Native Understanding of

100+ Languages

Multilingual Model

 

One of the most remarkable things about HIPSTO’s FALCON V platform and the underlying native Blind Vision technology that powers it is our highly accurate Natural Language Understanding of over 100 languages. We deliver ground-breaking web scraping, sentiment analysis, text classification and other intelligent services across all the world’s major languages, all without sacrificing levels of accuracy.

We believe the combination of the breadth of language coverage with high-quality results within one, single platform is unique and offers an industry-leading solution for global organizations who need to scrape, analyse and extract information from global content in real-time. One of the reasons we achieve this is because we don’t use translation services that fundamentally change the content that is being analysed.

Hipsto vs translation agent

Why Translation Sucks

 

HIPSTO’S expert AI technology team have tested the accuracy of native text analysis vs. Google Translate API on short-form text (Customer Reviews: Chinese to English and Russian to English).

We’ve always known that using ‘Translation Agents’ distorts the accuracy in translation of text data, but even we were shocked by our findings!

❌ Minimum of 10% distortion in both Classification and Sentiment Analysis, translating just into English (where Google Translate has a decent enough model) on short-form text (e.g. Customer Reviews under SKUs on E-commerce platforms).

❌ Using longer form text (e.g. SEC Filing, Legal Documentation, Publisher Content) and a lower quality open source translation agent to translate into multiple languages (e.g. Turkish into English), we estimate with confidence this margin to be in the minimum >40% range of distortion.

At the scale of millions of data points, this represents mission-critical levels of inaccuracy that you’re paying dearly for.

Sentiment Analysis

 

Real customers, real data – real meaning…

Global brands are waking up to the next level of insights hidden within customer reviews, social media messages and other text data.

…But extracting the data only tells half the story.

Sophisticated sentiment analysis is needed to augment text data with the rich contextual details vital for meaning.

Humans are hardwired to discern such meaning but even the most advanced scraping technologies have failed so far to deliver – at scale.

Until now. 

HIPSTO has developed an advanced sentiment analysis solution for customer reviews on e-commerce sites, that uses proprietary Natural Language Understanding (NLU) technology to understand the semantics and meaning of text, just like a person.

We’re proud of the amazing accuracy and consistency of our technology. In fact, our results are scoring significantly higher than our nearest market rivals – F1 accuracy score at 0.94 vs. industry-leading technology at 0.80.

Our technology works natively with 100+ languages, without any translation agents, making it perfect for global brands in multiple territories, who need absolute accuracy in almost any language, and consistency in sentiment composition on semantically similar texts.

Our Sentiment Analysis solution is part of a larger no-code Voice of Customer (VoC) AI Solutions pipeline that includes Web Scraping, Automated Data Set cleaning and Text Classification.

Get closer than anyone to your customers with HIPSTO, and turn text data into meaningful insights to dominate your market.

Sentiment analysis of a review
Text classification of a review

Automated Text Classification

 

You’ve heard of Voice of Customer…but are you ready for ‘Mind of Customer’?

Global brands and e-commerce businesses are beginning to see how emerging AI advancements can help them turn customer reviews, social media messages and other text data into valuable market insights.

But the real value lies in the meaning behind such insights.

If we know what our customer is saying, then we can get closer to what they are thinking.

By deploying Natural Language Understanding (NLU) technology, we can go beyond extracting text data, to truly understanding it.

HIPSTO has developed an advanced automated text classification solution for customer reviews on e-commerce sites, that uses proprietary NLU technology to understand the semantics and meaning of text, like a person – with amazing accuracy.

Our technology works natively with 100+ languages, without any translation agents, making it perfect for global brands in multiple territories, who need absolute accuracy in almost any language.

Our latest text classification solution is part of a larger no-code Voice of Customer (VoC) AI Solutions pipeline that includes Web Scraping, Automated Data Set cleaning and Sentiment Analysis.

Get even closer to your customers with HIPSTO, and take the global competitive edge.

Want +35% Accuracy, With -65% Cost in Your Text Data Analytics?

Shine a light on your hidden text data insights, anywhere in the world, with Blind Vision.

  Blind Vision

 

We have dubbed our proprietary web text data extraction and labeling technology, Blind Vision. It is now, arguably, the best in class globally and superior to the established and trusted Computer Vision and other technologies.

Test studies* have been conducted versus a US based web data integration platform that uses Computer Vision, and the results are conclusive. They showed a +35% increase in accuracy and -65% lower running costs using Blind Vision technology.

We like to remain a little secretive about the ‘sauce’, but we can say that Blind Vision combines sophisticated Raw Code Processing algorithms and our own deep learning network architecture.

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  Advanced Sentiment Analysis

 

Sentiment analysis is a very powerful tool with many commercial applications. However, it is very difficult to do well. Many claim to have a sentiment solution, but upon analysis, few in the market really do. Current solutions suffer from poor consistency, limited accuracy and lack of advanced deep learning techniques.

Humans can easily judge the polarity of text, unlike machines. We have developed an apex sentiment tool, using our proprietary neural network architecture, which enables real Natural Language Understanding (NLU) and emulates how humans judge the content and context of text.

Our solution provides consistent sentiment analysis of high or low-frequency content, in long or short format, across 100+ languages. And, we can do all of this with an impressive F1 score of 0.9443!

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  Named Entity Recognition

 

Valuable (business) information is buried in a largely text-based (79%) data explosion, most of which also resides in unstructured data on the web. The ability to extract, organize, analyze and connect large amounts of unstructured text data has become of paramount importance.

Extracting, classifying, and connecting entities via Named Entity Recognition (NER) technology plays an important role in sorting unstructured data and identifying valuable information. NER is a key foundational block for any information discovery pipeline and the basis for most Natural Language Processing (NLP) solutions.

We have built the new industry standard: Multilingual NER (in 100+ languages) that is unrivaled in accuracy vs. current ‘open source’ solutions and performs with an F1 score of 0.95.

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  Web Scraping

 

Web Scraping may sound easy, but it’s not! We have solved the 5 most prevalent issues faced by standard web scraping methods.

One key issue involves constant website layout changes. SEO improvements and UX/UI changes are delivered through HTML layout amendments. As a result, element locators that web scrapers are configured to in order to extract data, change and break the scraping process by extracting incorrect or no data. It takes a lot of manual effort to update these configurations and maintaining thousands of sources becomes near impossible.

We have fully automated the process of source reconfiguration to present you with a truly scalable, leading-edge web scraping solution. One that operates in 100+ languages and can scrape any text data from any web source in real-time.

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  Automated Text Classification

 

We have built an industry leading, multilingual, automated text classification capability that demonstrates superior accuracy (underpinned by Natural Language Understanding), uses no language translation layer (which significantly distorts the meaning of content) and is able to proces all length content, via our single, one stop shop, platform. 

These accuracy levels now mimic human understanding of any text.

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  BERT Semantic Similarities

 

Research into the possibilities of using the multilingual BERT model for determining semantic similarities of news content.

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  Semantic Similarity of
Arbitrary-length Text Content

Research on the specific features of determining the semantic similarity of arbitrary–length text content using multilingual Transformer based models.

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Read our latest Blog - Native vs. Translation Learn More >>