Sperta is building a risk-decision platform with a rules engine at its core that targets analysts and data scientists at fintechs and financial institutions. Its differentiator is an expression language with SQL-like syntax to make complex rule authoring accessible to users familiar with SQL. The platform includes rule unit tests, backtesting, percentage rollouts, integrations with data vendors, feature transformation, and a case management tool for decisions that require human review. Customers can bring their own models and Sperta provides an interface to integrate those models with its decisioning UI. The founders, Yifu Diao and Ming Fang, drew on experience building Uber’s Mastermind rules engine and Google Cloud AI Feature Store while designing the product. Sperta says it will price below competitors’ average of about $1 per decision. The company is still developing the product and hopes to ship an MVP by year’s end.

Total raised

$3M

Funding rounds

1

Latest round

Seed

Latest activity

Dec 2021