MCP for the Enterprise: Governed Workflows as Tools
MCP lets enterprise buyers expose governed workflows as reusable agent tools while preserving the same policies, permissions, validation, and audit trails.
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Insights on AI for regulated industries.
Policy-driven agents, document intelligence, and enterprise automation — from the team building it.
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The 60-Day Agent Deployment, Week by Week
What actually happens in a 60-day AI agent deployment: policy encoding, document calibration, integration, audit-mode shadowing, and the evidence gates that precede production.
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Anatomy of a 99% Agent: Production Accuracy
A 99% AI agent combines deterministic execution, evidence-linked extraction, confidence routing, review gates, and closed-loop correction in production.
AI Agent Pricing Models Compared
Compare per-seat, per-token, per-task, and per-outcome AI agent pricing to see how each model allocates risk and clearly reveals the real cost per decision.
Why Voting Does Not Get AI Agents to 99%
AI agent data shows 2-vote and 3-vote majority voting reduces random errors but reaches a costly floor near 10%. Learn why deterministic execution and review perform better.
What Is a Why-Trail? Audit Trails That Explain Decisions
A why-trail connects every AI agent decision to its policy version, source evidence, evaluated data, timestamps, final outcome, human review, and overrides.
AI Agent Speed Economics: What Cycle Time Is Worth
Cycle time is a third AI agent ROI axis alongside labor and technology cost. Learn how lending, insurance, and operations can price faster turnaround.
Structured Outputs for Enterprise LLMs
Structured LLM outputs make enterprise data parseable with enforced schemas, while evidence pointers, deterministic checks, and review routing make it reliable.
What Are Policy Profiles for AI Agent Workflows?
Policy profiles let one AI workflow apply rules by jurisdiction, counterparty, or product while preserving auditability and avoiding duplicated workflows.
2026 Enterprise AI Agent Market Map
Map the five enterprise AI agent categories in 2026 and compare who builds each workflow, who owns the logic, and how execution works at runtime for buyers.
Token Economics of AI Agents in 2026
AI agent token economics depend on cost per decision: architecture controls context replay, caching value, retry costs, and whether budgets stay predictable.
What Is an Agent Compiler? Plain English to Working Agent
An agent compiler turns plain-English policies and workflows into executable AI agents: no drag and drop, no code, and every decision traced to its source.