Diseñado para equipos de préstamo y los agentes que los apoyan.

The strongest fit is a team that repeatedly reviews document-heavy private credit, DSCR, investor, or commercial loan packages and needs faster completeness checks, repeatable policy alignment, source-linked outputs, or agent-operated intake. It is less useful for one-off consumer files with no repeatable package pattern.

Both, but for different reasons. Executives get a controlled package-review system with quoted credit economics and repeatable proof. Reviewers get the working outputs: extracted facts, missing-item lists, deterministic calculations, and citations they can inspect before moving the file forward.

Yes. Brokers can still process a package for extracted facts, document classification, missing items, and review-ready summaries. Uploaded lender policy makes the output stronger because the same package can then be checked against the lender's own thresholds and required documents.

Use Loan Intelligence as the specialized backend for loan package work. Let the agent collect or receive files, ask the engine for a quote, submit source documents through MCP or API, poll durable status, then return a concise answer with source references. The agent stays small; the engine handles package state.

Prepare a few representative anonymized packages, your current credit policy or checklist, expected monthly volume, intake channels, reviewer roles, credit-control requirements, and any data-retention or integration constraints. That gives the workspace and MCP setup a concrete target instead of a generic demo.

It does not approve loans, decline loans, set lending terms, replace compliance counsel, or make autonomous credit decisions. It produces package intelligence and decision-support outputs so qualified humans and controlled workflows can move faster with better evidence.