DragonLLM × FlexAI: Sovereign AI for Finance
Deploying fine-tuned financial models on sovereign, autoscaling infrastructure — with zero surprises.
DragonLLM (formerly Lingua Custodia) builds fine-tuned, specialized AI models for the financial domain. When they released two frugal models and needed flexible, sovereign infrastructure to expose them, FlexAI delivered managed inference endpoints with autoscaling and scale-to-zero capabilities — all hosted in France to meet strict data sovereignty requirements.
The context
DragonLLM is crafting fine-tuned, specialized AI models for the financial sector. The company recently released two frugal models designed for the financial domain and needed to expose them on infrastructure that was both flexible and scalable.
With European financial institutions as their primary customers, every decision around hosting, data handling, and infrastructure had to satisfy the strictest sovereignty and compliance requirements.
The challenge
DragonLLM faced a set of constraints that ruled out most off-the-shelf cloud solutions:
- Unpredictable traffic patterns: DragonLLM had no visibility into how many concurrent users would hit their endpoints, making fixed infrastructure impractical and expensive.
- Scale-to-zero requirement: Paying for idle GPUs was not an option. The team needed endpoints that could spin down completely when not in use and restart on demand.
- Sovereign hosting mandate: Working with major European financial institutions meant models and data had to remain on French soil — no exceptions, no compromise.
The net effect: they needed a partner who understood both the technical and regulatory landscape of European financial AI.
The solution
FlexAI proposed a tailored deployment that addressed every constraint:
FlexAI deployed DragonLLM's fine-tuned financial models on its sovereign infrastructure in France. All data processing and model hosting remained within French borders, satisfying the strictest regulatory and institutional requirements.
FlexAI provided fully managed inference endpoints with built-in autoscaling. Traffic spikes were absorbed smoothly, and endpoints scaled to zero during idle periods — eliminating wasted GPU spend entirely.
FlexAI's inference sizer tool helped DragonLLM's engineers benchmark and select the optimal GPU for their models. After rigorous testing, both teams consolidated to a single, highly efficient inference endpoint serving both models.
"We wanted to find a local partner to deploy our models on sovereign infrastructure. FlexAI proved to be a very easy and reliable solution. We never had any surprises, and the autoscaling capabilities absorbed the traffic smoothly."
The results
FlexAI delivered a production-ready sovereign inference platform that matched DragonLLM's unique requirements — autoscaling, scale-to-zero, and full data sovereignty — without compromise.
Why this matters
Deploy on sovereign infrastructure without giving up autoscaling, managed endpoints, or operational simplicity. Compliance and performance aren't trade-offs.
Scale-to-zero means you only pay when your models are serving traffic. For financial AI with variable demand, this transforms the cost model entirely.
No surprises, no manual scaling, no babysitting infrastructure. DragonLLM's team focused on model quality while FlexAI handled the rest.
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