Gst-Audit: The instrumentation tool for your pipelines
gstreamer, open-source, events, beaverThis blog post provides an overview of the Gst-Audit open source project, how it was born, and the technical challenges on building it
Research Initiatives
Spearheading the future of technology at Fluendo
RDI at Fluendo drives our continuous evolution. We go beyond immediate product development to investigate emerging technologies, explore untapped domains, and foster a company-wide culture of creativity. Our agile, open innovation model empowers internal talent to transform bold ideas into the next-generation of solutions.
How we drive innovation
Incubating new ventures
We focus on the earliest stages of the product lifecycle, exploring new business models and transforming fresh ideas into concrete product proposals.
Exploratory research
We dive deep into complex, emerging fields building a robust internal knowledge base before productizing.
Empowering internal talent
Our Innovation Committee channels ideas from any member of the company to drive innovation in products, processes, and methodologies.
Open source contributions
We believe innovation thrives in collaboration. We proudly support and actively contribute back to the Open Source Software (OSS) community.
Our Research Initiatives
Lynx →
Advanced video encoding optimized for desktop virtualization (DaaS & VDI)
A specialized, cost-effective, and energy-efficient encoding solution leveraging LCEVC-based enhancement layer, screen content coding (SCC) tools, content-aware encoding optimization, guided encoder search, and chroma upsampling to a enhanced EUC (End User Computing) UX (User Experience).
Raven →
Empowering the Edge: Intelligent multimedia architectures for real-time
The Raven initiative is Fluendo’s strategic research framework designed to navigate and lead the convergence of Multimedia Processing and Edge Artificial Intelligence. By transforming complex video streams into actionable, real-time insights, Raven establishes a robust foundation for next-generation AI SDKs, tailored consultancy services, and scalable hardware-accelerated products.
Cheetah →
Maximize video encoding performance by parallelizing across all GPU and CPU cores
Cheetah explores the usage of multi-core parallelization to slash transcoding times and boost resolution without changing the stack. A codec-agnostic meta encoder combines hardware and software resources to multiply encoding speeds, leveraging all machine resources to accelerate VOD encoding and improve live streaming resolutions.
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
Fluendo at GStreamer Conference 2025 in London
gstreamer, events, open-source, owlWatch Fluendo's technical talks from the GStreamer Conference 2025 in London.
Raven: A 100% GPU-driven AI inference framework for real-time video and graphics
ai, multimedia-edge-ai, fluendo-ai-plugins, ravenRedefining real-time AI inference with Raven's GPU-driven architecture.
NMS-Raster: Post-processing bounding boxes using the “G” in GPU
sports, multimedia-edge-ai, gstreamer, fluendo-ai-plugins, ravenEfficient bounding box post-processing using GPU-native NMS-Raster.