MAM system architectures in comparison

When looking „under the hood“ of Media Asset Management systems, there is a heavily complex technical world. We want to briefly delve into this world and explain why the technical architecture and the processes that a MAM system is built on matters. To simplify the topic, we find a good comparison with physical products that are more tangible and familiar to many in terms of performance indicators. Picture yourself buying a car. The first option you are offered at a car dealer is a massive muscle car, say Dodge RAM v10. It is renowned for its exceptional power and towing capacity, thanks to its robust 8.0-liter V10 engine, making it a top choice for heavy-duty tasks and off-road adventures. However, it is extremely expensive, heavily polluting, massive, and not really the futuristic sustainable car that you had in mind. Then you are presented with another option: a lightweight and speedy hybrid car with a price tag a third of the Dodge. It drives like a dream, has an advanced and stable software, is sustainable and has a set of cool features. You are thrilled! This is exactly what you wanted.

This visual is created with AI by FlowWorks.

What type of MAM systems do these two options represent in terms of system architecture? The Dodge RAM represents the “classical” MAM that operates on CPUs (Central Processing Units). They can perform key MAM functions such as transcoding and processing, but they do this to a high cost and with an inefficient energy consumption, being slower and more limited in terms of capacity than agile alternatives. What CPU-based processing entails is expensive hardware in terms of servers, intense maintenance related to software updates, data backups, and periodic hardware checks as well as operational inefficiency in terms of heavy electricity consumption and blocked Internet lines. As green tech continues to emerge as a mainstream topic, the awareness of digital sustainability is established. The CPU-based, “Dodge RAM”, MAM systems were experiencing their golden days when the amount of media assets was significantly lower, the quality of the material was less demanding, and processing requirements were relatively modest. They have not managed to keep pace with the growing demands of modern media production and management. What is happening today is that the volume of media assets is growing exponentially, the quality of content is consistently improving with higher resolutions and more complex formats, and the demand for faster, GPU-optimized MAM systems to handle these challenges has become increasingly evident. Every single person with a camera or a smartphone can be a content producer with large volumes of media assets. This calls for intelligent and light-weight systems that can manage the content with a sustainable and intelligent modus operandi.

This visual is created with AI by FlowWorks.

Let’s then look at the futuristic hybid smart-car. What does it do differently from the Dodge? It can use all its engines and inner components in a balanced and optimized way, making use of any one of its components that can perform a specific task most efficiently. For example, instead of using the CPU for tasks such as transcoding, face detection or AI, it makes use of different available GPUs (Graphical Processing Units) or ML (machine learning) accelerators, that can perform the task quicker and more efficient. At the same time, it is not using any computational power of the CPU, which then is free for MAM core functions (such as file handling, database publishing, archiving etc.) and user front ends. While the CPU-based “Dodge RAM” uses 100% of the CPU power, while still performing its tasks much slower compared to its challenger, the GPU-based system consumes only 1% of the CPU-capacity. For example, when the so called “Dodge RAM” system is transcoding at 100% of its capacity, it has no computational capacity left for any other tasks. This means that the user experiences extreme slowness and malfunction when simultaneously using the MAM system – simply because the system already is at its limits. As a comparison, when its counterpart, what we here exemplify as the “smart-car” system, is transcoding, the user will not notice this while simultaneously using the MAM system since the system has 99% of its capacity left for operating normally. In addition, when you need to scale up a “classical” MAM system that we compare with a Dodge RAM car, to, for example operate a growing amount of media assets, or when there is a need to add more users to operate the system, you are forced to buy expensive CPU-based hardware, that equals “muscles” of the Dodge RAM to be able to scale the system. With this, you gain more muscles but remain slow and operate with the same stagnating way as before – not to mention the enormous costs that this comes with.

A MAM system that can perform on the top of its class needs to be flexible and intelligent. Factors such as scalability, capacity and efficiency are at the centre of this. Modularity enables customization and a cost-efficient way to build a MAM system that serves the specific needs of a customer and can easily be extended with new features as new needs emerge. Digital systems are difficult to evaluate from the outside since the performance indicators are not clearly established and the architecture and processes that make the system are so highly complex that few are able to evaluate and understand them. Our advice to anyone searching for a MAM system or wanting to understand more of the topic is to ask any MAM provider of interest about the system architecture, which factors are affecting its capacity and how flexible and scalable the system is and to what cost it is scalable.

