Data, designed.
Not just generated.
Draw the tables, or just describe them. Declare the outcome the data has to hit, revenue climbing then dipping in Q3, an 18% churn rate, zero orphan rows, and Misata builds a real, connected world to match it exactly, from customer demos and test environments to analytics and AI workflows. Not sampled and hoped for. Designed on purpose.
Prefer the library? pip install misata. MIT licensed, runs locally.
The parameterized synthetic
data generation suite.
One core, built outward in three directions at once: open for anyone who wants to read it, no-code for anyone who wants to skip straight to designing, and an agent for the moment an AI-built pipeline needs a demo that actually earns the room.
The engine
The parameterized core. MIT licensed, pip install misata, and readable end to end, so trusting it never requires taking our word for it.
Misata Studio
The design surface. Draw the tables, describe them in a sentence, or start from a template, all running the same engine in your browser.
Misata Backlot
The agent. Describe a data world in plain English, declare what has to be true about it, and it builds, verifies, and lands the result, demo environments first, with more workflows to follow.
Most tools generate rows.
Misata designs a world.
A row-by-row generator fills columns with no idea what the neighbouring column says. Misata designs the whole thing at once, the schema, the relationships, the numbers you declared, so it holds together wherever someone clicks into it. One engine, aimed at whatever you’re building right now.
You can copy production and hope it survives the trip. You can fake it by hand and hope nobody looks too closely. Or you can design it, on purpose, and get exactly the data you meant to build.
A sentence is the fast way in,
not the only way in.
However you think about your data, Studio meets you there. Type it, draw it, import a schema you already have, or begin from a template. Every dataset shapes, corrects, and exports the same way from any starting point.
Designed freely.
Held together exactly.
The canvas is the part you feel. Underneath it is a deterministic engine: whatever story you designed, the numbers it produces actually match, every foreign key resolves, and a proof ships with the result, so the freedom to design it your way never costs you data that falls apart on the first join.
| order | customer | placed | amount |
|---|---|---|---|
| 10441 | Amara Okafor | 2025-10-04 | 612.40 |
| 10442 | Jonas Lindqvist | 2025-10-04 | 89.99 |
| 10443 | Priya Raghunathan | 2025-10-05 | 1,204.75 |
| 10444 | Tomás Herrera | 2025-10-06 | 247.10 |
| 10445 | Wei Zhang | 2025-10-06 | 58.25 |
| 10446 | Fatima Al-Sayed | 2025-10-07 | 430.00 |
Need it built for you?
We will build it.
Describe your schema, constraints, and deadlines. We will produce a custom relational dataset with integrity proofs, realistic distributions, and the exact aggregate targets you need, and deliver it to your inbox.
Bespoke datasets start at $50, quoted before any work begins.
Everything you need to know about
relational synthetic data.
Common questions about generating synthetic data, referential integrity, database formats, and compliance.
Declare it. Shape it.
Ship it with proof.
Studio is in public beta. Describe what you need, shape it, correct it, and export it. If something is missing for your use case, tell us and we will build toward it.
There is no support queue. Just me.
Misata is built by one person, so anything you send is read by the person who can actually change it. Ask how to model something awkward, tell me what data shape you keep wishing existed, or point at the thing that broke.
Requests that come with a real use case tend to get built first, because they are the ones I can verify I got right.