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.

Jay: Background removal redirection to DaaS & VDI endpoints →

Privacy and performance at the edge

The Jay initiative researches AI-driven background removal on the endpoint to optimize video conferencing in virtualized environments and reduce server overhead.

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

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October 20, 2026

Advancing RAVEN: Fluendo wins Red.es AI grant

multimedia-edge-ai, the-lab, fluendo-ai-plugins, raven

Driving the future of multimedia innovation We are proud to announce that Fluendo has been selected as a recipient of a grant Red.es IA cadena de valor 2025 Call for Proposals for R&D in Artificial Intelligence (C003/25-ED), framed within the Digital Spain 2026 Agenda. This achievement underscores our commitment to pushing the boundaries of multimedia technology and supports our long-term R&D roadmap. This boost will allow us to take our prototype, RAVEN, to the next level through the RAVEN HOOD project, transforming it into a real-time, cross-platform, open-source AI multimedia engine designed to integrate with the most demanding value chains.

September 3, 2026

Raven AI Engine v0.4.7: From an AI inference engine to a heterogeneous GPU computing platform

broadcasting, video-surveillance, multimedia-edge-ai, gstreamer, fluendo-ai-plugins, anonymizer, raven

Raven v0.4.7 and FAIP v1.2.6 extend GPU-accelerated AI processing to Ubuntu x64 with CUDA, Vulkan, heterogeneous execution, and user-defined shaders.

July 23, 2026

Guided encoder search optimization for remote desktop streaming

daas-vdi, codecs, gstreamer, optimization, the-lab, open-source, remote-desktop-coding-tools, h266-vvc, lynx

We explored how operating-system dynamic region information can guide encoder search decisions, reducing unnecessary analysis for remote desktop streaming while preserving coding efficiency.

July 22, 2026

Screen Content Coding Tools for Remote Desktop Streaming

daas-vdi, codecs, ffmpeg, optimization, the-lab, open-source, remote-desktop-coding-tools, lynx

We used SVT-AV1 as an experimental vehicle to isolate Screen Content Coding tools and evaluate a codec-agnostic methodology for improving desktop streaming quality and efficiency in DaaS & VDI environments.