What you should go for instead of expensive muscle-power is agility and intelligence.

We at Flow Works see that MAM systems will be an essential tool for anyone operating a large volume of pictures, videos or audio files in the near future. Thus, we are working on solutions that will make agile and intelligent MAM systems available to anyone who is ready to elevate their work around media assets to new heights. If this topic is as fascinating to you as it is to us, we should continue the disucssion together.

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AI in the world of Media

In the world of Media Asset Management (MAM), Artificial Intelligence (AI) has emerged as a transformative force, promising to revolutionize how media assets are managed, organized, and utilized. However, before diving into the topic of AI in MAM, it’s crucial to mention common misconceptions and gain a clear understanding of what AI in MAM involves, as well as the benefits it can offer to customers working in broadcasting and media production.

Defining AI in MAM

AI in MAM refers to the application of artificial intelligence techniques, such as machine learning and computer vision, to automate and enhance various aspects of media asset management. It’s about making use of algorithms and data analysis to make the management of huge media libraries more efficient and effective.

Misconception 1: AI in MAM is Synonymous with Automation

One common misconception is that AI in MAM is solely about automation. While automation is a significant component, it’s not the whole story. AI in MAM goes beyond routine tasks like file organization and metadata tagging. It includes sophisticated capabilities like content recognition, sentiment analysis, and predictive analytics.

Misconception 2: AI in MAM is Only for Large Enterprises

Another misconception is that AI in MAM is relevant for large actors in the media industry. In reality, AI-powered MAM solutions are becoming more accessible and affordable for media companies of all sizes. Smaller organizations can benefit from AI-driven efficiencies and cost savings as well.

Misconception 3: AI in MAM is a Universal Solution for Every Problem

It’s important to understand that AI in MAM is not a one-size-fits-all solution. Its effectiveness depends on factors like the quality and quantity of data, the specific use case, and the integration with existing workflows. While it can address many challenges, it may not be suitable for every situation.

Benefits of AI in MAM for Media Professionals

Now that we’ve clarified what AI in MAM is not, let’s explore what it can offer to customers working in broadcasting and media production.

Enhanced Content Discovery:

While advanced searches based on metadata already are an eastablished key feature of professional MAM systems, AI brings a new dimension to Content Discovery. While metadata-driven searches rely on structured data like titles and keywords, offering exact-match searches they are limited in searches based on context. AI-driven searches, on the other hand, enable content-based searches, similarity and relevance identification, and natural language processing (NLP). This provides a more comprehensive, context-aware, and nuanced approach to searches, based on visual, audio, text, and contextual aspects.

Efficient Metadata Management:

AI algorithms can generate and refine metadata, reducing the time and effort required for manual tagging. This not only improves content searchability but also streamlines content distribution and monetization.

Content Recommendations:

AI-driven recommendation engines can suggest related content to users, giving creativity input to users and encouraging content reuse.  

Quality Control:

AI can play a crucial role in the quality control of audio and video assets by automatically detecting anomalies or irregularities in the content. This includes identifying issues such as audio distortions, video artifacts, inconsistent color grading, or missing segments. This capability is of special importance in live broadcasting. Additionally, in post-production processes, AI-driven quality control reduces the risk of errors or imperfections, saving both time and resources.

Monetization Opportunities:

AI can analyze audience preferences and content trends, helping media companies tailor their content offerings, so they can keep viewers interested, and maximize revenue generation.

This article was originally published on LinkedIn

#MediaAssetManagement #AIinMedia #MAMtechnology #ContentDiscovery #MetadataManagement #MediaIndustryInsights #ContentManagement #MediaTrends #AIapplications

Green Tech concerns every organisation

Sustainability in the digital world is still a relatively unknown concept, but with recent global developments it is more important than ever. So called Green Tech is for many an abstract topic. While we talk about energy saving by using less lights or getting energy efficient household appliances, it may seem difficult to understand the magnitude of energy spent related to media asset management. Green tech is also not creating the momentum it deserves since there are many commercial actors in the market who make money on inefficient use of cloud storage or transferring large volumes of digital files and hence, do not want this topic to get attention. All digital assets consume energy partly by the storage that is used to store them as well as the energy needed to transfer, view or share them. For users, whether private persons (“prosumers”) or companies, this topic becomes increasingly more urgent as the number of digital assets continues to grow. Not only the amount of video, text and audio files increase, rich media in presentations or communications materials is the norm. What are we talking about with “digital assets”? Digital assets are every file, whether text, video, picture or audio. It therefore is a topic that concerns every organization or person working with digital material.

