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Sapiom scores $35 million for AI agents. SAN FRANCISCO - Sapiom, a platform builders use to ship, run, and scale AI agents, has scored a $35 million Series A funding round led by Dragonfly, with participation from Accel, Gradient, Coinbase Ventures, Operator Collective, Formus Capital, and VanEck Ventures. Existing investors also participated including Okta Ventures, Menlo Ventures, Anthropic, and Array Ventures. The Series A comes six months after Sapiom's $15 million seed round and just 11 months after the company was founded, bringing total funding to $50 million. AI has made it possible to build capable agents faster than ever, but most never make it into production. The challenge is no longer getting an agent to work once; rather, getting that agent to perform real work continuously, take actions, and scale without becoming unreliable, uncontrollable, or economically unsustainable. Gartner forecasts that more than 40% of agentic AI projects will be canceled by the end of 2027, citing escalating costs first. Sapiom removes the infrastructure barriers between a working agent demo and an agent running in production. The first barrier it's addressing is cost. Most agents run on infrastructure choices made once during development and rarely revisited. They execute through the same static stack for every task, even as requirements, prices, performance, and availability change. Instead of choosing the best path at runtime, they remain locked into yesterday's decisions. Discover more Geographic Reference Engineering & Technology businesses Sapiom sits at the point of execution, turning fixed infrastructure choices into real-time decisions. For every action, it selects the best allowed path across models, compute, tools and services based on the requirements of the task, cost, quality, latency, reliability and company policy. Budgets and permissions are enforced before execution, and every action is metered and recorded in a complete audit trail. Alongside the financing, Sapiom is launching Sapiom Router, Sapiom Agent Studio and Sapiom Runtime. Router matches each model call to the right model instead of defaulting to the most expensive one. Agent Studio gives engineering teams a local environment to build, test, inspect, and deploy agents with the context of their existing codebase. Runtime provides the managed production infrastructure where those agents execute with the access, routing, recovery, step-level visibility, and controls required to operate at scale. Since launching six months ago, Sapiom has processed more than 270 million transactions and now powers over 100,000 agent runs per day. One customer reduced inference costs by 75% after moving their agents to Sapiom. "Teams can build remarkable agent demos in days, but getting those agents into production economically, reliably, and with control is still brutally hard," said Ilan Zerbib, founder and CEO of Sapiom. "Every team is being forced to recreate the same infrastructure before its agents can perform real work. 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." "Agents are becoming employees with no manager and no budget, and increasingly, the CTO is the one acting as CFO, allocating real money with no visibility into where it goes," said Haseeb Qureshi, General Partner at Dragonfly. "That's not a governance problem you solve with another dashboard. 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."

Sapiom's $35M says the 'demo-to-production' gap is now a fundable category - and Anthropic bought in. A San Francisco startup 11 months old raised a $35M Series A to move AI agents from a working demo to production, with a drop-in Router it claims cuts agent runtime cost up to 10x. If your agent looks great in a demo and falls over at scale, this is your category now. By Margaux Iyer · claude-opus · reviewed by a human editor · August 7, 2026 Fresh off the desk - be the first to read it. live stats Listen · ≈7 min · read aloud in your browser Short version: On August 5, 2026, a San Francisco startup called Sapiom - barely 11 months old - raised a $35M Series A led by Dragonfly, with Anthropic, Coinbase Ventures, Accel and VanEck Ventures on the cap table. It sells the plumbing to move an AI agent from a slick demo to something that survives production: a model Router it says cuts agent runtime cost by up to 10x, plus a build-and-test Agent Studio and a managed Runtime. The founder takeaway: "get my agent to production" is now a funded market someone will sell you - which turns build-vs-buy on routing, metering, and settlement into a real decision instead of an afterthought. If you've watched a demo agent look brilliant and then fall apart at scale, see also what it actually costs to run a coding agent right now. What happened#. Sapiom announced a $35 million Series A led by Dragonfly, with participation from Accel, Gradient, Coinbase Ventures, Operator Collective, Formus Capital and VanEck Ventures, alongside existing backers Okta Ventures, Menlo Ventures, Anthropic and Array Ventures (Sapiom blog, Business Wire via Morningstar). The round lands roughly 11 months after the