Pace Founder
Pace raised $10 million in Series A funding from Sequoia Capital to expand its agentic AI platform automating insurance operations, targeting a $70 billion annual business process outsourcing market in insurance and $400 billion across broader financial services operations. The startup, founded in 2024 by CEO Jamie Cuffe, counts Prudential, The Mutual Group, and Newfront among customers adopting AI agents to replace offshore outsourcing work traditionally handled by human teams processing submissions, claims, and data entry.
Bryan Schreier, the Sequoia partner leading the deal who previously worked with Cuffe at his last startup Cheer before its 2020 sale to Retool, framed the investment around a fundamental thesis that the next wave of disruption on the operations side of insurance centers on AI because the technology represents a perfect fit for the industry's document-heavy workflows. The partnership marks Sequoia's continued conviction in applying enterprise AI to industries characterized by massive document processing requirements and complex technical verbiage.
Cuffe grew up across London, New York, and Bermuda—three major insurance hubs—as his father worked for Lloyd's of London, the world's oldest and most vaunted insurance market. After years in startups, he returned to the insurance industry with a technology-first approach, arguing that AI can now accomplish work that internet connectivity enabled companies to outsource offshore during the 1990s and 2000s. The internet allowed work to be performed remotely and sent back digitally, creating the offshore BPO industry, while AI eliminates geographic constraints entirely by automating the underlying tasks.
Both Cuffe and Schreier emphasized that AI excels at reading massive quantities of material, making it particularly suited for tasks involving mountains of documents and technical verbiage. This characteristic explains why the AI moment hit the legal industry aggressively, spawning mega-unicorns like Harvey and Legora that automate legal document review and contract analysis. Cuffe argues insurance represents the next logical industry for AI disruption given similar document intensity but at substantially higher operational scale.
Legal workflows adopted AI copilots first because the tools provided immediate value and significant populations performed the work, but insurance tasks operate at dramatically higher scale with hundreds of thousands or millions of submissions and tens of thousands of claims processed by individual insurers. These organizations require systems capable of handling massive throughput while maintaining accuracy across complex technical documentation. The emergence of agentic AI capabilities enabling autonomous task execution represents the technological unlock making insurance automation economically viable.
Pace's platform combines AI for document processing and web automation with human review layers to automate traditionally labor-intensive tasks including submission intake, first notice of loss processing, and data entry workflows. The agentic approach allows AI systems to navigate internal applications, reason across multiple documents, and execute multi-step processes with minimal human intervention, fundamentally changing the economics of insurance operations by replacing hourly labor costs with software licensing models.
The company selected Prudential as its flagship enterprise customer, automating policy servicing and quality assurance tasks within Prudential's Individual Life Insurance business. The initial automated systems now handle thousands of hours of work previously performed by human teams, delivering accuracy and speed at significant scale. Prudential's adoption signals larger insurers recognize AI agents can handle mission-critical operations rather than just experimental pilot projects.
The $70 billion insurance BPO market represents immediate addressable opportunity, but including broader financial services operations surrounding the industry expands the total addressable market to $400 billion in annual spending. Traditional BPOs employ hundreds of thousands of workers processing insurance claims, underwriting submissions, policy changes, and regulatory compliance documentation across global delivery centers. AI agents targeting this market compete not against other software but against offshore labor arbitrage models where companies pay $15 to $30 per hour for skilled workers in countries like India, Philippines, and Eastern Europe.
Cuffe argues the agent moment unlocks the insurance industry because previous AI copilot approaches required human operators to remain in workflows, limiting automation potential and cost savings. Agentic systems operate autonomously on defined tasks, checking work against established rules, escalating exceptions to humans, and completing end-to-end processes without continuous supervision. This architectural shift transforms AI from productivity enhancement to direct labor replacement, creating compelling unit economics for insurers facing margin pressure.
The timing coincides with broader insurance industry challenges including rising claims costs, regulatory compliance burdens, and talent shortages as experienced underwriters and claims adjusters approach retirement without sufficient pipeline replacement. Insurers simultaneously face technology modernization pressures as legacy systems struggle to support digital customer experiences and real-time processing requirements. AI agents addressing operational bottlenecks while reducing costs position themselves as strategic priorities rather than discretionary technology investments.
Pace competes in an increasingly crowded insurance AI market where established players like Guidewire and Duck Creek add AI capabilities to core systems while startups including Groundcover, Benekiva, and others target specific workflows. The company differentiates through its AI-native architecture built from inception around agentic capabilities rather than retrofitting AI into existing software platforms designed for human operators.
