Proximitty

Commercial lenders at community and regional banks, credit unions, and non-bank lenders handling C&I, CRE and SBA loans rely on manual, slow processes for document collection, financial spreading, and loan servicing. Analysts spend weeks chasing borrower documents like financial statements, rent rolls, tax returns, and debt schedules, then manually reconcile discrepancies. Legacy spreading tools are described as wrong roughly half the time, requiring heavy analyst rework, and existing platforms like nCino, Abrigo, and Moody's only document what happened rather than taking action. The page states that 2% of unserviced loans end in delinquency, pointing to servicing backlogs and lack of visibility into borrower obligations as a real cost of these manual workflows.

Proximitty offers an AI operating system that handles the full commercial loan lifecycle: document ingestion and reconciliation agents request and chase borrower documents and reconcile discrepancies in real time; credit analysis agents automate financial spreading and credit memo generation, learning edge cases and assumptions specific to each business; portfolio monitoring agents track covenants, closing requirements, and borrower obligations, escalating breaches before default; and a custom loan ops capability turns a documented procedure or screen recording into a production-ready agent without engineering resources. The system uses browser agents that operate on top of existing banking interfaces rather than requiring API integration, supporting 10+ core systems including Fiserv, FIS, Jack Henry, Finastra, Temenos, CSI, and Oracle FLEXCUBE, plus platforms like nCino, Abrigo, and Moody's. Integration is described as a three-week process (integration, sandbox testing, deploy) with no engineering lift needed. Governance is built in: every agent action is logged and reviewable, human-in-the-loop is configurable on any step, agents operate under scoped tools and policy-bound parame