Money follows AI that proves its value

A meter for AI spend

Larridin has secured $30 million in Series A funding to scale its AI Value Measurement platform, which helps enterprises track AI adoption, spend and productivity. The platform tracks AI workflows end to end: the company says it has tracked more than 82,000 workflows, and customers report a median $2.4 million in AI spend optimized within the first year. m:…6015

The company says it has measured over 2 billion AI sessions and customers report a 47% average increase in measurable team output. Those figures are the company's own, and investors should treat them as a claim to verify, but the funding thesis is clear: as AI spend grows, someone needs to meter it, and the meter itself is now a venture-scale business. m:…6015

The bottleneck is the data

Tommy Guy, CEO of Enderis and a former Microsoft research director, identifies training data as the primary bottleneck in enterprise AI development. He argues that models require data precisely on the edge of their capability to learn effectively, a standard that synthetic data often fails to meet because it lacks real-world statistical messiness. m:…8849

The conversation also highlights the industry's shift toward task-specific optimization Enderis builds offline test suites tailored to specific agents to define product behavior, and notes that AI graders that are only 80% correct are insufficient for training enterprise agents. That framing connects directly to the funding story: if data on the edge of capability is the constraint, then companies that can produce, curate or evaluate that data hold a scarce asset, and measurement of outcomes is how buyers tell whether it worked. m:…8849

An acquisition that scales proven work

Salesforce has acquired Cresta, an AI-powered customer service platform that originated from the Stanford Artificial Intelligence Laboratory. Cresta began by providing real-time guidance to human agents and has expanded to autonomous AI agents capable of handling complete customer interactions. m:…2561

Cresta is joining Salesforce, the endpoint of a path that ran from assisting humans to handling interactions itself. The pattern is the reverse of a capability bet: Cresta's path ran from assisting humans, to handling interactions itself, to being absorbed into a platform with distribution. For investors, that path is a reminder that proven workflow automation, measured in completed interactions, is what acquirers pay for. m:…2561

Across the three items, the through-line is proof. A measurement platform raises money, a founder argues the bottleneck is data quality rather than model size, and an acquirer buys a company that automated real customer work. The enterprise AI market is increasingly priced on evidence, and the companies attracting capital are the ones building the evidence layer. m:…6015 m:…8849 m:…2561

The evidence layer

Each of the three items fills a different part of the evidence layer. Larridin meters adoption and spend, tracking more than 82,000 workflows end to end and reporting a median $2.4 million in spend optimized within the first year, giving finance and security a shared picture of what AI costs and returns. Enderis argues the binding constraint is data on the edge of capability plus human-in-the-loop evaluation to judge success, which is a claim about how value gets created rather than how it gets measured. Cresta shows the endpoint: a company that moved from guiding humans to handling interactions itself, and was acquired for that proven workflow. Measurement, data quality and automated work are three sides of the same bet. m:…6015 m:…8849 m:…2561

The $30 million Larridin round is the smallest number in this story and arguably the most telling: investors funded the meter, not just the machine. m:…6015