By analyzing and adding millions of multilingual documents through this graph daily, it becomes an evolving and self-learning structure that, in real-time, represents what’s going on in the world.
Using this graph and understanding the hidden connections that make up the business landscape, Mito is able to know how relevant and significant each event is for any company, product or industry.
Extreme self-learning capabilities
Mito’s Context Relevance system uses state-of-the-art machine learning to assess the relevance and impact of each event. This usually requires massive amounts of manually generated training data for it to work properly.
Mito—on the other hand—has proven its ability to create customized machine learning models in a matter of days. By using our proprietary knowledge graph and a world-class entity linking system Mito is able to leverage its self-learning capabilities—even with only limited access to training data.
This means you don’t have to waste time sifting through unnecessary information, get only what matters, and what your business can use.
Our world-class language agnostic Entity Linking delivers structure, clarity, and insight to the constant stream of data. Mito currently covers more than 18 million different meaningful entities, such as people, places, companies, and even abstract concepts.
Duplicate articles covering a single story is a thing of the past. By performing real-time clustering on all ingested content, Mito is capable of identifying important events as they happen.
A combination of state-of-the-art content categorization techniques and our sophisticated Knowledge Graph makes Mito capable of classifying textual content. It works on pre-defined categories like finance and sports, as well as previously unknown content categories.
We fuel our Sentiment Analysis service with world-class Entity Linking to provide the highest possible granularity.
Tired of reading through stacks of long documents to get the essence? Mito.ai provides summarization. And as the rest of our platform, it works across language barriers.
Flexible data sources
We are constantly adding more data sources to our system improving our analysis constantly.