SciTransfer
Organization

CONTENT FLOW GMBH

Berlin SME developing accessible video livestreaming tools and AI-powered video compression using deep learning and neural networks.

Technology SMEdigitalDESME
H2020 projects
3
As coordinator
2
Total EC funding
€2.8M
Unique partners
2
What they do

Their core work

Content Flow is a Berlin-based technology SME that develops video livestreaming solutions designed to simplify and democratize live video production. Their core product, Contentflow, enables easy-to-use livestreaming without requiring professional broadcast equipment or expertise. More recently, the company has expanded into AI-powered video compression, applying deep learning and neural networks to improve video quality and reduce bandwidth requirements for streaming applications.

Core expertise

What they specialise in

Video livestreaming platformsprimary
2 projects

Two Contentflow projects (SME-1 and SME-2) focused on making livestreaming accessible, with the second scaling up significantly during COVID-19.

AI-based video compressionemerging
1 project

AISTREAM project applied neural networks and deep learning to video codec development, targeting visual quality optimization through entropy-based methods.

Democratization of media technologysecondary
2 projects

Both Contentflow projects emphasize removing technical barriers to livestreaming, positioning the company around accessibility of broadcast-grade video tools.

Evolution & trajectory

How they've shifted over time

Early focus
Video livestreaming platform
Recent focus
AI video compression and codecs

Content Flow followed a classic SME Instrument growth path: an SME-1 feasibility study for their livestreaming platform in 2019, then a full SME-2 scale-up in 2020 that explicitly addressed COVID-19 remote connectivity needs. By 2021, they branched into AI-driven video compression through the AISTREAM project, signaling a shift from pure platform development toward underlying video technology powered by machine learning. Their trajectory shows a company moving from application-layer tools toward deeper technical capabilities in video encoding.

Content Flow is moving from user-facing livestreaming tools into the AI and neural network layers of video technology, suggesting future work will center on intelligent video processing and next-generation codecs.

Collaboration profile

How they like to work

Role: consortium_leaderReach: regional2 countries collaborated

Content Flow operates primarily as a project leader, having coordinated two of their three H2020 projects. Their consortium footprint is minimal — only 2 unique partners across 2 countries — which is typical for SME Instrument projects where the company itself is the focus. When they do collaborate, they join as a specialist contributor (as in AISTREAM), indicating they can work both independently and as a technical partner in larger efforts.

Very small collaboration network with just 2 unique partners across 2 countries, reflecting SME Instrument funding where the company develops its own product. Their participation in AISTREAM suggests openness to joining external consortia when the topic aligns with their video technology core.

Why partner with them

What sets them apart

Content Flow combines practical product experience in livestreaming with growing R&D capability in AI-based video compression — a rare combination for a small company. Their COVID-era scaling demonstrated the ability to respond rapidly to market demand, and their move into neural network codecs positions them at the intersection of streaming infrastructure and machine learning. For consortium builders, they offer both a working product platform and emerging deep-tech expertise in video AI.

Notable projects

Highlights from their portfolio

  • Contentflow
    Secured EUR 2.3M in SME-2 funding — one of the larger single-company grants — with a timely COVID-19 pivot that demonstrated market responsiveness.
  • AISTREAM
    Marks the company's strategic expansion from application development into fundamental AI video compression research using deep learning and neural networks.
Cross-sector capabilities
Media and broadcasting technologyRemote communication and telepresenceAI and machine learning for multimediaEducation and e-learning platforms
Analysis note: Profile based on only 3 projects over a short period (2019-2021). The company's product and direction are reasonably clear, but the small project count and limited consortium activity mean collaboration patterns and network insights are thin. No website URL was available in the data to verify current operations.