In-product assistant
Gini Assistant: ask your workspace, inside your permissions
How it works, and what constrains it
No second login
The assistant runs behind the same session as the rest of the product. There is no separate credential and no separate access decision.
Your permissions, checked before any work
Each tool call verifies the caller's permission before touching the database, and the underlying service authorises again on its own.
Most questions never reach a model
A pattern-matching router sends direct lookups (your projects, your tasks, what is overdue) and aggregations (how many, what percentage, which project has most) straight to the database. One query, no model call.
A fixed set of approved capabilities
The assistant works through a defined set of actions agreed at startup — read your projects, search your tasks, add a comment, update an issue. Identity always comes from your session, never from the question.
Destructive actions are confirmed first
Anything destructive comes back as a signed confirmation covering the action, its arguments, the user, the company and an expiry — so a change happens because someone chose it, not because a question was phrased a certain way.
Writes are audited
Every non-read tool call is recorded, including the ones that failed.
Nothing sensitive in the logs
The assistant's metrics and audit records deliberately exclude question text, tool arguments, answers, and any user or tenant identifier.
Chat History for oversight
Questions asked of the assistant are available as their own permissioned report, so a company that wants visibility of how it is used simply grants it.
Inside the product, not bolted onto it
The assistant reaches the same services, with the same company scoping and the same authorisation, that every screen uses. That is what makes it safe to give to a whole team: an answer can only ever contain what the person asking was already entitled to see.
It is also built to be careful rather than quick. When a question calls for judgement, it takes the considered path rather than guessing from a pattern — because a confident wrong answer costs more than a slower right one.
- Runs in the session the person is already signed in to
- Permission checked before any work is done, and again by the service underneath
- Every action recorded, and destructive ones confirmed first
The questions teams ask it
Most of the day-to-day ones are direct: what is assigned to me, which tasks are overdue, what is the status of a project, when is the next milestone. Those are answered straight from your own data in a single query.
So are the counting questions — how many open bugs, what percentage of this sprint is done, which project has the most reopened issues. And when someone needs judgement rather than a number, compare, summarise and prioritise are there too.
In-product assistant: common questions
Can the assistant see data I am not allowed to see?
Can it change or delete things on its own?
Do questions about my tasks leave the workspace?
Can we see what people are asking?
Related
Security at Matrix
The controls the assistant inherits
Roles and permissions
The catalogue the assistant checks against
Questions to ask before adding an AI assistant
A checklist for evaluating any assistant in a business tool
Or go back to all features.
Try it against your own work
A workspace takes a couple of minutes to create. Put one real project in it and see whether this shape matches how your team already works.