Harper raises $47m to modernise business insurance with AI
February 26, 2026 - Harper, an AI-powered commercial insurance brokerage, has raised $47m across seed and Series A. The round was led by Emergence Capital, with participation from Y Combinator, Peak XV, Antler, 10X Founders, Fellows Fund, and Outset Capital.
Harper notes its Series A is the largest publicly disclosed Series A raised by a Black founder. The signal is clear: AI-native distribution is moving fast, and expectations on speed, accuracy, and broker-carrier collaboration are about to rise.
What Harper automates
- Reads and interprets applications and supplemental documents.
- Routes submissions to optimal markets based on appetite and capacity.
- Manages quotes, follow-ups, and broker-underwriter coordination.
- Claims to deliver bindable coverage within 24 to 48 hours.
Traction at a glance
- Active with 165+ underwriters.
- Serving manufacturing, healthcare, hospitality, transportation, and construction.
- 5,000+ businesses served in 13 months.
Focus: complex risks with real operating impact
Harper targets placements where delays stall operations: daycares that can't open without coverage; logistics firms that can't onboard drivers on time. Speed and precision at submission, triage, and bind directly affect cash flow and customer satisfaction.
Use of funds
- Grow engineering, account management, and operations teams.
- Deepen carrier relationships via direct appointments and expanded programs.
- Advance AI infrastructure for scale, accuracy, and compliance.
Why this matters for carriers, MGAs, and brokers
- Speed becomes table stakes: 24-48 hour placement cycles will reset client expectations.
- Data-first submissions: Clean, structured intake will win over email-and-PDF sprawl.
- Appetite clarity: Up-to-date appetite maps and real-time capacity signals reduce wasted touches.
- Underwriter leverage: Automation shifts human effort to judgment calls, referrals, and program design.
- Distribution shift: AI-native brokers will favor carriers with APIs, fast endorsements, and predictable SLAs.
- Compliance pressure: Audit trails, explainability, and model governance move from "nice" to "necessary."
What to do next (practical steps for the next quarter)
- Standardise intake: adopt structured fields for ACORD and common supplements; add OCR + entity extraction for unstructured docs.
- Expose key endpoints: appetite lookup, submission intake, quote, bind, endorsements, loss runs, and status webhooks.
- Triage rules: codify eligibility, referral criteria, and priority scoring so automation routes cleanly to the right desk.
- Quote discipline: guarantee response windows and fallback quotes to avoid stall-outs on complex risks.
- Underwriting controls: maintain bind authorities, referral workflows, and audit logs that are easy to review.
- Data contracts: agree on schemas, UW questions, and change management with top distribution partners.
- Program strategy: identify niches where speed + certainty let you price for service and win persistency.
Context for insurance teams
This raise accelerates a brokerage model built on automation-first workflows. If your placement cycle relies on manual email threads and PDF gymnastics, you'll feel the gap quickly-both in conversion and in broker preference.
The carriers and MGAs that win here will be the ones that remove friction, document their rules, and meet brokers where they work: APIs, clear SLAs, and rapid referrals.
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