Essencient provides awesome NLP out of the box, delivering a new level of language understanding for developers of conversational systems.

Not only does it accurately identify actions with time scales and named entities, it also uniquely and crucially identifies whether someone is seeking or giving guidance. Guidance metadata permits you to understand the critical difference between, “Should I have pizza for dinner?”, or, “You should have pizza for dinner.” Clearly, a vital difference that any chatbot needs to understand. And if you need increased accuracy in a specific domain, then its universe can be tailored to specific needs.

Move over intent, guidance is here!



Essencient’s unique noise reduction engine, based upon identifying the absence of meaning so uninformative texts can be removed, can deliver an unmatched semantic analysis across any domain. There is no need to “train” any machines. We just process the raw data, remove the noise based on your topic of interest and give you the semantic analysis of the results. This is what we used to correctly predict the Brexit and 2016 US Election votes: we simply cleared away the noise and then identified those with a positive intention to vote one way or the other.


Sportscroud uses Essencient NLP to deliver insights into what sports crowds are saying on social media, delivering a valuable resource to sports fans and sports-focused companies such as gambling and sports brands.

Who Are My Advocates?

Identifying social media brand advocates has long been among a marketer’s aspirations. We all know that nothing carries cred like a happy, independent believer. And if that believer happens to have, say, a few hundred thousand social media followers, the boost to the brand can be enormous.

The corollary, sadly, is also true: make an enemy out of a highly-influential blogger, and you have a major PR issue on your hands.

Identifying both of them follows about the same course, so let’s stick with advocates. How can you figure out who is advocating on your behalf?

The answer lies in the combination of two “signals” that we identify in a text (in fact, the addition of one more can be a real refinement; more on that later).

The first, and obvious, signal is polarity (a.k.a. sentiment). It’s hard to consider someone an advocate if they don’t like you. So step one is to isolate posts where a positive, direct reference to your brand has been made. Essencient provides that information directly and with an industry-high level of accuracy.

Positive sentiment is not, on its own, a definite marker for advocacy. This is because advocates have more skin in the game than just having an opinion: they want you to have their opinion, too. So, they offer advice about what they advocate: they tell you to buy it, or consider it, or take some other (presumably constructive) action about it.

That’s as distinct from them just intending to do something themselves. “I like that new Beamer and I’m going to buy it” is a good thing, but not as strong an advocacy as “I like that new Beamer and you should buy it”. The offering of advice is a clear marker, with positive sentiment, of advocacy. Essencient, and only Essencient, provides the so-called Guidance signal that can identify advocacy.

There’s a good refinement available: Flamboyancy, another signal that Essencient (alone) provides. Flamboyancy measures how “flowery” the language is in a post. “I took a long, exciting test drive in that beautiful new Beamer.  You should buy it immediately!” is a far stronger endorsement and call to action than the last example above. Factoring Flamboyancy into the identification of advocates can only improve your results.

As I mentioned, the corollary to advocacy is detraction. Knowing who vocally dislikes your brand is pretty important, as well. And, of course, knowing who your competitor’s detractors are is a powerful insight as well. Identifying detractors differs from identifying advocates only in the sentiment being expressed (obviously, it will be negative for detractors).

So there it is: advocates and detractors identified. If you layer on reach or Klout scores, you can pinpoint who your greatest reward and risk bearers are and, through your engagement team, influence them appropriately.


Awesome NLP

There is nothing new about Natural Language Processing technology.

There are plenty of people doing it. Right?

So why is Essencient NLP awesome?

It gives you more

Essencient can not only uncover more meaning from text than any other system on the market. Its patented methods of parsing the structure of the text means it is more accurate. It’s also a rules-based system so no effort is required to teach it, nor is it restricted to niche domains.

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Knows what’s important

What makes it even more awesome is some clever tech that uses all the data the NLP uncovers to make a human-like decision if anything important is being said about any topic in the text it is reading.                .xx

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Proven to deliver

It correctly predicted the outcome of both Brexit and the 2016 US Elections, just by reading Twitter posts and accurately working out when someone was saying something important.  Turns out we decide to do things based on how we feel…who knew!

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Multiple Uses

Its awesomeness means we are have limitless choices on where we can use it to deliver the best quality data. We want to know about your use case! Essencient really can enable your business to do more.                                                           .

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Uses Cases

Just some of the ways you can use its awesomeness


Find those people who love you and those that don’t by identifying when people are giving guidance about a topic. Only Essencient can do this!


Remove the noise to leave just the really meaningful data. Text and topic level sentiment; intent levels, actions & timescales; guidance; flamboyancy, plus more.


Automatically curate unstructured text such as posts and blogs by identifying the level of importance given to each topic being discussed.


 Forget just getting sentiment and intent, our awesome NLP uniquely allows a chatbot to identify when someone is giving or seeking guidance on a topic as well.


With our unique noise reduction process, our awesome NLP makes it easier than ever to find more sales leads and better understand customer free-text responses so you can improve service and do more business.


Our noise-reduced NLP data is really great at finding those things people are giving or seeking guidance on with intent, such as naughty stuff like fraud or attempts to damage a brand’s reputation.


Licence Essencient’s semantic search patents to use our awesome NLP to make a search engine or text mining system awesome as well, by linguistically matching the query and content for high quality recall.


