Field Reports and Decision Frameworks

Implementation field reports, architecture notes and practical evaluation frameworks. Each report states its evidence and limitations. Worksheets and proposed protocols are labeled explicitly.

Implementation and architecture field reports

• Intent-aware retrieval for enterprise RAG: lessons and the data it produces
• Calibrating AI graders: what we learned and what the scores reveal
• Turning customer conversations into countable data: what we learned
• Approved and generated answers: the data a two-tier help assistant can give you
• The production gap: lessons from seven AI workstream records
• What a voice AI platform's data shows, and when to bring it in-house
• Rebuild or tune? A decision framework for stalled AI systems

Decision frameworks and working templates

• AI Adoption in Atlanta: A Practical Evaluation Guide
• AI investment evaluation: compare automation, analytics and assistants
• Legacy technology decisions: what to measure before replacing a system
• AI model evaluation guide: beyond the legacy Multiplier-X1 overview
• AI readiness worksheet: evidence to gather before a pilot
• Operational bottlenecks: find the constraint before choosing a fix
• Human and AI-assisted decision comparison: a prospective worksheet
• The full cost of AI implementation: a planning guide

Bring the workflow, systems, accountable owner and acceptance evidence to a project review, or read how we scope delivery.