Blog & Insights
Best practices, technical deep-dives, and lessons learned from real-world AI deployments.
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RSSAI Implementation Best Practices: From Pilot to Production
A practical checklist to deliver AI projects end-to-end: scope, data readiness, evaluation, rollout, and operations.
MLOps in Production: A Practical Guide to Scaling AI Systems
An end-to-end overview of MLOps: versioning, deployment, monitoring, and continuous improvement.
Latest articles
Computer Vision in Manufacturing: Practical Quality Inspection
A practical approach to vision-based inspection: data collection, labeling, evaluation, and deployment considerations.
LLM for Thai: Practical Optimization & Evaluation
Thai tokenization, spacing, retrieval quality, and evaluation pitfalls—plus practical tips.
Measuring AI ROI: Beyond Technical Metrics
How to measure and communicate business value of AI investments to stakeholders and executives.
Edge AI Deployment: Bringing Intelligence to the Edge
Deploying AI at the edge: hardware constraints, latency, privacy, connectivity, and optimization techniques.
RAG in Production: A Practical Playbook
A set of practical practices for RAG: data governance, evaluation, regression tests, and safe rollout.
PDPA/GDPR for AI Projects: Operational Checklist
A practical alignment checklist for Legal/Compliance and Engineering (not legal advice).
Fine-tuning vs RAG: How to Choose (Practical Criteria)
Decision criteria: data quality, update frequency, cost, latency, and governance constraints.
AI-SPC: Practical Guide for Manufacturing Teams
How to add AI-assisted SPC in real lines: data, thresholds, false alarms, and rollout steps.
Incident Response for AI Systems: A Practical Runbook
Runbooks, alerting, and triage patterns for AI incidents: data, model, infra, and product behaviors.
Selecting an AI Vendor: A Practical Scorecard
How to compare vendors by delivery risk, security posture, cost, and long-term maintainability.