Insights

Knowledge for decisions.

Practical answers about building and operating AI, software and engineering systems.

01

What drives the cost of an AI project?

Cost follows scope, data readiness, integrations, evaluation, security and operating responsibility more than model choice alone.

02

AI agents versus traditional automation

Use deterministic automation for stable rules and agents for bounded ambiguity where review, tools and stop conditions are explicit.

03

Industrial IoT architecture: the practical layers

A reliable system separates devices, edge logic, connectivity, data services and operational applications, then defines failure behavior at every boundary.