Executive Summary (TL;DR) U.S. hospitals spend $19.7 billion a year on administrative appeals of denied claims (OIG 2023), while roughly 15 % of all initial claims are rejected (STAT 2024). Those denials jeopardise ≈ 3.3 % of net patient revenue (≈ $4.9 million per 250-bed facility). The AI Billing-Code Optimizer plugs into the Electronic Health […]
Financial institutions across the United States and Canada channel $61 billion each year into financial-crime and regulatory-compliance programs, yet non-compliance fines still land at 2.7× the cost of simply staying compliant (USA $42 B, Canada $19 B).¹ ²
The AI Financial Contract Compliance Checker steps in as a SaaS gatekeeper: it ingests loan agreements and investment contracts, flags clauses that violate Securities and Exchange Commission (SEC), Office of the Comptroller of the Currency (OCC), or Anti-Money Laundering (AML) rules, and recommends fixes before execution. Early pilots point to a 20–30 % cut in contract-review hours and a 15 % drop in regulatory findings, achieving ROI within 9–12 months.
A high-discipline execution framework for prompt and agent engineering, aligned with the IMPACT AI Product Management framework. The Impact Prompt + Agent Engineering Framework empowers AI teams to operationalize both prompt workflows and lightweight agent behaviors the way product and ML teams structure intelligent systems — with intent, metrics, and repeatability. Built for LLM-native teams deploying production-grade outputs. This framework is comprised of 8 structured stages that guide you from goal identification to agent-integrated, production-grade engineering. This is the operations layer for LLM-native systems. Build with intention. Optimize with discipline. Ship with clarity.Iterate, fork, or phase-out stale agents/prompts based on lifespan and metric performance