Enterprise AI Production OS

Summary

Ran Full Productionization across all seven units on the customer-support agent. Current Production Readiness Score:

41/100. Clear go/no-go recommendation with conditions, board-ready ROI model, and prioritized remediation backlog.

Unit 1 – Use-Case Triage & ROI Modeling

ROI Model (annual)

• Expected benefit: $1.85 M (ticket deflection + agent productivity)
• Expected cost: $420 k (inference + ops + monitoring)
• Payback: 3.1 months
• Confidence: Medium (data quality is the main risk)

Recommendation: Conditional GO — only after data readiness and evaluation gates are met.

Unit 2 – Data Readiness Score: 38/100

Critical gaps: knowledge-base freshness, ticket context richness, PII handling.
Top remediation items ranked by impact/effort included.

Unit 3 – Agent Reliability

Current critical-path success: 62%. Production gate set at ≥ 88% with max 2% critical failures. Failure-mode analysis and improvement backlog delivered.

Units 4–7

Governance control matrix, canary rollout plan, Day-2 SLOs + cost guardrails, and executive memo ready for the board.

Production Readiness Score: 41/100

Top 3 actions that raise the score fastest

1. Close the three highest-impact data gaps (raises score ~18 points)
2. Implement the golden + adversarial evaluation suite and hit the 88% gate (raises score ~15 points)
3. Add human-in-the-loop on high-risk ticket categories + full logging (raises score ~12 points)

Next steps

• Approve the conditional GO and fund the 6-week remediation sprint
• Assign owners to the top 3 actions
• Schedule board review using the executive memo produced in Unit 7