There's a question enterprise risk managers keep encountering in procurement reviews, and it's proving remarkably hard to answer: Who covers you if your AI agent screws up?
Not the standard tech errors-and-omissions policy, which increasingly carves out autonomous systems. Not cyber insurance, which was written for breaches and ransomware, not hallucinations. When an AI agent exceeds its authority, leaks customer data, or makes a binding commitment the company never intended, the coverage question lands somewhere between a shrug and a polite "we'll get back to you."
For B2B companies deploying agents into production workflows, that gap has hardened into a procurement obstacle. Buyers want proof of coverage before they'll sign. And into that vacuum has rushed a cluster of startups—Klaimee among them—promising purpose-built policies for risks the incumbents won't touch.
A Product in Two Acts
Klaimee, a San Francisco startup backed by Y Combinator, positioned its public launch around a regulatory deadline. The company went live in early 2026, with messaging that leaned heavily on the EU AI Act's high-risk obligations—set to begin enforcement in August 2026—and Colorado's new AI law, which took effect February 1, 2026, both of which impose liability frameworks that traditional insurance products don't neatly address.
But dig into the website and there's a mismatch. What Klaimee actually delivers today is a "Certification + Guarantee Pack"—essentially a risk assessment that scores AI agents across eight failure modes, from scope violation to model drift, and pairs that with remediation guidance and a financial guarantee. The full insurance product? "Coming soon," according to the fine print. That sits awkwardly alongside the company's earlier YC announcement, which suggested underwriting was already underway with 24-hour turnaround times.
Perhaps that's just startup velocity outpacing its own marketing copy. Or maybe it's the reality of building an insurance product from scratch—capacity takes time to source, policy language has to be drafted and reviewed, actuarial models need claims data that doesn't exist yet. Either way, the company's current offering is more risk audit than insurance policy.
The certification itself evaluates agents across dimensions like data exfiltration, unauthorized actions, output integrity, adversarial manipulation, and operational control failures. Companies walk away with a letter grade, a "Klaimee Certified" badge, and documentation designed to satisfy the vendor questionnaires that started all this procurement friction in the first place. Agents that score well, the pitch goes, will eventually get prioritized access to the insurance product—and lower premiums tied to their risk profile.
Why the Gap Opened
The liability void Klaimee is targeting didn't materialize overnight. In January, the Insurance Services Office introduced two new endorsements—CG 40 47 and CG 40 48—that explicitly carve out generative AI and autonomous system risks from commercial general liability policies. Carriers, confronting exposure they can't yet model, are repricing accordingly. The exclusions are spreading.
Ines Boutemadja, Klaimee's CEO and a former insurance growth lead at SafetyWing, has pointed to the Air Canada chatbot case as the ur-example: an agent makes a promise the airline had to honor, and the standard policy language offered no clear path to coverage. In an April blog post, she framed the problem as procurement friction. Customers ask for proof of AI liability insurance. Vendors go silent. Deals stall.
The regulatory calendar sharpens the urgency, at least in theory. The EU AI Act's obligations for high-risk systems were set to begin enforcing in August, though pending legislative amendments may push certain application dates into 2027 or later. Colorado's statute took effect in February. Either way, the combination of regulatory exposure and policy exclusions has handed procurement teams leverage—increasingly, they're requiring vendors to demonstrate affirmative coverage before contracts get signed.
Whether that dynamic is widespread or confined to certain verticals remains an open question. But the anecdotal evidence suggests enough friction to support a market.
First, or Just Early?
Klaimee's claim to be "the first" purpose-built coverage for AI agents runs into an inconvenient fact: several others got there earlier.
Armilla AI launched a coordinated structure with Lloyd's syndicate Chaucer in February, offering limits up to $25 million per policyholder and explicitly covering agent scenarios. Testudo, a Lloyd's-backed managing general agent, began underwriting U.S. AI liability policies in early 2026 and expanded its capacity panel in March with Atrium and QBE. HSB, part of Munich Re, introduced AI liability insurance for small and midsize businesses on March 18.
Then there's the startup layer. Ollive markets coverage for hallucination and algorithmic bias. Redberry Labs advertises "AI Liability Insurance for Autonomous Agents," covering misselling and incorrect fund transfers. RiskHelm offers first-party indemnity for execution errors—though it notably excludes third-party claims and hallucinations, arguably the riskier exposures. Cybe and Luphra are collecting waitlist signups.
What differentiates these approaches is scope and underwriting philosophy. Some products layer onto existing cyber or tech E&O towers; others are standalone. Some cover only first-party losses—your own costs when the agent fails. Others include third-party liability—the damages you owe someone else. Klaimee's bet is that certification comes first, and insurance follows the risk grade. Score well, get coverage. Score poorly, perhaps you don't.
It's a tidy model in theory. In practice, it requires solving adverse selection: only the riskiest deployments will buy coverage, which drives up premiums, which drives away the safer risks, and so on. The business model needs enough volume from lower-risk customers to subsidize the inevitable claims from higher-risk ones. That's insurance 101, but in a category with almost no claims history, the pricing is guesswork dressed up in spreadsheets.
An Industry Taking Shape in Real Time
A May report from Gallagher Re documented the exclusions and the emergence of dedicated AI liability products, noting that underwriters are building discipline into a category where the loss data is effectively nonexistent. Industry publications have tracked similar movement—capacity flowing into the space, policy forms proliferating, pricing still unsettled.
Klaimee itself is a small operation: Boutemadja and CTO Julien Catonnet, who brings AI software and enterprise compliance experience. The YC profile notes Boutemadja as the first Algerian woman in the accelerator. One unconfirmed source lists a $500,000 seed round in March, though neither the company nor YC have publicly disclosed funding details. (A startup this early is rarely flush with resources, which may explain why the insurance product remains in development while the certification tool ships.)
The immediate test is execution. The website FAQ acknowledges the insurance offering is "launching soon," with certified agents first in line. Whether that timeline holds—and whether Klaimee can source capacity and price risk competitively against incumbents already binding policies—will determine if this becomes a business or just a certification consultancy with ambitious plans.
What's Clear, and What Isn't
For enterprise risk managers, the broader takeaway is straightforward enough: the liability exposure is real, traditional policies don't cover it, and multiple carriers are now writing affirmative coverage. The procurement question has shifted. It's no longer "do we need this?" but "which product fits our deployment profile?"
What remains murky is whether the market is big enough to support this many entrants. AI agents are proliferating, yes, but most deployments are low-stakes—customer service triage, email drafting, meeting summaries. The catastrophic loss scenarios that justify insurance premiums are concentrated in a narrower band: financial transactions, legal advice, healthcare triage, high-stakes decision automation. That's a real market, but maybe not a large one. Not yet.
The other uncertainty is claims. Insurance products get stress-tested by loss events, and those haven't arrived at scale. When they do—and they will—the question is whether these policies hold up, or whether the fine print quietly excludes the very risks everyone thought they were buying coverage for. That's a story for another day, probably after the first round of coverage disputes lands in court.
In the meantime, the race is on. Klaimee and its competitors are selling a product the market didn't know it needed two years ago, trying to get distribution before the category consolidates. It's early, the rules are unwritten, and the claims experience that will eventually define the winners hasn't happened yet. Which is to say: typical startup dynamics, with the added twist that the product is insurance, and insurance is supposed to be boring.