With Essencient Awesome NLP you won’t just know whether a customer is happy or sad, it will tell you what, why and when!

Unmatched Granular Analysis

Makes your text data more awesome

Simply send your unstructured text to our servers and get back an unmatched granular level of linguistic analysis data you can use for almost any purpose.

‘I need awesome natural language processing technology to make my solution really fly’

Essencient Awesome NLP Signals

Linguistic analysis provided includes:

  • Sentiment levels
  • Intent levels, actions and time scales
  • Guidance detection, seeking and giving  [ this is really awesome as it’s COMPLETELY UNIQUE to Essencient NLP ]
  • Entity detection
  • Language flamboyancy level
  • Slang detection
  • Contrast level

Essencient NLP is delivered as an easily integrated application programming interface (API) from our scalable servers running on Amazon Web Services. Analysis data is returned in a number of formats including XML, JSON and CSV.

High Quality Data

Awesome noise removal

The Problem – noise

NLP that is not awesome can deliver decent data, but to use what it produces is often expensive because humans have to wade through the noise to find the good stuff. If it’s a cheap NLP service then chances are it won’t think about the noise and will leave the consumer to deal with it. Putting that into perspective, the noise around a topic on social media can be as much as 95% of the associated text brought back by a normal query….. wading though that would not be fun!

The Solution – get rid of the noise

We created a human-like machine that uses the signals produced  by our awesome NLP to decide if anything meaningful is being said. We don’t want to wade through noise….that would be mind-numbingly boring!

Each topic our machine finds is given an importance score dependent on the strength of meaning surrounding that topic. You can then use this score to set the filtering threshold to get just the data you want. Trust us when we say you don’t want the noise!

Enables powerful solutions

Proven to deliver awesome results

We used our tech to predict two of the historical political events of 2016 as a test of just how awesome Essencient’s NLP really is.  We extracted posts from social media with a few simple queries and put Essencient to work at clearing away the noise to identify how people really felt. The results speak for themselves!

UK EU Referendum – Brexit

% of Vote Prediction

  • Leave
  • Stay In

Actual Result

Stay In

2016 US Election

Predicted Seats Won

  • Trump
  • Clinton
  • Undecided
  • Split

Actual Result

306 seats
232 Seats

Meet the Talent

Meet the Team

Mike Petit

Mike Petit

Co-Founder/CEO North America/Worldwide COO
Mike is the inventor of the Essencient advanced natural language API. His career spans 37 years in information technology, with a concentration in Natural Language Processing (NLP) over the last 16 years. He involves himself deeply in all aspects of product development.

Mike is a lifelong musician and cruising sailor, is trying to learn golf, and resides in West Palm Beach with Leena and Roger the dog.

Rob Lancashire

Rob Lancashire

Co-Founder/CEO UK
Rob is also an experienced executive director with 15 years of successful entrepreneurial involvement in the strategic and commercial development of technology companies, turning them in to performance businesses that have achieved award winning growth.

Rob is a Fellow of the Institute of Directors and has been awarded the Certificate in Company Direction from the IoD. His major influences are his wife and children as well as Gru from Despicable Me…..freeze ray!

Read the latest from the blog

The blog

Can Machines Beat The Pollsters?

Can Machines Beat The Pollsters?

The BBC’s Technology Correspondent Rory Cellan Jones discusses with Essencient Co-Founder, Rob Lancashire, why the company thinks it has cracked extracting accurate feelings from social media using its Natural Language Processing and Noise Reduction technology and how they are using this to look for trends in feelings of support towards the main Parties during campaigning for…

Essencient AI Tech Outdoes Pollsters, Predicting Trump Support Well Before the Polls Close

Just like the London Mayoral Campaign and Brexit, Twitter Voices Signaled the Result London, UK & West Palm Beach, FL, US November 18, 2016:  As it did with the London Mayoral Race and the EU Referendum, start-up Essencient’s patented AI technology could sense the momentum on Twitter in the US Presidential Election well before the…

Social Media Lead Mining Company Essencient Proves Its NLP Tech By Predicting EU Referendum To Within 0.3%

Essencient today announced that its Social Media Lead Mining technology, which uses patented Natural Language Processing (NLP) technology to remove noise around a chosen subject or brand, had proven accurate enough at mining meaningful posts on Twitter to be able to predict the UK EU referendum to within 0.3%.  The company said that as far…

Essencient Infographic – Demonstrating ROI on Social Media Marketing

Essencient Infographic – Demonstrating ROI on Social Media Marketing

We have put together this infographic with some key facts around the challenge marketing leaders have in trying demonstrate ROI on social media marketing spend. Enjoy!

Lead Generation from Social Media – getting rid of the Noise within the noise to leave the needles

I read a really good article recently about how important the construction of the search query is when pulling data out of social media platforms such as Twitter. It’s definitely also our experience at Essencient that if you don’t get this right, you will pull back a large amount of noise that is just not…

Who Are My Advocates?

Identifying social media brand advocates has long been among a marketer’s aspirations. We all know that nothing carries cred like a happy, independent believer. And if that believer happens to have, say, a few hundred thousand social media followers, the boost to the brand can be enormous. The corollary, sadly, is also true: make an…

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