What Mulligan users actually want

14 sources cite submission acceleration as high-severity, and 3 sources specifically identify back-and-forth with carriers due to incomplete or incorrectly formatted submissions as the root cause of delays. Underwriters process Mulligan AI submissions faster (cited in 4 sources), suggesting validation quality directly impacts competitive advantage. One source quantifies the shift from hours to minutes, but incomplete submissions negate that gain by triggering rework cycles.

9 sources cite proposal generation as high-severity, with the current manual process taking hours or days and creating significant productivity drag for producers and account managers. One source quantifies the target as 3-5 minutes, a 95%+ reduction that directly impacts sales velocity. Producers are one of three core personas, and their primary job is closing deals. Hours spent assembling proposals from scattered sources (quotes, policies, binders) delays closure and limits volume.

11 sources cite data accuracy and verification as critical, and 2 sources explicitly identify deficiency detection (missing coverages, gaps, incorrect limits) as a workflow need. 9 sources highlight policy complexity as a barrier to client communication. Sample documents show dozens of coverage options, sublimits, and state-specific variations that brokers must explain manually. One source notes policies are subject to provisions, limitations, and exclusions that require careful review to avoid miscommunication.

5 sources cite carrier expansion as medium-severity but note 1-2 new carrier and LOB combinations added monthly as a competitive differentiator. The platform serves independent agencies, mid-size to large brokerages, MGAs, and wholesalers, creating diverse coverage needs. One source emphasizes the product already covers GL, BOP, WC, Commercial Auto, and Trucking with the largest carrier coverage in the industry, suggesting breadth is a retention driver.

6 sources cite multi-format document handling as high-severity, with Excel, CSV, and AMS-native export flexibility directly reducing manual reformatting. One source explicitly identifies formatting errors when importing commission data to AMS as a friction point that introduces risk and rework. The product already integrates with major AMS platforms (Applied Epic, EZLynx, AMS360, Veruna), but integration without native export forces users to manually reformat extracted data before import.

6 sources cite data quality and document integrity as medium-severity, with one source explicitly identifying audit trail requirements for compliance and regulatory auditing. Commission processing involves financial data that agencies must track for internal and external audits, and submissions to carriers create legal obligations around accuracy and completeness. Manual workflows cited in 24 sources lack systematic logging, exposing agencies to compliance risk if they can't reconstruct how data was processed or who made changes.

2 sources cite multi-persona support as medium-severity, identifying Producers (sales opportunities), Account Managers (comparisons and proposals), and Customer Success as distinct user types with different workflow needs. The product automates multiple workflows (commission processing, submissions, proposal generation, policy analysis), but without role-specific interfaces, users navigate generic dashboards that don't prioritize their primary tasks. Producers need fast proposal generation to close deals, Account Managers need side-by-side policy comparisons, and Customer Success needs deficiency detection to prevent churn.