Twenty-five years ago, Jim and I helped build the foundation of digital measurement at Comscore, turning the chaos of the early web into strategic business intelligence. Today, we're witnessing history repeat itself on an unprecedented scale.

We are excited to announce we have raised $30 million in Series A funding. Pelion Ventures led the round with existing investors Andreessen Horowitz (a16z) and Gradient Ventures, and new investors GFT, W23, Thayer, DG Daiwa Ventures, Alumni Ventures and Cougar Capital. This financing brings Larridin’s total funding to $47 million, to help leaders understand where AI is delivering value, where to invest, and how to improve workflows between humans and agents.

Gartner now forecasts that worldwide AI spending will reach $2.7 trillion in 2026, up nearly 50% in a single year, with another 36% jump expected in 2027. Marc Benioff has predicted "three to twelve trillion dollars of digital labor getting deployed." Yet enterprises are making massive technology investments while flying blind on what's actually working. That’s where Larridin comes in.

We started Larridin to answer a simple question: is AI actually working? Since then, the question has gotten bigger. AI has quickly evolved from asking questions in ChatGPT to now running major parts of entire businesses. It’s coding agents shipping pull requests, multiple agents running workflows end to end, and unexpectedly large token bills giving CFOs & CTOs heart attacks. In the past year, it has become clear to virtually every enterprise that AI deployments need a measurement layer. Larridin is that layer; the one platform that proves AI’s impact across your human and agent workforce.

Today, Spend Intelligence traces every license, token, and cloud model cost to the teams and agents using them. AI Impact shows adoption, fluency, and the hours AI returns in every department. Developer Intelligence connects engineering output, code quality, and delivery to AI spend, so engineering leaders can see where coding agents help and where teams need support. Workflow Intelligence finds the repeated work AI should take on next, then tracks each automation against a measured baseline. Together, they let leaders answer the three questions that matter most: what AI costs, what it changes, and where to transform next.

Larridin is moving as fast as AI is moving. Each month, our ability to help clients understand how their teams are using AI and identify opportunities to improve performance and ROI gets exponentially better.

This new funding lets us go further, faster. We’ll keep deepening how we measure the work people and agents do together, grow our engineering and customer teams, and keep publishing independent research like our State of Enterprise AI report and Larridin Data, so the whole market can see more clearly.

Twenty-five years ago, the web needed a measurement standard before it could become a real business. AI needs one now, and we intend to build it.

Let’s chart the path forward, together.

Russ, Jim, and Ameya