AI solutions for entertainment & media

Leveraging the abundance of data to uncover insights and introduce automation

Up to 50%

faster and more accurate image and video tagging


Human capabilities in sentiment analysis and bot detection

Up to 30%

lower customer churn and increased NPS

Use cases

Video and image taggingVideo and image tagging

Automating challenging video and image analysis to produce results on a par with human work

  • Aerial/satellite image recognition and classification
  • Detection of anomalies based on images (e.g. supporting doctors diagnosis)
  • Autonomous car simulations

Content sentiment analysisContent sentiment analysis

AI-driven language processing to automate sentiment analysis

  • Real-time data stream analysis
  • Finding correlations and patterns between different data streams

Viewer intelligenceViewer intelligence

Offering better customer experience and increasing loyalty

  • A recommendation engine with personalized suggestions for each customer
  • Calculating the probability of churn
  • Predicting revenue related to specific content

Programmatic ad optimizationProgrammatic ad optimization

Discovering anomalies, spotting bots and improving the performance of ad campaigns

  • Predicting the click-through rate of internet advertisements
  • Spotting internet bots that click ads

Let’s connect!

Are you curious if your business challenge can be tackled with AI?
Contact us and we’ll give you a free assessment and a quotation

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Case study

Aerial image recognition

Project challenge:

The client needed a system to automate the recognition of Right Whales from aerial photographs.

Tracking the individual Right Whales was necessary to protect the endangered species, track migration routes and count the whales in a herd. Whale identification had always been done manually, with skilled researchers comparing photos with a catalogue, a process that took up to three hours.’s solution reduced the time to three minutes, by developing the most accurate model in the world with over 87% up to 98% of accuracy. The model was based on Convolutional Neural Networks that have been optimally selected to deal with the uneven distribution of training data (some whales were underrepresented in the training set)

About the client:

The National Oceanic and Atmospheric Administration is a US agency in charge of protecting oceanic wildlife.

  • Country: US
  • Number of employees: 11,000+
  • Overall yearly budget: $5B+

Success stories

Assessing content quality

Brainly ML-based content management process automation Learn more


Predicting CTR and spotting bots in online advertising

CTR prediction 35% CTR prediction improvement over existing heuristics Learn more

#retail #dataanalytics

Autonomous vehicles

Volkswagen Generated over 100 years of simulated driving experience for vehicle training Learn more


Detecting propaganda and illicit content

The United Nations 91% of Twitter accounts disseminating terrorist propaganda identified Learn more


Automated mapping from satellite imagery

Humanity and Inclusion 95% accuracy in object recognition on satellite images Learn more


Diagnosing diabetic retinopathy

California Healthcare Foundation Human expert-level accuracy Learn more


Aerial image recognition

NOAA 98% time reduction in image analysis Learn more


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  • Sp. z o.o.
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  • Poland
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