As pioneers in the social media space, many years ago we realized the limitations of existing social media intelligence/analytics tools and saw an opportunity to take our real-world experience guiding large organizations combined with the latest machine learning innovations to create something much better. And we did.
Social media is powered by content, especially images, and our technologies build an ecosystem around clients that allows our software to understand their environment by recognizing objects, logos and other features found in images. The same approach applies to video recognition by parsing frames.
Natural Language Processing
By training machine learning models to understand the linguistics around clients – their company name, products, customers, etc. – we use natural language processing to form context and meaning, and ultimately eliminate false positives that skew insights.
Extracting emotions from social media content is no easy task, however natural language processing allows us to build a better understanding of what’s being said and whether it’s positive, negative or neutral.
As a way to recreate how we believe the human brain functions, we use deep learning to build ecosystems around clients that recognize all aspects of their environment – sights, sounds, and more.
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