Draw reviews at scale
Packages ingested, classified, policy-evaluated, delivered as finished reviews
Industries
Commercial Lending Automation with AI Agents
MightyBot automates the full commercial lending lifecycle. Draw reviews that broke automation for 30 years now run at $100B+ scale. 83% of lenders increasing GenAI budgets in 2026. 70% faster. 99% less time on task.
Why MightyBot
MightyBot automates the full commercial lending lifecycle: underwriting, draw reviews, covenant monitoring, servicing. 83% of lenders increasing GenAI budgets in 2026 (MBA survey). Draw reviews broke every automation tool for 30 years. MightyBot runs them across many institutions through Built Technologies, processing $100B+ in construction lending. 70%+ faster. 10x throughput. Ready for FinCEN's April 2026 effectiveness-based AML framework.
The agents read borrower, collateral, construction, covenant, and policy documents; apply lender rules; route exceptions to reviewers; and produce evidence-backed outputs for underwriting, draw reviews, servicing, and portfolio monitoring.
The Workflow That Broke Everything
Construction draw reviews defeated automation for three decades. A single package: inspection photos, invoices, lien waivers, budget reconciliations, change orders. Every document in a different format from a different party. Rule-based systems broke on variability. Generic AI hallucinated numbers. Hours per draw. Days to fund. Draw automation is now table stakes. The question is execution quality, audit trails, and policy enforcement.
Five capabilities.
One execution engine.
Parallel underwriting
Credit, collateral, cash flow, guarantor strength analyzed simultaneously
Covenant monitoring
Continuous portfolio-wide tracking of covenants and obligations
Financial statement spreading
Normalization, ratio calculation, trend analysis across periods
Same-day policy deployment
Plain English rules, deployed today
Production Results
Production numbers from real institutions.
USE CASES
Every commercial lending workflow. Automated
Industry workflow map
How commercial lending automation works in MightyBot
MightyBot automates commercial lending work by reading complex borrower, collateral, construction, and policy documents, applying lender rules, and producing evidence-backed review packages for underwriting, draws, covenants, and servicing.
Last updated: April 24, 2026| Inputs | Borrower packages, financial statements, budgets, appraisals, inspections, lien waivers, loan policies, covenants, and servicing records. |
|---|---|
| Execution | Agents spread financials, evaluate collateral and policy tests, compare draw evidence, monitor covenant obligations, and escalate exceptions with context. |
| Outputs | Draw-review findings, credit memo inputs, covenant exceptions, servicing tasks, ratios, policy flags, and lender-ready summaries. |
| Audit trail | Each finding retains the source file, clause, amount, calculation, policy rule, confidence signal, and reviewer action. |
| Best for | Commercial lenders that need more throughput from lean credit, construction lending, loan administration, and portfolio teams. |
See draw reviews in production.
Real packages, real policies, institutional scale. Not a demo. In production.
FAQ
Frequently Asked Questions
What makes construction draw reviews so hard to automate?
Extreme document variability from different parties. Photo evidence must match construction schedules. Cross-document validation where every line item must reconcile. Every other tool broke on at least one of these.
How does the Built Technologies integration work?
MightyBot is the execution layer within Built's platform — classification, extraction, photo analysis, policy evaluation. Built handles orchestration and lender experience. 200+ institutions. The integration is the product.
Can MightyBot enforce our institution's specific policies?
Policies defined in plain English — LTV thresholds, DSCR minimums, documentation requirements. 200+ pre-built policies ship out of the box. Your credit team modifies directly. No engineering required.
What happens with edge cases?
Edge cases handled. Configurable confidence thresholds per policy. Every routed item includes full analysis context and specific reason for flagging. Reviewers decide in minutes, not hours.
How quickly can we go live?
Weeks, not months. Start with one workflow — typically draw reviews or underwriting. Pre-built policy library covers common commercial lending workflows. No multi-year implementation.
How does MightyBot handle document variability?
Documents arrive in whatever format — PDFs, scans, spreadsheets, digital forms. Classified, extracted, and indexed automatically. A financial statement on page 47 of a loan package gets identified and surfaced. No upstream standardization.