Flow Works has the solution for the future of media asset management

We at Flow Works spent a few years envisioning the demands of the future digital world and have a solution that saves your time, money and minimizes the use of energy and cloud storage. Our software gives you a complete set of tools for everything one might need related to digital asset management – and the best of it all is that it will save you time, money and energy! Digital asset management is no longer a topic for just professional media producers, news agencies, production houses and so forth – it is a topic for every organisation that works with digital material.


Cloud storage is a huge business. For companies selling digital storage, it is good business when customers have a high quantity of large files. Large files eat up a large amount of storage space that generates income. For the customer this quickly gets expensive and in addition makes it more troublesome to share, view or distribute the material since it requires a solid and strong Internet connection as well as processing power to work with large files. This is inefficient and expensive! The ideal solution is to optimize the size of each file by automated transcoding that requires no action from the user. Flow Works’ software includes exactly this, giving its customers a professional tool for viewing, editing and sharing digital media files (among numerous other fantastic features). When digital files are in an optimized format, then less cloud – and physical hardware space – is used. In addition, with our software only the necessary parts, which is the content intended for sharing or distribution, are transferred to the cloud while the rest of the file stays on local cost-efficient storages (physical hard drives). With all this we limit processing power in the cloud – ultimately optimizing cloud usage. All this matters since it is part of enabling an increasingly digitized world while being energy efficient and sustainable.


Blocking Internet lines for inefficient use related to digital media files is wasting energy and slowing down other functions that make use of the same Internet connection. Not to mention the frustration we all are familiar with when trying to view a video that is stuck due to upload issues. The optimized file formats that we can offer with our software are transcoding, or in other words pre-processing the file automatically to a minimal size and optimized format. With pre-processed formats and files, we only transfer a fraction of the original sources through Internet lines while still maintaining highest quality. This keeps the Internet line free while delivering content with ultimate speed. This also speeds up the overall media workflow up to 25 times compared to other online services, while at the same time capping down the download file sizes for collaboration and distribution partners. When sharing for example a video online, it not only consumes Internet line from the one sharing it, it consumes Internet for every single viewer. The quantity quickly becomes enormous. Sustainability in the connected digital world that shares digital material is strongly linked to minimizing the use of Internet lines.


Flow Works is ultimately a software company, operating its own professional media asset management software since 2005. Hardware is still the other part of the digital world and therefore we have customized our software to function on the operating systems of QNAP NAS devices. NAS devices are in other words Network Attached Storage units that instead of being connected to a computer are connected to a network. This makes it possible to access all materials safely and quickly, as well as enables an easy back-up system. When working with digital media files, QNAP NAS devices are the go-to solution. Now, with our Flow software customers can make the most out of their QNAP NAS. How? They can access all materials stored on their QNAP NAS device through our browser-based user interface that allows the user to view, edit, share and collaborate both internally and externally related to the materials stored on the NAS. It is as easy as it gets when talking about media asset management and offers both private persons as well as professional organisations a very simple way to get started with professional handling of digital files.

The technical superiority of this set-up lies in the optimized use of resources that shifts the system’s resources to parts of it that do the job better. The user does not have to care for the technical processes that are working in the background, but the user naturally benefits from all the upsides of this power-efficient technology. For the user it is in the long run more green, more cheap, more efficient and more hassle-free! Why waste any more time on complex systems that cannot do the job anyway nearly as professional as ours?

Three trends that are re-shaping the MAM market from B2B to B2C

The MAM market has traditionally served large professional media producers such as broadcasters, news agencies, advertising agencies and industrial companies. MAM systems are known for being expensive and thus a strategic investment for many companies. All this is about to change. Read full article