‍The Challenge

A Fortune 500 insurance company was looking at AI agents to automate claims processing, the kind of efficiency gain that could process thousands of claims faster, reduce manual review bottlenecks, and free up adjusters to focus on the complex cases that actually need human judgment. But insurance isn't like consumer tech where you can ship fast and fix bugs later.

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When an AI agent incorrectly denies a valid claim, that's not a support ticket - it's a lawsuit waiting to happen. When it approves something it shouldn't, that's direct financial loss and potential regulatory scrutiny. The insurer's AI team understood the upside, but they also understood the stakes. They needed visibility into their AI systems before putting them in front of customers.

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Traditional monitoring could tell them if systems were up or down, but it couldn't tell them if their agent had just hallucinated policy language or why it decided to deny a claim that should have been approved. They needed a way to evaluate agents before deployment, trace every decision in production, and get domain experts (people who actually understand insurance, not just engineering) involved in validating outputs.

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The Solution

HoneyHive had built their platform for exactly these high-stakes environments. Pre-deployment evaluation against test suites to catch issues before they ship. End-to-end tracing using OpenTelemetry to understand agent decision chains. Annotation queues where insurance domain experts can grade outputs without needing to understand the underlying code. Session replays to debug specific decisions. Alerts when quality metrics start to drift.

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The technical fit was obvious. What would normally be a 12-18 month enterprise sales cycle - security reviews, compliance audits, legal approvals, pilot programs that go nowhere - took a different path. Through the Zero Prime network, we made the introduction. The insurer needed what HoneyHive had built, and HoneyHive had just achieved SOC 2 Type II, GDPR, and HIPAA compliance. Both sides were ready to move.

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The Results

Today, HoneyHive is deployed across multiple divisions at the Fortune 500 insurer, giving them the confidence to ship AI in a regulated environment where mistakes carry real financial and legal consequences. For HoneyHive, the deployment validates their platform at the scale that matters most: Fortune 500 enterprises with compliance requirements and domain experts who need to stay in the loop.

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The company recently raised $7.4M and is now working with Global Top 10 banks and other Fortune 500 companies in production. Their platform addresses what we see as one of the fundamental challenges in enterprise AI: how do you ship agents in environments where "move fast and break things" isn't an option?

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Why This Matters

Breaking into Fortune 500 accounts, especially in regulated industries like insurance and banking, typically takes years for early-stage companies. The procurement processes are designed to move slowly, and for good reason. These are environments where AI failures have consequences beyond bad user experiences.

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The intro didn't bypass those processes, but it got the HoneyHive founders into conversations with a high-volume insurer that was looking for a solution. When one of our portfolio companies has built the right product for the right buyer, our warm intros can turn 18-month sales cycles into actual deployments and enterprise contracts.