Use Cases
Every decision. Every document. Every policy, enforced.
MightyBot's policy-driven AI agents handle the back-office decisions that banks, lenders, insurers, and payment processors make thousands of times a day. Pick a use case to see the agent, the inputs, and the audit trail.
Commercial · CRE · Construction
Lending
Loan underwriting
End-to-end spreading, credit memo generation, and policy-checked recommendations.
DetailsMortgage underwriting
Residential mortgage automation with condition clearing and appraisal review.
DetailsCRE lending
Commercial real estate: rent roll abstraction, DSCR, and property-level underwriting.
DetailsConstruction draw reviews
Inspection reconciliation, lien waivers, and disbursement policy checks.
DetailsCovenant monitoring
Ongoing portfolio tests: financial covenants, reporting deadlines, default tracking.
DetailsFinancial spreading
Normalize financial statements into your taxonomy automatically.
DetailsCredit risk evaluation
Apply your risk rating methodology consistently across deal flow.
DetailsLoan servicing
Modifications, waivers, and exception processing with a full audit trail.
DetailsMerchant ops · Risk
Payments
Core platform capabilities
Cross-industry
FAQ
Frequently Asked Questions
How does a use case map to a MightyBot agent?
Each use case is typically a dedicated agent with its own policies, document sources, and output schema. Multiple agents can be composed into a larger workflow, and they share the same policy engine, data engine, and execution runtime.
What does it take to stand up a new use case?
Most production use cases reach first-pass accuracy within two to four weeks. The work is primarily in encoding your policy (what "good" looks like) and pointing the agent at your document sources; the platform handles ingestion, extraction, reasoning, and audit.
Can MightyBot handle a use case not listed here?
Yes. The platform is use-case-agnostic — any regulated decision workflow that requires reading documents, applying policy, and producing auditable output is a candidate. Listed use cases reflect the strongest customer patterns today.
Do I need to retrain a model for my use case?
No. MightyBot is a policy-driven platform, not a model-training workflow. You provide the policy; the platform applies it using frontier LLMs plus deterministic execution paths. No custom fine-tuning is required for most workflows.
See your use case run in production.
We'll demo with your documents and your policy, not a sanitized dataset.