AI Agent Policy Engine: Policy Management and Enforcement
A policy engine turns plain-English business rules into versioned, enforced logic for AI agents. How policy management and enforcement work, with an example.
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Policy-driven agents, document intelligence, and enterprise automation — from the team building it.
96 articles
A policy engine turns plain-English business rules into versioned, enforced logic for AI agents. How policy management and enforcement work, with an example.
Policy as code governs infrastructure checkpoints, while policy-driven automation compiles plain English business rules into auditable, end-to-end workflows.
How MightyBot moved agentic AI from demos to production infrastructure with policy execution, document processing, feedback, and progressive automation.
Control AI hallucinations in enterprise workflows with source evidence, structured extraction, policy validation, human review, and complete audit trails.
Built's Draw Agent automates construction loan draw review with 99%+ accuracy, 95% less review time, and 400% more compliance risks detected than manual review.
Built Technologies and MightyBot shipped Draw Agent by wrapping AI around existing systems, using daily feedback loops and a phased production rollout.
Enterprise AI adoption works when teams choose a measurable workflow, govern the agent, connect real data, start with human review, and scale after proof.
PhD-level AI agents can reason across complex tasks, but business value depends on context, tools, policies, evaluation, supervision, and workflow reliability.
Why AI agents fail without context, and how retrieval, tools, memory, policies, permissions, evals, and audit trails make production systems reliable.
AI agents reshape work by automating research, document processing, follow-up, monitoring, and policy checks while people retain judgment and accountability.
What makes an AI agent in 2026? The nine capabilities that separate real production agents from chatbots, copilots, RPA bots, and workflow automations.
MightyBot's 2024 journey moved from early integrations to meeting, search, sales, and workflow agents, shaped by beta feedback and rapid product releases.