HEAVY.AI
HEAVY.AI is a revolutionary GPU-accelerated analytics platform that enables enterprises and public sector organizations to make time-sensitive, high-impact decisions using big data. By leveraging advanced geospatial and time series analytics, HEAVY.AI allows users to query massive datasets hundreds of times faster than traditional systems, providing instant insights and dynamic visualizations. The platform is designed for industries such as telecommunications, energy, and utilities, and is backed by prominent venture capital firms, positioning it as a leader in the analytics space.
HEAVY.AI
HEAVY.AI is a revolutionary GPU-accelerated analytics platform that enables enterprises and public sector organizations to make time-sensitive, high-impact decisions using big data. By leveraging advanced geospatial and time series analytics, HEAVY.AI allows users to query massive datasets hundreds of times faster than traditional systems, providing instant insights and dynamic visualizations. The platform is designed for industries such as telecommunications, energy, and utilities, and is backed by prominent venture capital firms, positioning it as a leader in the analytics space.
TL;DR
What they do: GPU-accelerated analytics platform for very large, time-and-location-centric datasets
Flagship tech: HeavyDB — open-source GPU SQL engine with native geospatial support
Industry focus: Telecommunications, energy, government/public sector, utilities
Founded by: Todd Mostak and Thomas (Tom) Graham
Funding: Raised ~ $91.6M across five rounds (most recent disclosed: Series C, Oct 3, 2018)
Company Overview
Problem Domain
Fast querying and visualization of massive geospatial and time-series datasets for industries needing rapid, location-aware insights.
Industry
Analytics / Geospatial / Big Data
Tech Stack
Funding Track Record
Most recent disclosed round (Oct 3, 2018) according to company profiles.
Investor Signal
“Backed by GV (Google Ventures), In-Q-Tel, NEA, NVIDIA, Tiger Global Management, Vanedge Capital, and Verizon Ventures”