Osmos

Osmos provides an AI-powered data engineering platform that automates the cleaning, transformation, and ingestion of data without requiring coding expertise. The company was founded in 2019 by Kirat Pandya and Naresh Venkat, who previously worked together at Google Cloud on the Machine Learning team. Their experience helping a wide range of organizations with data challenges led them to recognize the growing need for better cross-company data collaboration.

The company's core offerings include the AI Data Wrangler and AI Data Engineer. The AI Data Wrangler is an agentic AI designed to autonomously clean, normalize, and ingest both structured and unstructured data, such as PDFs, Excel sheets, and messy CSVs. The AI Data Engineer functions like a mid-level data engineer, independently creating, testing, and iterating on Spark notebooks for more complex data engineering tasks. Both solutions are designed to replace manual data wrangling and brittle ETL (Extract, Transform, Load) processes with scalable and testable autonomous data engineering. Osmos has partnered with Microsoft, making its AI Data Wrangler available on the Microsoft Fabric platform, which enhances scalability and collaboration for enterprise-level operations.

Osmos operates on a business-to-business model, serving clients across various industries, including those in highly regulated sectors like healthcare and finance. Its revenue model is usage-based, charging clients per record processed through its pipelines and uploaders, with tiered discounts for higher data volumes. In July 2021, Osmos announced it had raised $13 million in a Series A funding round led by Lightspeed Venture Partners, with participation from CRV, Pear, and SV Angel.

Keywords: data engineering, AI data agents, data transformation, data ingestion, data cleaning, autonomous AI, no-code data platform, ETL automation, data wrangling, Microsoft Fabric, structured data, unstructured data, data pipelines, data normalization, AI-powered automation, enterprise data management, big data, SaaS, machine learning, data collaboration