Openeyes

Company Overview

Snapshot

Founded in March 2020 by Dan Charash, Yoav Oron, and Omry Sendik, Openeyes operates with 11–50 employees. The company has raised $23M across two funding rounds from three investors.

Business overview

Openeyes is an insurance company focused on providing innovative commercial automotive insurance solutions for fleets. The company leverages cutting-edge technologies, including a risk management platform that analyzes telematics, weather, and traffic data to identify accident risks and help fleet managers improve safety. Additionally, Openeyes utilizes advanced algorithms and machine learning for precise underwriting and streamlined claims handling, aiming to offer lower rates and greater efficiency for its customers in the Fintech & Insurtech sector.

Strategic signal

This funding validates the company's approach to commercial automotive insurance for fleets, signaling investor confidence in its technology-driven risk management and underwriting solutions. The investment suggests a focus on scaling operations and further developing its platform to address the specific needs of the commercial automotive industry.

Company Intelligence Q&A

When was Openeyes founded and by whom?

Openeyes was founded in March 2020 by Dan Charash, Yoav Oron, and Omry Sendik.

What is Openeyes' primary focus?

Openeyes focuses on providing commercial automotive insurance to fleets, aiming to offer lower rates by helping fleet managers reduce the frequency and severity of traffic accidents.

What is the core technology offered by Openeyes?

The core of Openeyes' offering is its risk management platform, a software solution that analyzes data from telematics, weather, and traffic to identify risk sources and provide insights for accident prevention.

Which investors participated in Openeyes' February 2023 funding round?

In February 2023, Openeyes secured an A Round with participation from Pitango First.

How does Openeyes improve underwriting and claims handling?

Openeyes uses advanced algorithms and machine learning techniques to underwrite policies more accurately, which can lead to lower rates for customers, and also streamlines claims handling for quicker and more efficient processing.