What makes AI-enabled Profuz LAPIS unique in a data-centric world?
Digital Asset Management systems emerge as essential for enhancing efficiency
Owing to the widespread digitalisation of data, AI-enabled digital asset management media systems are bringing revolutionary change to the industry. Forecasters predict that within a couple of years, market demand will double in size as digital data and digital content production grows. Digital asset management is a crucial requirement for most businesses to survive what is coming ahead, as these systems offer a centralised, secure, and efficient way to manage digital assets.
While the full value of technology continues to become evident, it is obvious that AI has tremendous potential to streamline and speed up data processes, with the promise of significant productivity gains and competitive advantage.
Powering AI with a media asset management system can assist companies in accomplishing tasks more efficiently. MAMs encompass tools for workflow management, orchestration, and automation, which, when joined with AI technology features such as enriched metadata and speech-to-text, provides new levels of functionality.
If there is anyone whose brains are to be picked on this topic, look no further than Kamen Ferdinandov who not only has the expertise, instinct and ingenuity in this vital area, but has been way ahead of the curve.
As CTO of tech firm Profuz Digital and developer of the Profuz LAPIS media asset management system, Kamen is passionate about providing businesses with platforms that can adapt to their workflow as opposed to the other way around. He outlines below what he thinks makes the AI capability in LAPIS different to other media asset media systems that are AI-enabled, expanding on why he believes companies should choose Profuz Lapis over other systems at this critical time.
User-friendly media asset management system Profuz LAPIS is making headway, already being used by global broadcasters such as Canal+ France, Council of Europe, Bulgarian National Radio and many other organisations as an indispensable advantage. Packed with every tool and feature required to manage multiple TV channels, it is designed to organise all the media assets within a media organisation, which includes movies, documentaries, series, clips, and promotions, to be categorised, searched, filtered, and sorted. Additionally, tools for importing and mass editing are provided to facilitate the most efficient asset management process.
“The architecture in Profuz LAPIS is built with the vision to allow for further additional data processing, transformation and aggregation modules to be included. The ability to be able to further add AI-enabled data processing, transformation and aggregation is already effortless in LAPIS, as it has been programmed to do it naturally. In LAPIS, this processing is classified and it’s possible to have more than one module per type,” Kamen explains, “For example, you can add multiple translation engines, so that the most appropriate one, based on language pair, or type of translation, and so forth, can be selected.”
LAPIS also supports local or cloud AI engines. Usually, LAPIS clients tend to opt for local AI because of data protection policies.
Due to the fact that LAPIS can perform various other data transformations, makes it possible for some AI processing data to be pre-processed before utilising a particular engine, or post-processed after an engine.
“Another unique advantage of LAPIS is that it can provide or prepare complex data to AI engines. This means that not only singe data objects and their primary metadata can be used as source material for AI engines, but also related objects’ metadata. Some AI engines allow the use of different types of data for common vectorisation – for example text, images and sounds to use common classifiers – LAPIS is perfect for these scenarios because of its data handling approach of all the data and any data within a single hub,” Kamen notes.
As a leading platform, LAPIS prioritises digital security with its advanced features.
Profuz LAPIS also brings additional benefits regarding global scalability and integration as it is adaptable and designed for global scalability by offering seamless integration capabilities with various organisational tools, encompassing content management systems, marketing platforms, and design applications. Such integrations facilitate the effortless transfer and management of digital assets across different platforms, minimising the need for manual intervention and enhancing organisational productivity.
As the central hub of enterprise data management, LAPIS serves as a powerful data analytics and reporting tool that improves over time with machine learning capabilities.
In addition, LAPIS is an excellent and reliable centralised asset source. Digital asset management platforms offer a unified solution for organising and accessing a variety of digital content, ranging from images and videos to text documents and audio files. This centralisation is pivotal in eliminating the inefficiencies associated with scattered storage systems, ensuring consistent brand representation. Advanced search functionalities and metadata tagging capabilities expedite asset retrieval, streamlining workflows and boosting productivity.
A plethora of recently added AI features are currently available in the Profuz LAPIS system of which a few are summarised below.
Semantic search is a powerful feature that allows all text based data in LAPIS to be searched semantically or by meaning, in addition to the obvious keyword or phrase searches.
Speech to text converts audio and video files to timed text. This can be used for subtitles or text search into associated media files. Depending on the engine, various languages are supported, and some engines allow direct translation from audio. For example Whisper allows any supported language to English, whereas Microsoft allows for any supported multiple languages simultaneously.
Speaker identification can identify different speakers in the audio/video materials. This can be used for automatic segmentation, classification, and so on.
Text to speech features support of both normal and timed text is supported.
Translation of simple text, text files and timed text can be translated. Timed text is managed by LAPIS for the engines that do not support timed text translation.
Object recognition is available for both images and videos. Depending on the chosen engine, various types of objects can be automatically detected allowing sub-image classification and search function.
Face recognition – In LAPIS you can add identity photos which can be used to recognise people in images and videos. Unknown faces will only be detected and further classified manually. This data is used also in search results.
Text extraction (OCR is available for both images and videos, depending on the engine that is used and the multiple languages that are supported. All extracted text is used for search results too.
“Profuz Digital is a specialist systems integration developer that was founded in 2014 and has been equipping a number of broadcasters over the past decade with performance-leading customised services. As CTO and technology developer at Profuz Digital, my focus is on how we make life easier for broadcasters, and how we can create software that adapts to each customer’s unique way of working.
By investing in Profuz LAPIS, organisations of all sizes immediately place themselves in the best position to capitalise on next-generation technologies and continue to evolve their business to stay ahead of the competition. We are passionate to help broadcasters work in the most efficient manner possible.” Kamen adds.
Gain further insight by watching the series of mini tutorials via You Tube https://profuzlapis.com/video-tutorials/
