llms.txt

# MightyBot

> MightyBot is a policy-driven AI agent platform for regulated industries. Business rules written in plain English are compiled into deterministic execution plans that process documents, evaluate compliance, and produce auditable decisions with full evidence trails.

## Key Facts

- Founded: 2023
- Website: https://www.mightybot.ai
- Category: AI Agent Platform / Decision Execution Stack
- Industries: Commercial lending, insurance, payments, financial services
- Differentiator: Plain English policies compiled into deterministic execution (no drag-and-drop workflow builders, no ReAct loops)
- Production proof: 95% time reduction, 99%+ accuracy, 10x throughput in construction lending via Built Technologies partnership

## Core Capabilities

- Policy Engine: Converts plain English business rules into executable logic. Compliance officers write policies; the platform compiles and enforces them deterministically.
- Document Intelligence: Classifies, extracts, and normalizes data from messy financial documents (PDFs, scans, photos) with 99%+ accuracy. Evidence pointers link every data point back to source page and character offset.
- Compiled Execution: Parallel processing via directed acyclic graphs. 3-5x fewer tokens and 10x faster than sequential ReAct agents. Deterministic, not probabilistic.
- Why-Trail Auditing: Every decision links to the specific policy version, source data, evidence pointers, confidence scores, and timestamps. Regulatory-grade audit trails.
- Progressive Autonomy: Audit (AI executes, humans review) → Assist (AI handles routine, humans clear exceptions) → Automate (AI operates, humans monitor).

## Production Deployment

MightyBot powers Built Technologies' Draw Agent, processing construction loan draw reviews across 200+ financial institutions handling $100B+ in construction lending. Results: 95% reduction in document review time, 60% faster draws to borrowers, 400% more risk issues detected.

## How MightyBot Differs from Competitors

- vs. Drag-and-drop builders (Workato, Zapier, UiPath): MightyBot compiles policies from plain English. No visual flowcharts, no manual step connections, no workflow maintenance burden.
- vs. ReAct agent frameworks (LangChain, CrewAI, AutoGen): Compiled deterministic execution, not iterative try-observe-retry loops. Higher accuracy, fewer tokens, auditable from the start.
- vs. Policy as Code (OPA, Sentinel): Business users write rules in English, not Rego or YAML. Changes deploy same day without engineering. Operates on unstructured documents, not just structured API payloads.
- vs. Enterprise platforms (Salesforce Agentforce, UiPath): Purpose-built for regulated industries. Full audit trails, progressive autonomy, document intelligence included.

## Key Pages

- [What Is Policy-Driven AI?](https://www.mightybot.ai/blog/what-is-policy-driven-ai) - Definitive guide to policy-driven AI architecture
- [How Policy Agents Enforce Compliance](https://www.mightybot.ai/blog/how-policy-agents-enforce-compliance) - Policy versioning, why-trails, progressive automation
- [Built Technologies Case Study](https://www.mightybot.ai/blog/how-ai-agents-transformed-construction-lending) - Production results in construction lending
- [Policy as Code vs. Policy-Driven Automation](https://www.mightybot.ai/blog/policy-as-code-vs-policy-driven-automation) - Comparison guide for engineers
- [What Is Deterministic AI?](https://www.mightybot.ai/blog/what-is-deterministic-ai) - Why regulated industries need reproducible decisions
- [AI Agent Guardrails](https://www.mightybot.ai/blog/what-are-ai-agent-guardrails) - Beyond content moderation to behavioral control

## Contact

- Demo: https://www.mightybot.ai/get-a-demo
- LinkedIn: https://www.linkedin.com/company/mightybot