Works with Claude, ChatGPT and other AI assistants

Your AI delivery team, under your control.

Your AI does the work. Your people check it.

Gunnie.ai refines, estimates, builds, reviews and releases your tickets with AI. Your team checks and approves. Every step stays within your rules, and on record.

In daily use today: 69 tickets built end to end in 27 days.

CALL LOG · acmetoday
14:02:11 · [email protected] · reader312ms
search_productsallowed
Magento · "office chair" · 12 products
14:03:40 · [email protected] · developer1.4s
pr_review_contextallowed
Bitbucket · shop #482 · 6 files
14:05:02 · [email protected] · reader4ms
read_filedenied
Bitbucket · shop/app/etc/env.php
rule role reader › read_file: not allowed
3 calls · 2 allowed · 1 deniedall recorded
Connects toMagentoAkeneoJiraLinearBitbucketGitHubGitLabFigmaSlack
69
tickets built end to end
242
tickets pre-refined
184
tickets estimated
187
pull requests reviewed
84,307
lines of code written

Results of the routines Gunnie.ai is built from, in daily use on a live production project and on Gunnie.ai itself. Every line reviewed by a person. Updated hourly.

The delivery pipeline

Every step a ticket takes. AI does it, people check it.

Your team stops doing the groundwork and spends its time on the decisions. Most steps already run in Gunnie.ai as routines and open to beta companies first, each one only once it is at least as good as the routine it comes from.

01Built, in the beta

Pre-refinement

Reads every new ticket against the code and earlier work, and proposes a note with open questions, risks and a first approach. It is added to the ticket once you approve it.

PeopleYour product owner answers the questions.
02Built, in the beta

Team estimate

Proposes story points on your own scale, with its reasoning as a comment, before the refinement meeting. Nothing is set until you approve it.

PeopleThe team agrees or adjusts.
03Built, in the beta

Autonomous development

Picks up ready tickets, builds them on a branch with tests, runs your quality checks and opens a pull request. Hands a ticket back when it needs a person.

PeopleDevelopers review and merge.
04Available now

Code review

Reviews every pull request against its ticket and acceptance criteria, in two passes, with your own rules on top.

PeopleThe author fixes, a reviewer approves.
05Built, in the beta

QA pre-check

Opens the pages a ticket touches on your test environment, checks the acceptance criteria it can see, with screenshots, and proposes a comment before a tester looks at it.

PeopleTesters do the final check.
06Built, in the beta

Release notes

Writes the notes for every released version from its tickets, in plain language, and sends them to your stakeholders.

PeopleYou decide who receives them.
Routines

Work that runs on its own, and waits for your yes before it writes.

A routine is a piece of the pipeline that Gunnie.ai runs for you: it starts by itself, does the reading and the thinking, and hands you the result. Anything it wants to change in your systems comes to you first, exactly as it would be written.

01Starts by itself

On a schedule or an event

On weekday mornings, on every new or updated pull request, or when a ticket enters a status you pick, such as Refinement. You can also start a run by hand to try it out.

You seeWhen it runs, for which projects and repositories, and how many tickets per run.
02Approval first

Proposes, never just writes

A routine turns its work into proposals: the exact note, estimate or comment, on the exact ticket. You approve or reject each one; a proposal waits up to seven days. Only an approved proposal is written.

You seeEvery proposal word for word, on the Approvals page and with the run that made it.
03Within budget

Costs you can see

Every routine has its own monthly budget and a limit per run. You see an estimate before a run starts and the cost after it finishes.

You seeThe result of every run, its cost, and every call it made in the call log.
How it works

Routines run on their own. Skills decide how. People decide what ships.

Not one more chat window your team has to remember. Routines do the groundwork themselves, every step passes the gate, and every step is written down.

01

Connect your systems, set the limits

Shop, product data, tickets, code and designs. Allow-lists and roles decide what is in reach, for people and routines alike.

02

Switch on the routines

They start themselves, on a schedule or when a ticket or pull request changes, on Gunnie's own server. Nobody has to remember to ask.

03

Trusted skills, your rules on top

Gunnie's proven skills, your organisation's rules and your repository's standards. Every run records the versions it used.

04

People approve, everything is recorded

Results land in your tickets, pull requests and Slack. People decide what ships, and every call is in the log.

The skills

What makes the routines good enough to trust.

A model on its own is a capable newcomer. What makes a routine dependable is knowing how good work is done here: what to check, what counts as proof, when to stop and ask a person. Gunnie.ai writes that knowledge down as skills, built and refined over months of routines doing this work every day for a real development team. Whatever a skill knows, every step it takes stays within your rules and on record.

Your repository's standards
AGENTS.md, .ai/, linter configs
narrowest, wins
Your organisation's rules
Skills page in the control panel
Gunnie's base skills
Built and refined over months of daily use
the base
One routine run
CollectProve or dropReport
Within your rules, and on record
01Every report

Proof before a finding

A routine reports only what it has shown to be true: the broken path is reached by real callers, the rule is quoted from where it is written. What it cannot prove becomes a question.

You seeEach finding with its proof, and what was not checked.
02Every ticket

Measured against what was asked

Work is checked against the ticket and its acceptance criteria, one criterion at a time. A criterion that is not met is never waved through, however good the rest looks.

You seeEvery criterion marked met, not met or unclear.
03Every routine

Knowing when to stop

A routine that is unsure does not guess. It hands the work back to a person with the exact question, and the next step waits for the answer.

You seeA ticket handed back with one clear question.
04Every run

Your rules on top

Three layers: the base, your organisation's rules and the standards in your own repositories. The narrowest one wins, and a rule that is not written down is never cited.

