Synthetic Data for CRM
A CRM dataset is a pipeline: accounts hold contacts, contacts drive deals, deals move through stages. Misata generates all of it with the stage lifecycle modeled as a state machine, so deal progression looks like a real funnel rather than random labels, and every foreign key resolves.
The tables Misata generates
accountsCompanies with industry, size, owner, and deal-value roll-upscontactsPeople tied to accounts, job titles, coherent emailsdealsPipeline stage lifecycle, amount, close date after create dateactivitiesCalls and emails referencing real contacts and dealsWhat holds true, every time
- Deal stages follow a realistic funnel, not uniform random labels
- An account's total pipeline equals the sum of its deals
- Close dates never precede create dates
- Every contact and activity references a real parent record
Frequently asked
Do I need real CRM data to generate this?
No. Misata builds the dataset from a specification, not a sample. There is no real CRM data to source, anonymize, or leak. You describe the tables you need and the engine constructs them with referential integrity and realistic distributions.
Is the generated CRM data privacy safe?
Yes, by construction. Nothing is learned from real records, so there is no membership to infer and nothing to leak. It runs entirely on your machine with no API key for the core engine.
Can I control the outcomes, like rates and totals?
Yes. Declare a target such as a monthly volume curve or an event rate and Misata produces rows that hit it exactly, while foreign keys stay intact and roll-up columns reconcile after a JOIN.
Choosing a tool? How Misata compares