AI Insurance Brokerage Harper Raises $47M
Harper, an AI-native insurance brokerage, has raised a combined $47 million in seed and Series A funding. The company fully automates insurance workflows, including submission routing and document collection, enabling it to process deals in 1-2 days versus the industry standard of 5-7. The platform handles over 1,000 customers monthly, demonstrating a scalable model for verticalized agent orchestration.
- The founding team combines deep industry knowledge with technical expertise; CEO Dakotah Rice comes from a family of insurance brokers, while CTO Tushar Nair previously led ML/AI engineering teams at Goldman Sachs. - The $47M funding round was led by Emergence Capital, a firm with a track record in backing workflow automation leaders in regulated markets, with participation from Y Combinator and Peak XV Partners, bringing Harper's total funding to approximately $54 million. - Harper's system operates as a multi-agent workflow where AI handles discrete tasks: it ingests client data, normalizes it against the appetites of over 160 carriers, auto-populates submission forms, and manages follow-ups with underwriters. - The company deliberately chose to become a fully-licensed brokerage rather than selling software to existing agencies, allowing for greater control over product development and speed, aiming for software-like margins on traditionally manual work. - This model reflects a broader trend in insurance of using multi-agent systems (MAS), where separate AI agents autonomously manage specific sub-tasks like data intake, risk profiling, fraud detection, and customer communication to automate complex end-to-end processes. - To scale its systems, Harper employs a unique "Future AI Founder" role where individuals first embed within operations to manually handle sales and service requests, documenting every edge case before helping to design the automated systems that will replace their manual work. - In China, the AI insurance landscape is mature, with giants like Ping An and ZhongAn embedding AI across the value chain and regulators like the CBIRC providing clear guidelines for AI development, fostering a mobile-first, ecosystem-driven market. - Chinese insurers are rapidly adopting Large Language Models (LLMs), with over 60% having an LLM application in production; a majority (71%) co-develop solutions with tech partners, and the open-source DeepSeek model is a dominant choice for in-house development.
