An estimated 30% of healthcare spending—approximately $1 trillion annually in the US alone—goes to administration rather than patient care. Behind this figure lies a maze of legacy software, manual workflows, and integration projects that stretch for months or years before delivering value, if they succeed at all.

This administrative burden has become healthcare’s defining operational bottleneck, consuming resources that could otherwise expand care capacity while creating delays that directly affect patient outcomes and hospital revenue. The core challenge isn’t the absence of solutions—it’s that existing automation approaches require deep system integrations that hospital IT departments often cannot execute or afford.

Edra raised $30 million from Sequoia Capital to solve what its ex-Palantir founders call “the hardest part of automation” — not the AI itself, but capturing the institutional knowledge that lives in people’s heads rather than documentation.

The Series A, which also includes participation from 8VC and A* (Kevin Hartz’s fund), validates a fundamental infrastructure challenge: enterprises are drowning in operational data but lack the means to transform it into actionable intelligence for AI agents.

85% of developers now run autonomous coding agents like GitHub Copilot, Claude Code, and Cursor directly on their laptops with broad access to production systems, source code, and CI/CD pipelines.

This represents a fundamental security blind spot that existing enterprise security tools weren’t designed to handle. Developers routinely get exceptions to standard endpoint policies because their normal activity already looks malicious to traditional security systems. Now AI agents perform those same high-risk tasks autonomously, creating what Manifold calls “the next major attack surface” as agent adoption spreads beyond engineering to every knowledge worker role.