Sapiom Secures $35 Million to Help Companies Control AI Agent Costs

Sapiom raised $35 million in a Series A round to continue growing its platform that helps builders ship, run and scale artificial intelligence agents.

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.