You seeYour rules in the control panel, with their history.
05Every skill

Proven before it replaces anything

A skill takes over a step only when it finds at least what the routine it replaces found. Every run records the skill versions it used.

You seeThe skill versions behind every result.
06Every version

Sharper with every miss

Each false alarm and each missed issue from daily use goes back into the skills. That loop, run for months on real tickets and pull requests, is what makes the output reliable.

You seeA miss you report turns into the next version.
Available now · What your team asks

Plain questions, answered from the live systems.

No exports, no copy-pasting between tabs. Each answer comes straight from the system that owns the data, within the reach of the person asking.

Sales and support

“How many ergonomic office chairs do we have in stock, and at what price?”

search_productsMagento
Product data

“How complete is SKU 40211 for the web shop channel?”

pim_productAkeneo
Product owners

“Give me the whole story behind ABC-123: comments, links and the code so far.”

ticket_contextJira + Bitbucket
Anyone with the right role

“Create a ticket for the broken price filter on the category page.”

create_ticketJira
Developers

“Review pull request 482 in shop against the ticket.”

start_code_reviewBitbucket + Jira
Developers

“Which spacing and colours does the checkout frame use?”

design_contextFigma
Central code review

One review standard for the whole team.

Start a review from your assistant today, or, in the beta, let it run on every pull request. Gunnie.ai runs it on its own server with trusted skills: a proven base, your organisation's rules on top and the standards in your repository. It reads the pull request, the ticket and its acceptance criteria, checks its findings in a second pass, and reports back to whoever asked.

Security

Built to be trusted with your systems.

Giving an AI access to your shop, tickets and code is only sensible when you control the reach and can see every step. That is what Gunnie.ai is for.

A gate, not a copy

Gunnie.ai reads your systems live when someone asks. It keeps no copy of your products, tickets or code.

Least privilege

Roles decide the tools, allow-lists decide the reach. Anything outside them is denied and logged.

Questions stay private

The call log records who, what and when. Never the question, the arguments or the answer.

Tokens locked away

Connection tokens are encrypted with AES-256-GCM on arrival and are never shown again, not even to admins.

Organisations kept apart

Row-level security in the database separates every organisation, on every query.

Hosted in the EU

On a dedicated server in a European data centre, not on shared cloud infrastructure.

Read the security overview
Questions

Frequently asked questions

What is Gunnie.ai, in plain words?

An AI delivery team that works inside the systems you already use. Today it reviews code and answers questions from your web shop, product data, tickets and code; in the beta it also prepares, estimates and builds tickets. Your people check and approve the work. Gunnie.ai decides what the AI may reach and writes down every step.

What problem does it solve?

Developers lose a large part of their week to groundwork: reading tickets, collecting context, estimating, reviewing, writing release notes. AI can do much of that, but most companies hesitate to give it access to their shop, tickets and code, because nobody can see what it touches. Gunnie.ai does the groundwork and keeps the AI inside your rules, so your team spends its time on decisions.

Who is it for?

Companies with a development team, in house or hired, that work from tickets and pull requests. Developers get the reviews and the groundwork; product owners, support and sales can ask plain questions about products, orders and tickets without needing a developer.

How quickly can we start?

Asking questions and starting code reviews works as soon as your systems are connected. An admin connects each system once with an access token, and every member adds one address to their AI assistant. The routines that run on their own, such as pre-refinement and estimates, start in the beta: we set them up with you and tune the skills to how your team works.

Do we have to change our tools or the way we work?

No. Gunnie.ai works with your Jira or Linear, Confluence, Bitbucket, GitHub or GitLab, Magento, Akeneo and Figma as they are, and the routines follow your process, your definition of done and the standards in your repositories.

Which AI assistants does it work with?

Claude, ChatGPT and other assistants that support MCP, the open standard for connectors. Your team keeps the assistant it already uses.

Does it work with Slack?

It will, with the beta. Install the Gunnie.ai Slack app and pick a channel: the routines report there, so your team sees what the AI did without opening another tool. Answer in the thread, with a reply or a ✅, and the AI gets to work within the reach of the person who replied. The app comes to the Slack Marketplace later.

Will it replace our developers?

No. It takes the groundwork off their plate. People still decide what gets built, approve every change and decide what ships.

Can the AI change things in our systems?

Only what you allow. Each role gets its own tools, and allow-lists limit which projects, repositories and files are within reach. Most tools only read. Anything that changes something, like creating a ticket or a note a routine wants to add, waits until it is approved in Gunnie.ai, whatever AI assistant was used. Files that hold secrets, such as .env files and keys, are never read. The code review never posts on a pull request by itself.

Is our data safe?

Gunnie.ai reads your systems live and keeps no copy of your products, tickets or code; only a routine’s result and a change waiting for approval are kept, for 30 days. The call log records who did what and when, never the question or the answer. Files that hold secrets are never read. Access tokens are stored encrypted, the server runs in a European data centre, and nothing is used to train AI models.

Which AI runs the code review and the routines?

Claude, through Gunnie’s own account, in the EU. Usage is counted per organisation, within a monthly budget you set, and under Anthropic’s commercial terms your data is not used to train models.

What does it cost?

During the beta we agree the price with each participating company. Code reviews and routine runs show their cost one by one, within a monthly budget you set yourself, and every routine has a budget of its own.

Ship more with the team you have.

Join the beta. Tell us which systems you run and how your team works; we set up Gunnie.ai with you.

Join the betaLog in