Brelly - 2026 Pricing, Features, Reviews & Alternatives

Brelly is a cloud-based AI-powered claims workspace designed for property insurance claims across residential and commercial loss types, including wind, hail, hurricane, fire, and water damage. The platform consolidates policies, estimates, contacts, documents, emails, and photos into a single structured claim record, then applies AI to help users organize, analyze, and act on that information. All AI-generated outputs are subject to user review before any external action is taken, preserving professional judgment throughout the workflow.

Built for public adjusters (solo practitioners, scaling firms, and full firms), licensed insurance professionals, contractors, and policyholders such as homeowners and business owners, Brelly addresses the full lifecycle of a property damage claim. Core capabilities include AI-assisted drafting of carrier-ready communications and letters grounded in claim-specific facts, line-item estimate comparison that surfaces discrepancies across multiple estimates, and policy interpretation that translates complex insurance language into plain English. A timestamped document and communication timeline provides an audit-ready log of every event, submission, and update. Risk flagging detects inconsistencies, identifies missing documentation, and highlights risky language in outgoing communications before it reaches carriers or opposing parties.

Brelly integrates with existing systems where teams manage email, documents, photos, schedules, and customer records, reducing the need to switch between tools. Compliance alignment maps claim activity against policy terms, state statutes, and applicable laws. Policyholder-facing guidance supports coverage term comprehension, claim progress tracking, and compilation of ALE reports or out-of-pocket expense records. Claim summary reports condense the full claim into a shareable snapshot for stakeholders. The platform also supports faster onboarding of new adjusters by providing access to templates, standard operating procedures, and historical claim data.