Milestone raises $10 million Seed round to measure AI’s true impact on code
The Israeli startup helps companies track how AI tools like Copilot and Claude Code affect code quality and speed.
Milestone, which has developed an enterprise platform for measuring the adoption and impact of AI coding tools, announced on Thursday that it has raised $10 million in Seed funding led by Heavybit and Hanaco Ventures, with participation from Atlassian Ventures and notable angel investors, including John Donovan, former CEO of AT&T, Tom-Preston Warner, co-founder of GitHub, Paul Daugherty, former CTO of Accenture and Amit Agrawal, past president of Datadog.
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Milestone has developed a platform that connects to the full chain of enterprise development and AI-based coding tools, such as GitHub Copilot, Claude Code, Windsurf, and Cursor. The platform tracks how these tools are used and cross-references the data with metrics such as code quality, development speed, and long-term maintainability, providing development leaders with a clear view of how AI is affecting real performance.
The company said it already works with dozens of clients, including Sapiens, monday.com, Kayak, Cross River Bank, HiBob, Varonis, and Blackhawk Network.
Milestone was founded by CEO Liad Elidan and CTO Prof. Stephen Barrett, who met at Trinity College Dublin, where they began a long-standing research collaboration focused on measuring software development efficiency. The company currently employs around 25 people in Israel and the U.S. and plans to expand its development and product teams in the coming months.
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“Generative AI is rewriting how software is built, but most companies are still guessing at the results,” said Liad Elidan, co-founder and CEO of Milestone. “Milestone closes that gap by quantifying what’s actually happening inside engineering organizations so they can turn AI adoption into measurable performance. When teams can finally see how AI affects their work, they trust it more, and that trust drives broader adoption across the company. That’s how you create a real AI culture, not just AI experimentation. An AI culture means every developer, team, and manager understands the value of AI in their workflow, speaks the same language of metrics, and uses data to continuously improve how they build software.”
