Generative AI has become a key part of coding workflows, but most companies struggle to track its usage, let alone its return on investment. Israeli startup Landmark hopes to help with a platform designed to correlate the use of AI tools with engineering metrics, including code quality.
The catch is that those companies have to give Milestone access to their codebases, a bet that investors initially questioned, CEO and co-founder Liad Elidan told TechCrunch. But with clients including Kayak, Monday and Sapiens, the startup has now raised a $10 million funding round led by San Francisco-based venture capital firm Heavybit and Israeli firm Hanaco Ventures.
In an unusual coincidence, Elidan and Milestone’s CTO, Professor Stephen Barrett, had gone years without meeting in person when they started fundraising. Unlike most of Milestone’s Israel-based team members, Barrett lives in Ireland and teaches computer science at Trinity College Dublin, where Elidan was once his student and the two connected through software projects.
Despite the distance, the duo kept in touch over the years and eventually decided to found a startup focused on engineering efficiency, just as coding assistants and other code generation tools were taking off. GitHub Copilot has since surpassed 20 million users, but companies still lack visibility into how these tools are being used and impacting productivity.
According to Elidan, Milestone answers these questions by building on four pillars—codebases, project management platforms, team structure, and the coder tools themselves—to create what he describes as “a GenAI data lake.” In practice, this gives organizations actionable data about which teams are using AI and to what effect — thanks to their own insights.
Armed with this data, managers who are under constant pressure to leverage AI to drive productivity can, for example, measure the speed of feature delivery, Elidan said, and they can discover whether recent bugs were caused by AI-generated code, and they can make informed decisions about where to apply these tools.
This also gives Milestone a front-row seat to ROI — the “holy grail question” it aims to answer in detail for its clients. But at a high level, he said, “We don’t have a customer who used Milestone and said, ‘OK, GenAI isn’t helping me, I’m going to revoke all my licenses.’ In fact it is the opposite. They want to test more Gen AI tools.”
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This rapid adoption also means Milestone must keep pace with a rapidly evolving landscape. “It used to be autocomplete, then chat, then agent-based chat and on and on,” Elidan said.
That’s also where Barrett’s academic background helps the team understand the wave of transformation their clients are going through. “Many of the ways we’ve been thinking about engineering will have to change,” the professor told TechCrunch. “I think in a way, AI is complementing the team and engineers are now becoming managers.”
To keep up with the tools powering this wave, Milestone says it has partnered with multiple vendors, including GitHub, Augment Code, Qodo, Continue and Atlassian — the company that powers Jira and whose venture arm Atlassian Ventures also participated in this seed round.
The round was also backed by angel investors including GitHub co-founder Tom Preston-Werner, former AT&T CEO John Donovan, Accenture senior technology consultant Paul Daugherty, and former Datadog president Amit Agrawal — all of whom understand that what Milestone is building is relevant to the business market in question, Eli.
That focus on the business was intentional from day one, with Milestone saying no even to prospects who were too small — “a very difficult thing,” Elidan said, but something that gave the startup clarity around a roadmap that required enterprise credentials and features. Focus would be his main advice to other founders, and Milestone is taking advantage of it: The startup won’t expand on measuring GenAI’s impact on marketing or other functions, even as it grows.
