Unicorn NLP

Language Understanding APIs

Unicorn NLP

Language Understanding APIs

The path to the summit has never been so easy.

Unlock the power hidden in reviews and other user-generated content.

Apply Cognitive APIs to your data and get human-like quality at the cost of automation.

The path to the summit has never been so easy.

Unlock the power hidden in reviews
by combining the most powerful AI for Reviews with your brilliant ideas,
and your business will become the next Unicorn.

Unicorn NLP develops human-like Cognitive APIs for reviews and other user-generated content.
More profound than Watson and more accurate than Google.
It is also much more cost-effective and you can get the on-premise version with 0 cents / text.

It is the next-generation of Keywords, Categories, Concepts and Sentiment Analysis.
Our technology detects more high-quality information from reviews than these services combined.
That is why it is called Sentiment Analysis 2.0.

Explore Cognitive APIs

Discover unique value in your data by applying human-like Cognitive API

Each product is a set of Semantic Models designed for a specific domain (Healthcare Data, App Reviews, Hotels Reviews, Restaurants Reviews, etc.). Think of it as a Cognitive APIs that was trained, tested and re-tested on millions of reviews and other texts, and it is optimized to your data.

We do not apply general models trained on any content and then adapt it to a specific domain. Each type of review is different. Drug reviews differ a lot from Hotel Reviews and have less than 25% in common. Even Apartment Reviews differ in 40% from Hotel Reviews. That is why, to provide a new level of quality, We designed and built from the ground-up a set of dedicated semantic models that are optimized separately to different domains (Drug/Patient Reviews, Hotel Reviews, Restaurant Reviews, NPS & Surveys, etc.).
With this unique approach, we cover more than 90% of the information/facts contained within the review. Testing it on hundreds of thousands of reviews, we achieved very high accuracy (precision=90-95%)

We call it Human-like Analysis because with these parameters we achieve the same quality as detected by skilled analysts (humans). It opens up a lot of new functionalities that can be easily combined with your product without any post-processing, additional training or configuration to your data.

See products

With the right Cognitive API you are able to provide deep tech that even a child can understand

What this technology can do

and much more. Click below and see examples of how our tech can be applied to the travel domain.

See more about what this technology can do

You get ready-to-use technology that you can integrate with your product in days.

Ready-to-use technology, no configuration/expertise needed

You can use this technology as a standalone without any linguistic or machine learning skills, or augment your already functioning machine learning solutions.

You do not get a "domain-independent" solution that sometimes works, sometimes doesn't, and it is up to you to configure it to your data. We specialize in making Cognitive APIs for user-generated content which are easy to use. We hide all the complexity inside and provide ready-to-use data on the output in a well-organized JSON.

Easy-to-use output with a human-like accuracy

Each product was designed, built, and tested on hundreds of thousands of reviews and other texts from a specific domain. You do not need to set any confidence score, apply any post-processing or train these models to your data. We undertake to ensure that our technology works at a very high level with your data.

All information detected by our technology makes sense and is simple and accurate enough to display to the user or used to provide new functionalities.

Comparison of our technology vs. Sentiment Analysis & Concept/Keyword/Topic Analysis

1. Sentiment Analysis & Concept/Keyword/Topic Analysis - Current technology available

"Breakfast was tasty" => Breakfast: positive
"Breakfast was huge" => Breakfast: positive
"Breakfast was not included" => Breakfast: negative
"Breakfast was very tasty but limited choices" => Breakfast: neutral
"Breakfast was delicious but you had to pay extra" => Breakfast: neutral

2. Sentiment Analysis 2.0 - Unicorn NLP (new Cognitive APIs)

"Breakfast was tasty" => Breakfast: tasty
"Breakfast was huge" => Breakfast: big portions
"Breakfast was not included" => Breakfast: not included
"Breakfast was very tasty but limited choices" => Breakfast: tastypoor, limited
"Breakfast was delicious but you had to pay extra" => Breakfast: tastynot included

Language has colors. Do not reduce it to black & white. Read more...


Test it on your dataset

What's next