From Algorithm to Geopolitical Impact 

In a sector where data and artificial intelligence redefine operational capabilities, a European leader in defense and aerospace AI partnered with Thiga to scale its most strategic products.

The company develops solutions for analyzing satellite imagery and complex signals, enabling the automatic detection of military assets from multisource data. Faced with rapid growth and exponentially expanding data volumes, it needed to strengthen product scalability and structure its product governance to sustain long-term innovation.

Thiga’s mission focused on AI Product Management: enhancing data pipeline performance and embedding a value-driven product approach within an organization historically rooted in engineering excellence. The goal: combine technological rigor, operational reliability, and product vision to help the company reach a new level of data and AI maturity.

Master a highly technical and sensitive product

Operate in an environment combining AI algorithms, data pipelines, and high-security software integration, requiring constant alignment between geospatial engineers, AI experts, and backend developers.

Engage with end users under strict confidentiality 

Since clients were mainly governmental and military institutions, direct feedback collection was often impossible. This constraint required rethinking validation methods and feature prioritization.

Handle exponential data growth

The surge in satellite imagery, a true “data tsunami”, called for a complete redesign of the ingestion pipeline and clearer data governance to ensure scalability and prepare for new data types.

Support organizational scaling

As the company transitioned from expert teams to a product organization, synchronization between squads became critical, requiring streamlined prioritization, smoother communication, and a shift from “outputs” to “outcomes.”

• Increased scalability of the data ingestion pipeline: significantly improved capacity to process and store massive volumes of satellite imagery across formats.
• Enhanced reliability and industrialization of data flows: successfully prepared for the integration of new data sources and sensors.
• Improved delivery performance: greater release predictability and proactive management of delays and priorities.
• Strengthened product culture in a technical environment: closer collaboration between data, AI, and product teams.
• International recognition of the solution: product now deployed across several ministries and government institutions, demonstrating both technical robustness and organizational maturity.