A San Francisco startup that built software to track whether companies are actually getting their money's worth from artificial intelligence just pulled in $30 million in Series A funding. Larridin, which sells what it calls an AI value-measurement platform, said the new round brings its total funding to $47 million as enterprises nationwide wrestle with ballooning AI bills and murky returns.
Pelion Ventures Leads a Crowded Funding Round
The Series A was led by Pelion Ventures, with participation from existing backers Andreessen Horowitz and Gradient Ventures, according to Business Insider. New investors GFT Ventures, W23, Thayer Investment Partners, DG Daiwa Ventures, Alumni Ventures and Cougar Capital also joined the round, the outlet reported. Larridin's own announcement, posted on the company's blog, confirmed that total funding now stands at $47 million, with the fresh capital earmarked for product development and team growth.
Business Insider's report adds that Larridin had a 20-person workforce heading into the raise, and that the company wants to double its head count. The outlet also cited Larridin chief executive Russell Fradin, who said business picked up around the second quarter of the year as more companies grew concerned about their AI costs. Per the same report, companies have increasingly shifted their attention toward squeezing better returns out of AI spending once the size of their bills became apparent.
What the Platform Actually Measures
Larridin describes itself as an AI value-measurement platform that gives enterprises visibility into AI costs, the team output produced with that spending, and opportunities for further automation. An independent profile from Altss notes that the platform measures four dimensions of enterprise AI usage — adoption, workflow changes, developer output and velocity, and AI-related spending — by connecting to tools such as GitHub, Jira and procurement systems to generate role-specific reporting for business leaders, according to Altss.
The company also recently expanded its reach: Larridin announced in late September that its products became available on Google Cloud Marketplace, according to Yahoo Finance. In that same announcement, Larridin said its platform has tracked more than 2 billion AI sessions and provides visibility into AI usage across more than 60,000 enterprise users.
Customer Numbers and an Independent Challenge
Business Insider reported that Larridin grew from having one enterprise customer in December of the prior year to 50 customers now. But the Altss profile pushes back on how verifiable those figures are, stating that the company does not disclose the number of customers, the time period measured, or any third-party audit behind its reported results. Larridin itself reports a 47% average increase in measurable team output across its customer base, along with a median $2.4 million in AI spend optimized within the first year — figures that, per Altss, remain vendor-supplied rather than independently confirmed.
Larridin's own Q3 2026 data offers a more granular look at engineering teams it measures: AI-assisted pull requests rose from 35% of merged code changes to 62%, while code cycle time dropped from 9.5 hours to 7.3, according to the company's blog post. Output per engineer rose 33% between the second and third quarters of 2026, though Larridin's own report notes that AI spend per unit of output was 89% above its May level by September — and the company explicitly states that its findings are descriptive and do not establish causation.
A Broader Industry Reckoning Over AI Returns
Larridin's pitch lands amid wider industry uncertainty about whether AI investments are paying off. A Deloitte survey found that 81% of companies reported faster decision-making from AI, yet only 25% said they were using it to deeply transform their businesses. The same survey found 71% of companies track total AI inference and API spending, but only 44% track per-unit inference cost — and 23% said accountability remained unclear when an AI system produced a negative outcome.
Deloitte also found the share of companies reporting revenue gains from AI climbed to 28%, up from 20% in its January report, while 40% of companies now allow AI systems to execute decisions without human approval to at least a moderate degree. A separate Larridin-backed study with Carnegie Mellon researchers found that companies with the most specific AI disclosures in public 10-K filings saw an 8% revenue-growth advantage over those with the least detailed disclosures — though the study found no similar link to operating margins or future stock performance. A 2025 report from the Wharton School found 72% of enterprises were formally measuring generative AI ROI, with three out of four leaders reporting positive returns.
As first reported by The National Law Review, Larridin's funding announcement frames the company as building tools to prove AI's impact across both human and AI-agent workforces, reflecting the growing enterprise pressure to justify AI spending with hard numbers rather than assumptions.
