Case study

Turning a Fragmented Topic Into Five Usable Architecture Patterns

An architecture guide that organized the scattered field of disconnected edge AI into five named, comparable patterns engineers could design against.

Client: Actian

The brief: Actian wanted to reach engineers building AI for places where cloud connectivity cannot be assumed, like mining, offshore energy, manufacturing, and defense, and to establish authority on edge and offline-first data architecture.
The challenge: Edge AI for disconnected environments is real but fragmented: the patterns are spread across separate industries and rarely named or compared. The piece had to make the space concrete without a cloud fallback to lean on, and stay useful to an architect rather than drifting into abstraction.
The approach: Researched how inference and control actually run offline across those industries, then distilled the field into five distinct patterns (the Drone, the Factory, Hierarchical Federated Learning, Store-and-Forward, and the Network), each with its constraints, trade-offs, and the situations it fits.
The work: A long-form architecture guide on Actian's developer blog, structured so a reader can match their own connectivity and data-sovereignty constraints to a pattern.
The outcome: Published on Actian's developer blog, where it ranks number one in search for the "edge AI architecture" keyword.
What this demonstrates: Synthesis of a fragmented topic into an original, usable framework, and architecture-level technical writing for a specialist engineering audience.

Need this kind of content? Hire me →