
Individual developers really did speed up. Teams did not. Three things break it — and they all come from every person running their own AI, their own way.
Change in team delivery speed after AI adoption.
Faros AI 2026 · 22,000 devs
Only 17% say AI made the team work together better — its lowest-rated effect.
Stack Overflow 2025
Each step's output is written for a human to read. The next person has to turn it back into something their own AI can use — and detail is lost every time.
Everyone keeps the work in their own place. The team never shares one clear, current picture of what is being built.
Each one works alone. It does not know how the rest of the team works, what the others are doing, or where its own job fits.
Where it fits
| Kind of tool | What it does | What you are left with |
|---|---|---|
| Engineering analyticsJellyfish · LinearB · Swarmia | Measures what already happened and shows you where work stalls. | A chart. You still have to work out what to change. |
| AI coding toolsCopilot · Cursor · Claude Code | Makes one developer much faster inside their own editor. | No idea of the team, the product, or what happens next. |
| Project toolsJira · Linear | Tracks the state of the work as people update it by hand. | A board. It does not move the work or carry the context. |
| Irison | One teammate that knows your product and your team, carries each piece of work through every step, and brings the right person in at the right moment. | Work that keeps moving — with an expert approving every step. |
Connect Jira, GitHub and Slack. Irison reads your product, maps your process, and takes the next story all the way through. You will see the first clean handoff the same week.