From Pilot to Production: A Blueprint for Scaling Edge AI

As enterprises push AI beyond the data center, the gap between a successful pilot and a production deployment at scale has become the defining challenge of edge computing. Most edge AI projects don’t fail in the lab, they fail in the field, where connectivity is unreliable, environments are harsh, and sending a technician to every site isn’t an option.

This white paper, developed in partnership with OnLogic [link to website], provides a practical blueprint for IT and OT leaders ready to move from experimentation to full-scale edge AI operations. It examines why traditional cloud architectures break down at the edge, the foundational hardware and software decisions required to prevent failure, and how purpose-built hardware combined with autonomous orchestration from ZEDEDA enables deployments that scale.

Topics include:

• Where and why edge AI deployments break down
• The architectural decisions that prevent failure
• Hardware requirements for real-world edge inference
• Autonomous orchestration: zero-touch provisioning, zero-trust security, and workload management at scale
• Real-world orchestration examples across energy, renewable, and automotive
• The Field-Ready Edge AI Evaluation Questionnaire
• The full-stack solution: OnLogic powered by ZEDEDA