In this episode I caught up with Ash Alex and Jimin Seo, co-founders of Hyades, to discuss BlazerOps, an agentic platform for building machine-learning models and pipelines for geospatial data. They explain how the platform aims to make spatial ML faster and more accessible, helping engineers automate complex workflows while enabling analysts to define objectives in plain English. We discuss how geospatial agents differ from conventional LLM and coding-agent workflows, why spatial data requires specialist tools, and how multiple agents can coordinate data inspection, preprocessing, model development, and evaluation.
A major focus is how BlazerOps combines general-purpose language models with specialist geospatial models and curated technical knowledge. Ash and Jimin describe their in-house foundation model for spectral imagery and explain why geospatial applications may require a toolkit of specialist models rather than a single universal “supermodel.” We also discuss embeddings, fine-tuning, bespoke architectures, organisational knowledge, and how agentic development could free ML engineers and researchers to focus on more advanced work.
Jimin Seo leads operations and global partnerships at Hyades, with a background in commerce and law, and passion for designing and delivering software solutions. He works closely with the technical team to translate organization-level data, privacy, IP and trustability requirements into a trustable, personal and powerful platform to enable spatial ML development for everyone.
Ash Alex is the CEO of Hyades. Coming from a physics background, Ash has experience designing optical communications systems for commercial satellites at the University of Auckland, Cornell, and NASA’s Decadal Survey Program, where he was exposed to the complexities of working with geospatial data. His mission is to embed spatial insights everywhere.
