Logical Clocks Raises Euro 1.25 Million To Launch Hopsworks, A Data Platform for AI

PC: Logical Clocks, Hyperscale AI for the Enterprise with Hopsworks.

Logical Clocks has raised €1.25 million in seed funding. The latest funding will be used to launch Hopsworks, a data platform for AI.

The funding is raised from Inventure, Frontline Ventures, and AI Seed. Further, the funding round Led by Timo Tirkkonen of Inventure.

Logical Clocks AB was co-founded by Assoc. Prof Jim Dowling, Prof Seif Haridi and researchers at KTH University and RISE SICS in Stockholm.

Hopsworks’ Big Data platform, Hops, was shown to be the world’s fastest Hadoop in work done in collaboration with Spotify and Oracle. Hopsworks’ existing customers are in a variety of verticals from finance, to the vehicle industry, to telecoms, and healthcare.

Chairman of the board, Inventure, Timo Tirkkonen said, “Hopsworks is a continuation of Scandinavia’s history of producing transformative computing platforms - this time for Big Data and AI. This funding will scale engineering to accelerate innovation while keeping the focus on building out the customer base.”

Associate Professor at KTH University, Dr. Jim Dowling (CEO) said, “Our mission is to help enterprises transform their data into intelligence, whether that data is on-premises or in the cloud. Hopsworks is a user-friendly platform for data science that can be used to build end-to-end pipelines that take raw data and refine it progressively until you have a model ready for use in production. Hopsworks will manage your valuable assets for AI in the industry’s first enterprise feature store, managing features for generating training data, experiment versioning for repeatable data science, and model management.

Logical Clocks provides Enterprise support for the open-source Hopsworks platform. It is used to solve the data problem for Deep Learning and AI, where a new class of platform with support for GPUs is needed to refine ever-increasing volumes of data into training data, the fuel for AI systems.