Ask Your Data Questions In Plain Language
Conversational analytics lets any team member type a question the way they would ask a colleague and get a governed answer back — a number, a table, or a chart — without writing SQL or waiting on the data team.
Required To Ask
To First Answer
Every Response
Why Conversational Analytics Matters
Most organisations do not have a shortage of data. They have a shortage of people allowed to touch it. A question that takes thirty seconds to ask takes three days to answer because it has to travel through a ticket, a queue, an analyst, and a review. By the time the number comes back, the meeting that needed it has already happened and the decision was made on instinct.
Conversational analytics removes that queue without removing the controls that made it necessary. Questions are answered against the same governed models your analysts curate, so definitions of revenue, churn or on-time delivery stay consistent no matter who asks. Every answer shows the fields and filters it used, which means a result can be challenged and checked rather than simply believed.
In practice this changes who participates in analysis. Operations managers investigate their own anomalies. Finance tests a hypothesis before escalating it. Analysts stop producing one-off extracts and spend their time on the modelling work that only they can do. The measurable outcome is not just faster answers — it is a larger number of questions being asked at all.
What You Get
The capabilities behind conversational analytics in Mimasa AI.
Natural Language Questions
Ask "Which regions missed target last quarter?" and Mimasa AI resolves the tables, joins and filters behind the scenes.
Follow-Up Context
Each answer keeps context, so you can narrow by region, change the period or switch the metric without restating the question.
Answers As Charts Or Tables
Mimasa AI picks the clearest representation for the question and lets you pin any answer straight to a dashboard.
Governed By Design
Questions run against governed datasets and respect the same access rules as the rest of the platform.
How It Works
From connected data to a working outcome, in four steps.
Connect Your Data
Point Mimasa AI at your databases, warehouses or uploaded files.
Ask A Question
Type the question in plain language — no schema knowledge needed.
Review The Answer
See the result with the underlying data so you can verify it.
Pin Or Share
Save the answer to a dashboard or share it with your team.
Why It Matters
No Analyst Queue
Business teams answer their own questions instead of filing a ticket and waiting days.
One Version Of The Truth
Everyone queries the same governed datasets, so two teams never argue over two numbers.
Analysts Freed Up
Routine pulls disappear from the backlog and analysts spend their time on real modelling work.
Where Teams Use It
Making Self-Service Analysis Safe To Trust
The biggest objection to letting non-analysts query data directly has always been trust: if anyone can ask anything, how do you stop two people from getting two different answers to the same question? Conversational analytics in Mimasa AI answers this by never letting a question bypass the governed model underneath it. The natural language layer translates a question into a query against the same tables, joins and metric definitions your analysts already maintain, so the flexibility of asking freely never comes at the cost of consistency. A finance director and a regional manager typing the same question get the same number, because both requests resolve against one shared definition of revenue rather than two private interpretations of it.
Trust also depends on being able to see the working, not just the result. Every answer Mimasa AI returns carries the fields, filters and time period it used, displayed alongside the number or chart itself. That transparency turns a conversational answer from something you either believe or dispute into something you can actually check, which is exactly the habit good analysts already have and the one self-service tools usually strip away. Because the underlying rows remain reachable, a surprising answer prompts a quick look at the data rather than a debate about whether the tool is broken.
Over time this changes the shape of who does analysis inside a company. Instead of a small team of analysts fielding requests from everyone else, questions get asked and answered where they arise — in a sales review, during a finance close, in the middle of an operational escalation. Analysts are not replaced by this; they are freed from repetitive extraction work to spend their time building the governed models that make every one of those conversations reliable in the first place.
Common Questions
Do users need to know SQL?
No. Questions are typed in plain language and Mimasa AI translates them into governed queries against your connected data.
How do I know the answer is right?
Every answer shows the data it was built from, so you can inspect the rows and the filters that produced the number.
Can answers become dashboards?
Yes. Any answer can be pinned to a dashboard and refreshed on a schedule.