GRDF
Generative AI embedded into quality engineering at scale.
The Challenge:
GRDF's delivery teams maintain software that millions of households depend on, where every release must meet strict reliability requirements. Regression testing had become the bottleneck: suites grew faster than teams could maintain them, and manual triage consumed engineering time. Our squad combined LLM engineering, quality expertise, and data engineering to turn testing from a bottleneck into an accelerator.
We managed every stage of the engagement, from the initial AI opportunity audit and architecture blueprint to development, evaluation, and production rollout. Our goal was to deliver a platform GRDF's teams could own, evolve, and trust as their systems grow.
Client Goals
- Reliable Critical Systems – Keep the software behind France's gas distribution network reliable while accelerating releases.
- AI-Augmented Quality – Embed generative AI into test generation, defect triage, and regression analysis at scale.
- Autonomous Internal Teams – Transfer AI engineering skills so GRDF's teams own and evolve the platform durably.
Key Services Provided
- GenAI Engineering – LLM-powered test generation and maintenance grounded in GRDF's technical corpus.
- Digital Quality – Quality engineering framework with continuous evaluation and regression pipelines.
- Digital Analytics – Data pipelines feeding models with reliable features and observability signals.
- Digital Empowerment – Training and co-construction program making internal teams autonomous on AI.
Critical infrastructure demands engineering discipline. We worked closely with GRDF's quality teams to build an AI platform that reflects their standards, earns operator trust, and holds up under audit.
Project Solutions
We believe critical systems deserve AI that is engineered, not improvised. For GRDF, we delivered solutions that balanced automation gains with strict guardrails, ensuring every stakeholder, from engineers to auditors, could trust what the platform produced.
- Assessment First – Auditing delivery flows and test assets to target the highest-impact automation opportunities.
- Guardrailed AI – Designing evaluation pipelines and guardrails so every AI-generated artifact stays trustworthy.
- Industrialization – Deploying the platform on GRDF's infrastructure with observability, governance, and skill transfer.
The result is a quality engineering platform that cut regression effort by 62% within eight weeks while raising critical-path coverage, and internal teams trained to keep improving it, whom we support on the projects that follow.
