5 Questions to Ask Before Buying an AI Agent Platform
Most AI agent platforms demo well and deploy poorly. These five questions separate platforms that work in production from platforms that only work in presentations.
Blog
Policy-driven agents, document intelligence, and enterprise automation — from the team building it.
69 articles
Most AI agent platforms demo well and deploy poorly. These five questions separate platforms that work in production from platforms that only work in presentations.
Agentic process automation (APA) uses AI agents to execute workflows requiring judgment and adaptation — replacing rigid RPA scripts. Learn how APA works in financial services.
An AI agent audit trail links every automated decision to the specific rule that governed it, the data that informed it, and the evidence that supported it.
Gartner predicts 40%+ of agentic AI projects will fail by 2027. This playbook covers the four-step on-ramp, policy-first design, and the 60-day path from kickoff to production.
Policy-driven automation in financial services converts lending policies, compliance rules, and regulatory requirements into executable logic that AI agents enforce consistently with full audit trails.
AI governance has shifted from policy documents to executable infrastructure. Only 25% of organizations fully govern AI, yet governance makes projects 3.4x more effective. Here is what works.
Most AI ROI claims in financial services fail scrutiny. A practitioner framework for measuring what matters: four metrics, production data showing 5-10x returns, and the benchmarks that hold up.
Deterministic policy enforcement means every AI agent decision follows the same rules, produces the same output for the same input, and generates the same audit trail. For regulated industries, this is a prerequisite.
How AI agents automate construction loan draw processing with document intelligence, policy checks, evidence trails, and human oversight. Built Technologies and MightyBot achieved 99%+ accuracy, 95% time reduction, and 10x throughput.
ReAct agents reason iteratively at runtime: observe, think, act, repeat. Policy-driven agents compile business rules into execution plans before runtime, producing more predictable outcomes, lower cost variance, and stronger audit trails.
Policy-driven AI turns business rules, evidence requirements, and human oversight into executable agent workflows. Learn why it is the missing layer between enterprise AI pilots and production deployment.
A 2026 AI agents market map for enterprise buyers: coding agents, workflow agents, vertical agents, agent infrastructure, agent washing, and how to evaluate production-ready platforms.