It works in your tools, on your cloud, by your rules.
Engineers, a product manager, a reviewer and a QA agent. Each one does only its job.
Your task board, your repository, your cloud, your models. Nobody installs anything.
Set the rules once, hand it tickets, get results back in the ticket.
Agents in the roles you defined, each on its own machine, choreographed by a playbook with a gate at every handoff.
Every step leaves a comment in the ticket: what it did and why.
Agentic solutions that come with Kadmo and add value from day one. New ones keep arriving.
Takes a ticket, works on its own machine and branch, opens a pull request and fixes what review sends back.
Playbook · Feature implementation
Turns a goal into an epic, splits it into tickets sized for one agent each, and checks the result against the intent.
Playbook · Goal to tickets
Runs your test suite on the live environment after every change or release and files what breaks as tickets.
Playbook · Release check
Runs every night over dependencies, secrets, configuration and new code. The work nobody wants to do by hand.
Playbook · Nightly scan
Reads what shipped, updates your docs and drafts the customer update, so documentation never falls behind the code.
Playbook · Docs and customer update
Reads your codebase and past runs and writes down what every other agent needs to know, so the next run starts smarter.
Playbook · Skill discovery
Builds and updates pages from a brief: layout, copy and components, published to your site once you approve.
Playbook · Page from a brief
Why a fleet beats a single assistant that takes a whole ticket alone.
engineering output, quality kept
the fleet keeps working after your team logs off
accepted without rework, first pass
engineers’ output from one product manager
A frontend agent is better at frontend work than any generalist.
Every window stays small and sharp; no agent holds a whole ticket.
Nothing moves on before its gate passes.
What one run learns, every following run loads.
Every agent writes what it did and why into the ticket.
A better model ships, you switch.
Teams running a Kadmo fleet, in production.
club management software
less developer time per ticket after two weeks
“We have already been using AI in our engineering team, but with Kadmo we brought speed to a new level.”
Marc ZwieblerCEO, Kurabu
Your tools, your cloud, your models, your gateway.
Each agent gets its own machine and scoped credentials.
Outbound traffic is allowlisted per agent.
Every run keeps its full transcript, replayable any time.
What an admin needs to let agents work and stay in control: set once, kept on every run. Included in Business and Enterprise.
An agent works as its role, on its own machine, with that role’s tools and credentials and no others.
Gates and approval policies for playbooks and for new agents. A step that needs approval waits.
Spend limits per account and per workspace, in euros, against what every run really costs.
Every model shows its region, and a policy keeps a workspace to the regions you allow.
The full transcript of every run, replayable any time, and the audit log to export.
Single sign-on with SAML; with SCIM, your team’s accounts follow your directory.
Custom agentic solutions for your stack and your process, built with you.
Sales, customer service, back office, purchasing and internal knowledge are on the Custom services page.
Frontend. Design-system migrations and component work, one pull request at a time. See the use case
Backend. API versions, dependency upgrades and the test backfill nobody has time for. See the use case
QA and test. A regression pass on every release, reported in the ticket. See the use case
DevOps. Pipelines, runners and infrastructure changes, each behind a review. See the use case
Data. Schema migrations and pipeline checks that run before anyone asks. See the use case
Documentation. Docs that follow the code, updated with every merge. See the use case
Security. Dependency and secret scans every night, with the fix as a pull request. See the use case
Compliance. Evidence collected as the work happens, ready when the auditor asks. See the use case
A repository, a task board and one thing from your backlog. Kadmo works inside the tools you already use — Jira or Linear, GitHub or GitLab — so there is nothing to replace and nothing to migrate. We set the fleet up with you, and it is live within days.
On your cloud. Every agent has its own machine and its own scoped credentials, outbound traffic is allowlisted per agent, and model calls go through your own gateway. Your code never leaves your perimeter: no personal AI accounts, GDPR ready, hosted where you choose.
Claude Code and Codex today, on models from Anthropic, OpenAI and Google — direct, through Bedrock, or behind your own gateway. There is no lock in: when a better model ships, you switch.
You will know, to the cent. Every run reports its real token spend in the ticket, in one place, so a shipped ticket has a price. The models run on your own accounts, at your own rates.
Live within days. Try it on one thing from your backlog, see the result, then decide.