
Multimedia Edge AI
Real-time media processing with intelligent edge solutions
Accelerate your media processing with ultra-low-latency, AI-enhanced video solutions, optimized for edge performance where milliseconds matter.


Boosted and intelligent video solutions
For applications requiring immediate data analysis and low latency—such as real-time monitoring, autonomous vehicles, and intelligent surveillance—processing information locally is far more effective than relying on centralized cloud servers.
At Fluendo, we combine our expertise in multimedia processing, hardware acceleration, and artificial intelligence to create solutions that deliver exceptional performance and reliably on-edge devices.
Our edge-focused approach ensures we meet the high-performance demands of industries that operate seamlessly on edge devices, catering to sectors that demand real-time, reliable data analysis.
Boosted and intelligent video solutions
For applications requiring immediate data analysis and low latency—such as real-time monitoring, autonomous vehicles, and intelligent surveillance—processing information locally is far more effective than relying on centralized cloud servers.
At Fluendo, we combine our expertise in multimedia processing, hardware acceleration, and artificial intelligence to create solutions that deliver exceptional performance and reliably on-edge devices.
Our edge-focused approach ensures we meet the high-performance demands of industries that operate seamlessly on edge devices, catering to sectors that demand real-time, reliable data analysis.
Key challenges of AI projects
Deep multidisciplinary expertise
A successful implementation demands advanced knowledge across media processing frameworks (FFmpeg, GStreamer, DirectX), AI frameworks (TensorFlow, PyTorch, ONNX, TensorRT, OpenCV), multi-threading, and hardware accelerators, making it challenging to build, benchmark, deploy, and maintain these solutions.
Heterogeneous hardware
With cloud, edge, desktop, and mobile devices leveraging a diverse array of CPUs, GPUs, and VPUs (from NVidia, Intel, AMD, ARM Cortex-A, ARM Mali, and more), adapting solutions across these platforms is no small task.
Framework integration
The diversity of development and production hardware makes the “program once, deploy anywhere” model unattainable without customized approaches to integrating pipelines across various AI frameworks.
Deep multidisciplinary expertise
A successful implementation demands advanced knowledge across media processing frameworks (FFmpeg, GStreamer, DirectX), AI frameworks (TensorFlow, PyTorch, ONNX, TensorRT, OpenCV), multi-threading, and hardware accelerators, making it challenging to build, benchmark, deploy, and maintain these solutions.
Heterogeneous hardware
With cloud, edge, desktop, and mobile devices leveraging a diverse array of CPUs, GPUs, and VPUs (from NVidia, Intel, AMD, ARM Cortex-A, ARM Mali, and more), adapting solutions across these platforms is no small task.
Framework integration
The diversity of development and production hardware makes the “program once, deploy anywhere” model unattainable without customized approaches to integrating pipelines across various AI frameworks.

Frequently Asked Questions (FAQ)
At Fluendo, we are dedicated to delivering innovation and quality in our multimedia Edge AI solutions. We invite you to connect with us to explore how our cutting-edge technologies can elevate your projects to new heights. We’ve compiled the most frequently asked questions to help you better understand how we work.
How can Fluendo help your business? +
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.
Can you help us create a custom AI application? +
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.
Can Fluendo port our Python AI model to an embedded PC? +
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).
Can you help us improve our AI model’s accuracy? +
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.
Can Fluendo optimize our slow AI application? +
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.
We are into AI but but we are missing the tools and know-how to make it happen. Can you help? +
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.
From the code to the action
Developments that bring real-world results. These case studies show how our solutions help your business achieve goals and enhance user experiences.Case Studies


Advertisement detection in multimedia content
The application automatically detects precise timestamps of advertisements embedded within multimedia content by utilizing advanced artificial intelligence techniques. This eliminates the need for manual labeling, significantly boosting efficiency and reducing costs associated with advertising and marketing tasks.
Read more
Real-Time sports analysis with AI on the edge

Virtual avatars for AMD GPUs in video games streaming
Concepts with real-world potential
These use cases showcase the ideas, technologies, and approaches we’ve developed to solve real industry challenges.Use Cases

Real-time AI weapon detection for safer public spaces

AI-Driven subject tracking with PTZ Cameras for live events and surveillance

AI drones for wildlife monitoring and population management

AI-powered depth-aware color correction for subaquatic drones
Bits & Bytes
Explore our blog, one byte at a time. Our team unpack our latest news, industry insights and in-depth articles to connect you with the multimedia world.Blog
Read more about our work

AI-based soccer metrics extraction app
AI-powered soccer app that extracts tactical metrics like player distances, movement tracks, and team identification from broadcast video—all in real time and without manual intervention.

Virtual avatars optimized for AMD GPUs in video games
Discover our latest AI-based 3D virtual avatars rendering application for video games and Twitch streaming.

Intelligent parking spot occupancy detection
What if your parking lot could define its own layout and monitor occupancy, without any manual intervention? In this blog post, we explore how Fluendo helped a mobility client automate parking spot detection and tracking by optimizing their car detection model and replacing manual spot labeling with a fully automated, computer vision-based proof of concept running on edge AI infrastructure.

Privacy-preserving AI video surveillance with edge intelligence
Real-time AI and GDPR compliance don’t have to be at odds. Learn how Fluendo’s Raven Engine makes privacy-first, edge-based AI video analytics a reality—without compromising on speed or accuracy.