Describe a schema. Get realistic data. In one conversation.
An autonomous AI agent asks clarifying questions, plans, and generates relationally-consistent data into a live database — then iterates in chat, exports to any format, and writes matching documents.
- How many customers?
- Date range for invoices?
- Currency mix?
| customer | plan | mrr |
|---|---|---|
| Marlowe Diagnostics | Scale | $1,290 |
| Nordkapp Labs | Team | €480 |
| Brightfield Health | Enterprise | $4,200 |
One hot-swappable model layer. No lock-in.
From a sentence to a full dataset, conversationally
No fixtures to hand-write, no generator scripts to maintain. You talk to an agent; it plans and builds.
Describe
Paste a schema or describe it in plain language — tables, fields, and the relationships between them.
Clarify
The agent asks the questions a good engineer would — volumes, ranges, distributions — before it writes a single row.
Plan
It orders tables by dependency, resolves foreign keys, and picks realistic distributions for every column.
Generate
Rows stream into a live per-tenant database — watch the turns arrive over SSE as the agent works.
Iterate
"Add 200 churned accounts." "Skew invoices to Q4." Refine in conversation, with snapshot & revert on every turn.
Export
Export to any format — streamed in the background and emailed to you the moment it's ready, with matching documents.
An agent that understands your data model
Conversational data agent
Not a form and not a template. A real agent that plans, calls tools, validates its own output, and course-corrects — the way an engineer would.
Relationally consistent
Foreign keys resolve, cardinalities hold, and distributions look real. Data your app and your tests actually accept.
Multi-vendor model layer
One hot-swappable abstraction over Claude, OpenAI, OpenRouter and DeepSeek. No lock-in, deterministic in CI.
Live streaming turns
Watch the agent think, plan, and write in real time over SSE — optimistic UI, never a frozen spinner.
Any-format export
CSV, JSON, SQL, Parquet, SQLite. Streamed off the request path, emailed on completion, purged on a retention timer.
Matching unstructured documents
Generate invoices, clinical notes, or contracts that reference the exact rows in your structured data — so end-to-end tests have documents that actually line up.
Enterprise-grade, off the request path
01 · Isolated per tenant
Every user's data lives in its own database, sealed behind Fernet-encrypted keys. Cross-tenant reads return a clean 404 — never a leak.
02 · Durable by design
Generation and exports run on Celery workers, not the web request. They survive a redeploy, retry on failure, and email you when done.
03 · Reversible & audited
Every agent tool call is recorded in an append-only log, and each turn snapshots — so a one-click revert always takes you back.
Generate your first dataset in a conversation.
Describe a schema, answer a couple of questions, and export realistic data in minutes.