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Squirro launches new advanced AI platform TRINITY to enable Machine Learning to deliver insights driven applications across the enterprise

Squirro’s TRINITY platform to become the digital nervous system for the enterprise

Squirro,the advanced context intelligence and insights solution provider, has announced the launch of its new platform TRINITY, an advanced technology that places Artificial Intelligence (AI) and Machine Learning (ML) right at the heart of the enterprise.

Squirro is also launching a range of new features all based on TRINITY – Smart Filtering, Graph Search and Trend Detection – that will enable organisations to drive more revenue by extracting vastly improved insight from their structured and unstructured customer data and benefit from contextual and intuitive enterprise search.

“For the most part, AI has so far been more hype than substance. TRINITY is a groundbreaking yet pragmatic approach to put AI and ML right at the core of the modern enterprise,” said Dr. Dorian Selz, CEO and co-founder, Squirro. “Data is any organisation’s most valuable asset and we believe AI and ML are crucial in helping maximise that value, making companies smarter and employees more effective in their day-to-day roles.”

Working with customers in industries such as Financial Services (FS), telecommunications and manufacturing, earlier in 2017 Squirro completed a $10m Series B funding round, with investors including Orange Growth Capital and Salesforce Ventures. The new features (all available in Q4 2017) are the first product enhancements since then, and include:

Smart Filtering – a few keywords are not sufficient in enterprise search. Squirro Smart Filters allow users to express complex search concepts quickly and easily. Just upload a few samples, and Squirro does the rest, locating the right information anywhere in an organisation’s emails, databases, documents, spreadsheets, intranets and much more. It is so intuitive it will even make relevant and contextual suggestions back to the user, summarised as a simple word cloud which can be fine-tuned as desired.

Machine Learning is integral to Smart Filtering, with its word vectors that enable Squirro to add content from other places, suggesting related relevant search terms and even training the algorithm to make suggestions for additional items to improve a smart filter.

Graph Search – deepens customer insight by providing a user with a visual representation of all interactions and engagement with a customer. It looks at masses of unstructured data – all emails sent to an organisation, delivering the right information at the right time to the right person, in different departments and multiple locations – and provides a way for a user to take meaningful action with a customer, outlining clearly and in real-time who knows who within an organisation.

Trend Detection – using a single data point within an enterprise can be very powerful in terms of alerts and predicting behaviours and incidents, but Trend Detection takes this further by tracking thousands of data points. This allows the building of relationships between data points and gives much more powerful analysis and insight into what trends and patterns may occur.

“We have always placed huge emphasis on R&D and the new AI and ML based features reflect that, all helping our users to better understand their customers in different ways,” continued Dr. Dorian Selz. “Enterprise Search is ineffective – that’s clear to any knowledge worker struggling to locate the right information – so by introducing context, our Smart Filters will make a dramatic difference. We want all our new features to enable tangible business benefits such as this, and ensure that AI and ML start delivering on the hype.”

The new features will be further underpinned by a significant increase in the volume of data that Squirro can manage, upgrading from gigabytes to terabytes and even petabytes per day. This enables Squirro customers to “plug in” their data lake, begin extracting value in a matter of minutes or hours, providing genuine return on their Big Data initiatives.

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