Fluendo offers comprehensive solutions for real-time media processing, from building robust MLOps infrastructure to the deployment and optimization of AI models on specific devices. We ensure your solutions are production-ready, with ongoing maintenance and performance optimization to guarantee the best results for your business, whether you’re working with embedded systems or complex edge environments.

Absolutely! We start by understanding your needs to design and develop a custom AI model tailored to your challenges. After evaluating its performance in real-world scenarios, we deploy it to ensure optimal performance and reliability.

We have extensive AI and hardware optimization expertise, enabling seamless adaptation and deployment of your AI model to embedded systems. We also offer Raven AI Engine, a versatile AI runtime designed for optimized inference across various platforms (NVIDIA, AMD, etc.) and programming languages (C++, C#, and more).

Of course! Our AI development team excels in refining models that don’t meet specific KPIs. Using techniques such as data filtering, synthetic data generation, model fine-tuning, and optimization, we help enhance your model’s accuracy and achieve the desired outcomes.

We specialize in enhancing the performance of AI applications. Thanks to our expertise in hardware acceleration and efficient runtime environments, we can drastically reduce inference times, making your model suitable for real-time applications.

Fluendo has developed a powerful in-house MLOps infrastructure to ensure traceability throughout the AI lifecycle. From model creation to production monitoring, our system tracks datasets, models, and reports, aligning with the latest EU AI Act regulations and ensuring transparency and compliance.