Company Overview
Snapshot
Founded in August 2014 by Niles Fleischer and Alex Nimberger, AIONZ operates with 1–10 employees. The company has secured funding across four rounds and was acquired by General Motors in June 2023.
Business overview
AIONZ, also known as ALGOLiON, develops smart diagnostic software to enhance the lifespan of lithium-ion batteries and mitigate safety risks. Its core product, AlgoShield, utilizes patented algorithms to provide early warnings for potential battery safety hazards, including fire risks, up to a week in advance. This technology serves various markets such as electric vehicles, portable electronics, medical devices, and aviation, operating within the Energy Tech sector and focusing on predictive analytics and safety solutions for lithium-ion batteries.
Strategic signal
In June 2023, AIONZ was acquired by General Motors, a significant development that validates the importance of predictive battery diagnostics in the automotive industry, particularly for electric vehicles. This acquisition highlights a strategic move by a major automaker to integrate advanced safety and longevity solutions for EV batteries, signaling a growing industry focus on preventing battery fires and extending product life cycles.
Log in to access full profile ›Company Intelligence Q&A
- What is AIONZ's primary offering?
- AIONZ's primary offering is AlgoShield, smart diagnostic software designed to extend the life of lithium-ion batteries and prevent safety hazards by providing early warnings.
- When was AIONZ acquired and by whom?
- AIONZ was acquired by General Motors in June 2023.
- Which investor participated in AIONZ's funding round in January 2021?
- In January 2021, Mobilion Ventures participated in a funding round for AIONZ.
- Did AIONZ receive any grants from European organizations?
- Yes, AIONZ received a grant from the European Aviation Safety Agency in November 2017 and from EU Horizon 2020 in October 2016.
- What is the core technology behind AIONZ's AlgoShield software?
- AlgoShield utilizes patented algorithms to provide alerts about safety risks up to a week before they could develop into a fire, without requiring supplementary hardware.