About Cinchapi

Cinchapi is on a mission to give meaning to the world’s data.

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About Cinchapi

Atlanta Startup Battle champion Cinchapi (pronounced “syn-chap-ee”) is transforming how data scientists, analysts, and developers explore and work with data. The Cinchapi Data Platform (CDP) and its Ask, See, and Act workflow was purpose-built to simplify data preparation, exploration, and development. Its natural language interface combined with machine learning and a visualization engine make working with data conversational, efficient, and intuitive. Imposing no schema requirements, the CDP streams, comprehends, and stores definitive data generated in real-time by IoT devices as well as conventional, legacy, and proprietary databases.

Our Story

Cinchapi was founded in 2016 by Jeff Nelson, after previously working at companies like Palantir, MailChimp and Ionic Security and also co-founding Blavity.

After personally experiencing and witnessing other developers struggle with legacy tools ill-prepared for high velocity data, Jeff started the open source Concourse Database project to tackle those challenges and engage a broader community in shaping the future of real-time data management.

Cinchapi Inc. is the continued manifestation of a vision to deliver computing without complexity by giving developers better tools to make better software for the masses. We produce the Cinchapi Data Platform, made up of Concourse, Impromptu and Sponge. Our technology pushes boundaries in machine learning, natural language processing and distributed systems.

From our home base in Atlanta, GA, we help thousands of users interact with data in brand new ways.

The Cinchapi Data Platform

The Cinchapi Data Platform (CDP) combines machine learning with human intelligence to make working with data more efficient and intuitive. By imposing no schema of its own, the CDP was purpose-built to work with any high-velocity or static data source. This makes it ideal for data analysts and scientists looking for real-time data analytics and insights derived from disparate or decentralized data sources.