Company Overview
Snapshot
Founded in May 2023 by Ben Luria, Oded Shmueli, and Michael Leybovich, Hirundo operates with 11–50 employees. The company has raised $9.7M across two funding rounds from four investors. In June 2025, Hirundo secured an $8M Seed funding round, led by Maverick Ventures Israel.
Business overview
Hirundo develops a platform designed to optimize machine learning data for teams, addressing critical issues within the machine learning lifecycle. Its core technology focuses on optimizing and reducing training data, analyzing the root causes of model prediction faults, and enabling the removal of problematic data from training models without necessitating a full retraining process. The company serves enterprises and professional services within the software development industry, operating primarily in the Business Software sector with a focus on Artificial Intelligence and Natural Language Processing.
Strategic signal
In June 2025, Hirundo announced an $8M Seed funding round, led by Maverick Ventures Israel, to advance its machine unlearning technology. This investment validates the growing market need for solutions that tackle critical AI challenges such as hallucinations, bias, and toxic data in trained models, signaling strong investor confidence in Hirundo's approach to enhancing AI reliability and ethical deployment.
Log in to access full profile ›Company Intelligence Q&A
- When was Hirundo founded?
- Hirundo was founded in May 2023.
- Who are the founders of Hirundo?
- The co-founders of Hirundo are Ben Luria, Oded Shmueli, and Michael Leybovich.
- What was a significant funding event for Hirundo?
- In June 2025, Hirundo raised an $8M Seed funding round. The round was led by Maverick Ventures Israel, with participation from Plug and Play and Alpha Intelligence Capital.
- What recognition did Hirundo receive in July 2025?
- In July 2025, Hirundo won first prize in the RAISE Summit Start-Up Competition, beating over 1,100 other AI startups.
- What is Hirundo's primary focus in AI?
- Hirundo specializes in machine unlearning, developing technology to make AI models 'forget' hallucinations, biases, and vulnerabilities by removing problematic data from training models without retraining.