What we do
We offer a framework where marketing demand of product meets the media content owner, establishing commercial agreements between the parties that can be dynamically extended to accommodate new product placements with the use of our placement solutions.
Characterizing & Locating
Use of specially trained AI Convolutional Neural Networks (CNNs) for object recognition and localization to incorporate advertising messages to existing video products. .
Data for Media Providers, Content owners, Advertising Campaigns, Scanned media data, DAM, and online updates of advertising products availability.
Combination of available advertising and marketing demand with the appropriate Video Product and advanced system approval.
It is divided into two subsystems depending on the type of the Advertising Product 2D and 3D.
Production of our own programs using our framework SaaS
- Difficult to target core audience with TV ads.
- Companies can’t afford to spend thousands of euros on a high-profile advertisement or campaign without knowing the impact it can have on their brand.
- Television viewers usually avoid commercials using Zapping & Zipping.
- 30% of digital users in 2018 are using AD blocking technologies.
- The advertiser's investment depends on the acceptance of the products to the consumers.
- TV series have a lower value after their first broadcast date.
- Influencers haven’t got directly access to Adv Campaigns.
- Music industry has greatly reduced its revenue and is looking for new ways to increase it.
- The high Cost for video advertisement.
- Placing Products on high-acceptance programs increases, the product acceptance & the positive behavior from consumers.
- The influence of product placements in television serial comedies on consumer attitudes toward the products is very high.
- Increases brand awareness & enhancing engagement of the audience.
- Cost reduction.
- Alternative approach for the annoying media promotion.
- Maintain complete editorial control.
- An End to End Solution in a fraction of the conventional required time.
- Increasing the value of TV series.
- Easy bridging Influencers with Advertising campaigns.
When we are dealing with the post production phase multiple CNN instances each with custom trained models can scan the media in order to detect and classify the objects found in the corresponding timecode (tc). Separate passes will occur for the detection of objects that are well suited for placing a product in relevancy to them (e.g. tables, street signs, roads, walls, bottles, mugs, refrigerators, books, newspapers, desks, etc.) and different instances can scan the media for commercial images, logos etc. Then all the collected data are available in the decentralized DB infrastructure for evaluation and further commercial exploitation.