Flood is the largest uninsured peril in US property: mispriced, under-distributed, and overdue for modern tools. We're the AI-native flood specialist built to close that gap, with underwriting, distribution, and oversight on a single platform.
waterbearAI
How can I help you with flood insurance today?
Why it matters
Insurance is the first layer of defense.
Accurate flood pricing does more than close the protection gap. When we can see, for every building, the true cost of its risk, property owners, lenders, and regulators gain a reason to act, to elevate, retrofit, and build to a higher standard. Priced right, insurance becomes the signal that makes the built environment more resilient. Getting that price right is where the hard part begins.
The problem
The same structural gaps show up on every side of the transaction: the property owner buying coverage, the agent placing it, and the carrier backing it.
Most flood-prone properties sit outside the official flood zones. The ones inside are watching NFIP premiums climb under Risk Rating 2.0. Either way, the coverage rarely matches the actual risk at the building.
Flood is the hardest coverage to quote accurately and the easiest to skip. The tools available make it slow and uncertain. Agents need flood to be as easy to quote and bind as any other line.
Private flood is a $20B+ market growing 20%+ a year, but deploying capital into it takes underwriting infrastructure most platforms don't offer: building-level pricing, real-time accumulation controls, and transparent loss analytics.
One gap. Three problems to solve at once.
Property owners need the right coverage, agents need it to be easy, and carriers need infrastructure they can trust. To close the flood protection gap, you have to solve for all three.
This is the reality. A flood map tells you where water is expected. Decades of recorded losses tell you where buildings actually flood, and the two diverge sharply: most catastrophic losses land in zones the official map calls low risk. Pricing that correctly takes more than history. It takes historic losses combined with topographic, hydrographic, and geographic corrections, feeding stochastic models tuned for the perils that drive the damage, storm surge and fluvial (stream) flooding. That combination is the hard part, and it is exactly what building-level pricing requires.
What we do
Four capabilities, built as one system, to get the right flood protection to the right property at the right price.
Componential pricing at the structure, calibrated on recorded loss. Historic losses combined with topographic, hydrographic, and geographic corrections, feeding stochastic models tuned for storm surge and fluvial flooding.
Flood coverage (standalone private flood, excess above NFIP, and parametric) matched to the risk at each building. Broader in breadth and depth than NFIP.
Quote-to-bind in minutes through APIs, an agent portal, or existing workflows. Built to meet agents and property owners where they already are.
Most insurers are a black box: a price, a yes or no, and little else. We show agents and property owners how we got there, from risk segmentation to pricing to claims. Reasoning in the open builds confidence and accountability on both sides.
How we operate
Flood insurance lives under constant review by capacity partners and regulators. We built Waterbear as one system, so decisions are explainable, overrides logged and handoffs defensible.
One connected system.
Distribution, risk analysis, and operations share one architecture, so signals captured at quote time flow straight into pricing and coverage decisions.
Decisions carry their rationale.
Physics-based stochastic modeling. Any decision traces back to the signals and models that produced it.
Automation with accountable handoffs.
Automation handles the routine cases. Specialists own the edge cases and the judgment calls. Handoffs are logged and auditable.
Coverage
Three lines of flood coverage, each built to fit the risk at the individual building and to go beyond what NFIP provides.
Primary flood protection, matched to the building.
Extra limit on top of NFIP or a primary policy.
Index-triggered coverage for fast recovery.
Inside the platform
Dedicated interfaces for the three personas who move the book - insurance specialists, agents in the field, and the customers they serve. One connected workflow. A supervising AI directs specialized agents for each step, with actions logged, attributable, and reversible.
A one-stop workspace (command center, portfolio analysis and agent performance) with an AI agent that answers anything across the book, surfaces risk concentrations, and recommends actions on individual or bulk cases.
Request full preview →Live book overview, customer search, bulk CSV quoting, area-tier risk lookups, and commission tracking in one place. Concentration and pricing anomalies flagged across the portfolio. One agent scales to hundreds of renewals.
Request full preview →A chat-first surface your customers use to represent their own property facts, explore flood risk by address, and review coverage in plain language. The insured owns the record, so there's less back-and-forth for the agent and a cleaner audit trail that helps reduce E&O exposure.
Request full preview →waterbearLeadership
Veteran operators from the insurance and built-environment industries, with deep expertise across flood risk modeling, program design, distribution, and AI-native insurance operations.
Insights
Cat-exposed specialty insurance needs three supervised loops feeding a single audit trail. The integration is the product, and audit-trail-first design is what makes the architecture deployable for capacity partners, operators of existing flood programs backed by third-party capacity, and regulators.
Read →The capital to close the protection gap is there. The problem is distribution design: quoting workflows assume agents are underwriters. Move the risk intelligence into the platform, and the agent never has to carry it.
Read →Contact
Whether you're looking for distribution, partnership, or deploying capacity, we'd like to hear from you.
