Sapiom Raises $35M Series A to Slash AI Agent Costs as Companies Scrutinize Spending

Sapiom raises $35M to cut AI agent running costs

Sapiom raised $35 million to cut the runtime cost of AI agents, sometimes by tenfold. Among the investors backing it is Anthropic, one of the model makers whose bills it is built to shrink. Sapiom is a San Francisco startup that sits between AI agents and the models they run on. It has raised a $35 million Series A. Dragonfly led the round. It comes 11 months after the company launched, and six months after a $15 million seed led by Accel. That takes total funding to $50 million. The pitch is narrow and timely: make AI agents cheaper to run. At the moment an agent acts, Sapiom decides which model, tool, or service it may use. It enforces a budget before the money is spent. Its Router sends each call to the cheapest capable model, not the most expensive one. The platform has processed more than 270 million transactions since launching six months ago. The bill that made the case The clearest case is a customer named Polsia. The AI startup employs nobody, running swarms of agents to help operate other businesses. Its projected revenue jumped from $100,000 to $10 million in a year, Semafor reported. But its token bill climbed with it, hitting $1.2 million a month on Anthropic. After Sapiom ran a series of evaluations, that bill fell roughly tenfold, to about $100,000. "It's just unsustainable," founder Ilan Zerbib told Semafor. He argues that startups cannot deploy at the prices frontier labs charge, even when the demand is there. Here is the awkward part. Anthropic is one of Sapiom's investors, returning for the Series A alongside Okta Ventures, Menlo Ventures, and Array Ventures. A model maker is helping fund the startup whose product is spending less on model makers. Zerbib frames it as aligned, not adversarial. Cheaper inference lets companies build more agents. Some of that work, he argues, will still need the most powerful models. Cost is the new constraint Sapiom is riding a shift in how companies talk about AI. Gartner forecasts that companies will cancel more than 40% of agentic AI projects by the end of 2027. Escalating costs are among the leading reasons. Corporate AI budgets are getting their first hard audit. Some firms are already capping what staff can spend. Semafor pointed to a KPMG survey of 2,100 executives in June, in which just 7% could name established returns. Zerbib's bet is that the number of agents is about to explode. There may be tens of millions of software developers, he told Semafor. In his words, "we're talking about trillions of agents that will operate in the economy in the next three years." Most of that work, on his numbers, does not need a frontier model. "In 95% of cases, it doesn't make sense to go to a very expensive frontier model," he said. TNW has covered how US firms are already swapping frontier models for cheaper ones to control spend. Dragonfly's Haseeb Qureshi is joining the board. He calls the gap an infrastructure problem, not a dashboard one. "Agents are becoming employees with no manager and no budget," he said, "and increasingly, the CTO is the one acting as CFO, allocating real money with no visibility into where it goes." A crowded toll booth Sapiom's Router puts it up against OpenRouter, the best-known name in model routing. Its difference, per Semafor, is the infrastructure. Sapiom serves open-weight models from its own racks in a San Jose data centre. Most rivals act purely as middlemen. It charges for the compute directly, instead of adding a markup. It is one of a wave of startups selling agent infrastructure to investors this year. That edge may not last. Routing is starting to look like a commodity. Amazon and Microsoft now bundle it into Bedrock and Azure. Open-source routers are free. OpenRouter alone moves around 25 trillion tokens a week. One market tracker counts 80 active routing competitors. Sapiom is betting on what it owns underneath: the inference, and the controls around it. That, it hopes, is what separates a feature from a company.

Sapiom Secures $35 Million to Help Companies Control AI Agent Costs | PYMNTS.com

The Series A came 11 months after Sapiom was founded, six months after its launch and six months after a seed round in which it raised $15 million, the company said in a Wednesday (Aug. 5) press release. Sapiom's platform addresses the cost of running AI agents by making real-time decisions on the best allowed path across models, compute, tools and services based on the requirements of the task, cost, quality, latency, reliability and company policy, according to the release. In the six months since its launch, Sapiom has processed more than 270 million transactions. The company's platform now powers more than 100,000 agents runs per day, the release said. Sapiom also announced Wednesday that it is launching three new products: Sapiom Router, which matches each model call to the right model; Sapiom Agent Studio, which gives engineering teams a local environment for building, testing, inspecting and deploying agents; and Sapiom Runtime, which provides a managed production infrastructure in which agents can operate at scale, per the release. Sapiom Founder and CEO Ilan Zerbib said in the release that the platform is designed to help teams get agents into production economically, reliably and with control. "Every team is being forced to re-create the same infrastructure before its agents can perform real work," Zerbib said. "Sapiom exists to remove those barriers. We are starting with cost because it is where the economics break first, but our ambition is much larger: to remove whatever stands between builders and the next trillion agents." Sapiom's Series A round was led by Dragonfly, and Dragonfly Managing Partner Haseeb Qureshi will join Sapiom's board of directors, according to the release. Qureshi said in the release that Sapiom solves the common problem in which agents operate with no budget and chief technology officers allocate money with no visibility into where it goes. "That's not a governance problem you solve with another dashboard," Qureshi said. "It's an infrastructure problem, and it needs to be solved at the point where agents act and money moves. Sapiom is the only team that we have seen execute this at scale." PYMNTS reported Friday (July 31) that after two years of "tokenmaxxing," or pushing employees toward the biggest AI models and the heaviest usage, companies have shifted their focus to proving that AI usage is worth what it costs.