Slai builds a developer-first platform that lets teams ship machine-learning applications without assembling their own infrastructure. The product connects data sources (databases or S3 buckets), runs user-provided Python models to produce predictions, and exposes that logic via an API. The platform handles input validation, output processing, versioning, and model monitoring so developers can focus on data and models rather than glue work. Slai positions itself as a GitHub-like experience for ML, including the ability to fork existing machine-learning recipes. CEO and co-founder Eli Mernit says the company’s goal is to empower developers to build state-of-the-art machine-learning models more easily. The company recently raised a seed round to support its product development and growth.

Total raised

$4M

Funding rounds

1

Latest round

Seed

Latest activity

May 2022