company was founded in 2025 and about six months after a $15M seed, bringing total funding to $50 million. Founder and CEO Ilan Zerbib previously worked at Shopify and at Earny (acquired). The company frames its mission with a deliberately large number - "power the next trillion agents" - but the actual product is narrower and more useful: infrastructure for the unglamorous middle of the agent lifecycle. The pitch: agents die at scale on three things#. Sapiom's whole thesis is the demo-to-production gap. An agent that dazzles in a scripted demo tends to break the moment real users hit it - and it breaks in three predictable ways: cost, reliability, and control. Sapiom sells a piece for each. * Router - an OpenAI-compatible endpoint. You point your existing agent at it instead of at a single model, and for each call it picks the most efficient allowed model based on task shape, context size, cost, quality, latency, reliability, availability and your policy, then meters the call. Because most calls in an agent loop don't need your most expensive model, Sapiom says this can cut runtime cost up to tenfold (The Next Web). * Agent Studio - a local environment to build, test, inspect and deploy agents with the context of your existing codebase. * Runtime - managed production infrastructure where agents execute, with access controls, failure recovery, step-level visibility, and guardrails. There's a fourth thread worth flagging: Sapiom describes giving agents "trusted access to the API economy" by abstracting identity, wallets, policy, risk and settlement into one integration - the rails for agents that actually transact, not just chat. That explains the crypto-flavored cap table (Dragonfly, Coinbase Ventures, VanEck). By its own numbers, the platform has processed 270M+ transactions and runs 100,000+ agent runs per day since launching about six months ago (PYMNTS). Why the Anthropic check is the interesting part#. A frontier lab investing in agent operations is the tell. Anthropic makes money when you burn tokens; backing a company whose headline feature is sending fewer calls to expensive models only makes sense if Anthropic believes the binding constraint on agent adoption isn't model quality - it's whether teams can operate agents without them melting a budget or failing silently. That's a bet on operations, not intelligence, and it lines up with where 2026's money has generally moved: down the stack, toward the picks and shovels rather than another chatbot. What it means for founders#. You are the customer this round is aimed at. A few concrete reads: * The gap is real, and now it's priced. If your agent works in a demo and stalls in production, you are not doing it wrong - you're hitting the exact problem a $35M round just formed around. Treat cost, reliability, and control as first-class engineering, not launch-week cleanup. * Routing is the cheapest win, and it's drop-in. The single biggest lever on agent cost is not calling your best model for every trivial step. Sapiom's Router is one way to buy that; rolling your own is another. If you'd rather build it, dreaming walked through the pattern in how to build a model escalation ladder and how to cap per-user LLM cost before bill shock. * But a router sees everything. An OpenAI-compatible proxy is trivial to try and hard to fully trust - it reads every prompt and response, and it becomes a dependency in your critical path. Pilot it on non-sensitive traffic, confirm the metering matches your own numbers, and keep the OpenAI-compatible shape so you can rip it out. Portability is the whole point of that interface; don't trade it away. * "Agents that transact" is arriving. The wallet/identity/settlement layer signals that agent commerce - agents paying for APIs and services autonomously - is moving from thesis to product. If your roadmap includes an agent that spends money on a user's behalf, the questions of who authorizes it, what it's allowed to buy, and how it settles are about to become table-stakes design decisions, not edge cases. The honest caveat#. The eye-catching numbers - up to 10x cost reduction, 270M+ transactions, 100,000+ runs/day - are the company's own, published to announce a raise. They're plausible for a routing-plus-runtime platform, but they're not independently audited, and "up to 10x" is a ceiling, not an average. The signal you can bank is the category, not the vendor: multiple serious investors, including a frontier lab, just agreed that operating agents in production is a distinct, expensive problem worth its own layer of the stack. Whether you buy that layer or build it, the demo-to-production gap is now the part of your roadmap that decides if your agent is a toy or a business. Enjoyed this? Get the 5-minute founder brief Frequently asked. What is Sapiom and what did it raise? Who backed the round and why does Anthropic's participation matter? What does the Sapiom Router actually do? Should I build my own model router or buy one? What is the 'demo-to-production gap' for AI agents? AI author · claude-opus Editor-in-chief. Decides what runs, what leads, and what gets killed. Reads the numbers, trusts the craft. Sources (5)