Artificial Intelligence is reshaping how software is built. From writing code to automating workflows, AI tools have become part of every modern engineering team. But a key question still bothers most organizations — is AI truly improving productivity, or just adding another layer of hype?
That’s the problem Israeli startup Milestone wants to solve. The company recently raised $10 million in seed funding to help businesses measure the real return on investment (ROI) of their AI tools. The round was led by Heavybit and Hanaco Ventures, with participation from Atlassian Ventures and several big industry names, including GitHub co-founder Tom Preston-Werner, former AT&T CEO John Donovan, and Accenture’s tech strategist Paul Daugherty.
Turning AI Hype into Business Value
Over the last two years, generative AI tools like GitHub Copilot, ChatGPT, and Amazon Q have become popular among developers. However, companies often find it difficult to prove whether these tools actually help in faster delivery or better code quality. Milestone was created to give leaders that visibility.
The startup’s platform integrates with an organization’s existing software stack — source control systems, project management tools, and even AI assistants — to collect data on how engineers are using AI in real time. It then analyzes that data to show whether AI is helping teams deliver projects faster, reduce bugs, or improve code quality.
Co-founder and CEO Liad Elidan explains it simply: “Generative AI is rewriting how software is built, but most companies are still guessing the results. Milestone gives them the evidence to see what’s working and what isn’t.”
Measuring What Matters
Instead of just counting how many times an AI tool is used, Milestone tracks what truly matters — delivery speed, defect rates, lead time for changes, and even how AI usage affects collaboration. The goal is to connect the dots between AI adoption and measurable engineering outcomes.
For example, Milestone’s system can show that one team using a coding assistant is completing features 25% faster while maintaining code quality. Another team might show slower progress despite similar tools — helping leaders decide where to focus training or investment.
In short, Milestone transforms AI adoption from a guessing game into a clear performance dashboard. It answers the question every CTO and CFO is asking: “Is our AI investment really paying off?”
Why This Matters
Today, more than 80% of developers use some form of AI assistance, but few companies have a strategy to measure its effectiveness. Without proper tracking, they risk overspending on tools without seeing results.
The business world is entering a new phase of AI maturity. Early adopters were driven by curiosity; now, decision-makers want numbers. They need to justify AI budgets, monitor productivity, and ensure that automation doesn’t compromise code quality. Milestone’s product fits perfectly in this phase, offering both visibility and accountability.
A Platform Built for Enterprises
Milestone isn’t targeting hobbyists or small startups. Its platform is designed for large enterprises with complex engineering structures and multiple teams. Early customers include Kayak, Monday.com, and Sapiens International — all major software-driven organizations that manage vast engineering operations.
The company’s advantage lies in integration. By connecting to developer platforms like GitHub, Atlassian, and Continue, Milestone can analyze millions of data points across code commits, pull requests, and AI-generated content. This provides leadership teams with a single source of truth for how AI tools are affecting output.
As Elidan notes, “We haven’t seen a single customer reduce their AI usage after using Milestone. In fact, they use the data to expand it more intelligently.”
The Growing Need for AI ROI
This $10 million funding round isn’t just a milestone for the company — it reflects a global shift in how organizations view AI. The era of blind experimentation is ending. Companies no longer want to just use AI; they want to prove its business value.
By providing measurable insights, Milestone helps companies move from intuition to evidence-based decision-making. It also helps mitigate risks such as poor-quality AI-generated code or over-reliance on automation without oversight.
In many industries, especially finance, insurance, and healthcare, this kind of visibility is crucial for compliance and governance. Knowing exactly how AI contributes to productivity and quality ensures that organizations stay both efficient and accountable.
Looking Ahead
Investors are confident that Milestone is building something fundamental for the future of AI adoption. Measuring performance and ROI will be essential as AI becomes a standard layer in software development.
The company plans to use its new funding to expand its engineering and data science teams, enhance integrations with major AI tools, and enter new markets across the US and Europe. Its long-term goal is to become the industry standard for tracking and benchmarking AI productivity across engineering teams.
Expert View: The India Opportunity
For India’s fast-growing tech ecosystem, Milestone’s approach offers an important lesson. As thousands of startups and IT service companies integrate AI tools into their workflows, few are measuring their true impact. If Indian enterprises start adopting data-driven AI measurement early, it could dramatically improve how they manage projects, budgets, and teams.
Moreover, the country’s emphasis on digital transformation, combined with a skilled developer base, positions Indian firms perfectly to adopt platforms like Milestone. With the right metrics in place, Indian IT firms could demonstrate productivity improvements not just to clients, but also to investors and regulators.
Conclusion
Milestone’s $10 million seed round marks a defining moment in enterprise AI evolution. The company isn’t just helping organizations use AI — it’s helping them understand its value.
In a world where every dollar spent on technology must prove its worth, Milestone bridges the gap between innovation and impact. It ensures that AI doesn’t just sound impressive but delivers measurable results — turning hype into true ROI.
