From Algorithm to Geopolitical Impact: Supporting the Product Transformation of a European Leader in Defense AI

Artificial Intelligence & Data Industry & Automotive & Defense

From an expert-led organization to an impact-driven Product organization

We embedded as AI Product Managers within a European defense AI company, scaling the satellite imagery ingestion pipeline and structuring Product governance across squads. The solution is now deployed across several government institutions.

Sommaire

Context

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.

Challenges

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 ».

Our approach

01
Structuring the squad
- Took over the leadership of the Data Ingestion squad: facilitated agile ceremonies, prioritized critical topics, tracked releases, and managed delivery trade-offs.
- Defined a clear, cross-squad Product roadmap to align the data pipeline strategy with broader company goals.
02
Building an impact-driven Product approach
- Conducted technical and product discoveries to identify levers for scalability and integration of new imagery types.
- Co-created the squad vision and objectives with internal users (AI, Data, and Geospatial teams).
- Prioritized efforts based on measurable impact on algorithm performance and data reliability.
03
Embedding new Product practices
- Adapted the Shape Up methodology to improve topic preparation and streamline delivery.
- Organized cross-functional workshops with engineers and domain experts to break silos and align decision-making.
- Strengthened Product culture through knowledge sharing and adoption of outcome-driven practices.
04
Scaling governance and organization
- Supported the scaling of the Product organization: clarified ownership, optimized resource allocation, and synchronized releases across squads.
- Reinforced communication with leadership to showcase progress on strategic data and ingestion initiatives.

Our impact

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.

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From Algorithm to Geopolitical Impact: Supporting the Product Transformation of a European Leader in Defense AI

Context

Challenges

Our approach

Structuring the squad

Building an impact-driven Product approach

Embedding new Product practices

Scaling governance and organization

Our impact

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