Research & playbooks
for shipping AI in Asia.
Frameworks we use in client engagements, plus original research on AI adoption across the markets we operate in. No hype, no rehashed Western reports.
Why customer service is the right AI first project
Three reasons we keep recommending customer service automation as the first AI deployment — and one warning.
RAG vs Fine-Tuning vs Prompting: Which Pattern Fits Your Use Case?
Three deployment patterns, three sets of trade-offs. A decision tree that picks the right one for your AI use case in under five minutes.
Responsible AI in Practice: A NIST AI RMF Walkthrough for Operators
The NIST AI Risk Management Framework is the most useful free resource in responsible AI. Here is how to actually apply it in a mid-market enterprise.
Building an Internal AI Platform: Reference Architecture for 200-1,000 Person Companies
A reference architecture for an internal AI platform sized for mid-market enterprises, with the components that pay back and the components that do not.
From Pilot to Production: An MLOps Maturity Model for Mid-Market Teams
A four-stage MLOps maturity model designed for mid-market AI teams, with the practices to add at each stage and the practices to skip.
The Mentor Model: Why External AI Teams Fail Without Internal Capability Building
External AI teams that build and leave create dependency, not capability. The mentor model fixes that, with measurable handover criteria.
Shadow AI: How to Get Visibility Into the AI Your Employees Are Already Using
Your employees are already using AI tools you have not approved. Here is how to discover, catalogue, and bring shadow AI into governance without killing it.
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