Most AI initiatives fail not because the technology doesn't work, but because organizations aren't ready for it. Missing governance frameworks. No observability into what models are doing. Compliance gaps that regulators will eventually find. Architecture that can't scale past the pilot.
This extends to AI-assisted software development itself. Tools like Claude Code, Cursor, and Copilot don't deliver results out of the box — they require agentic harnesses: structured memory, rules, subagents, and skills that encode your architecture decisions, coding standards, and domain knowledge. Without that foundation, AI generates plausible code that doesn't fit your system. Building the harness is the difference between AI as a novelty and AI as a force multiplier.
We fix the hard parts — from governance to the development toolchain — so your AI investment actually delivers.
Frameworks, maturity assessments, and monitoring systems that keep your AI accountable and compliant.
Enterprise AI infrastructure that scales. From agentic platforms to RAG pipelines to LLM governance.
AI-enabled software engineering across healthcare, manufacturing, defense, and enterprise. We build the systems, not just the strategy.
ISAE 3402/SOC Type 2, data governance maturity programs, and audit readiness for regulated organizations.
Legacy system decomposition, CRM evaluation, and platform migration for organizations that have outgrown their tech.
We work across regulated industries where AI decisions carry real-world consequences — healthcare, financial services, defense manufacturing, and international nonprofits.
Payers, health systems, and managed care organizations
Payments, fraud detection, and compliance automation
Production scheduling, supply chain, and DCAA-compliant systems
International organizations with complex compliance requirements
$1.6B
In payments processed
$32B
In managed subledger accounting
120+
Platform evaluations
80+
Country operations
AI absorbed the coordination work that filled middle management calendars. At the same time, AI broke the hiring pipeline that would have found the people who can actually make AI work. Both happened at once. Most engineering leaders haven't connected them.
Read more →Building a high-performing agentic engineering environment isn't about prompting — it's about encoding three things into a structured operating system: your development process, your domain model, and your technical architecture. Here's how they map to rules, subagents, memory, and the knowledge graph.
Read more →AI coding tools out of the box generate plausible code that doesn't fit your system. The difference between AI as a novelty and AI as a force multiplier is the harness — structured memory, rules, subagents, and skills that encode your architecture into AI behavior.
Read more →AI Implementation Group was founded by Carl Tierney, a technology executive with 28+ years in enterprise software spanning healthcare, financial services, and nonprofit sectors. Before consulting, Carl built a technology company from zero to a multi-tenant SaaS platform processing $1.6B+ in transactions, grew an enterprise consulting practice to 70+ professionals at Blackbaud, and collaborated with the Gates Foundation, United Nations, and WorldVision International. He holds an MBA from The Ohio State University.
More about Carl →
AI Implementation Group