MonkeyLearn leverages machine learning for rapid text analysis

Contxto – If you are seeking a tech solution for rapid tech analysis, then MonkeyLearn could have your answer. Used by tech support teams, product management officials and developers alike, users can save a week’s worth of work and perform meticulous tasks in just a few hours.

Leveraging machine learning, the software analyzes text data to extract topic, sentiment and intent keywords. Plus, clients can personalize the software to best fit their company’s needs.

MonkeyLearn’s text analyzer

MonkeyLearn is a machine learning-powered software that offers both topic and sentiment analysis behind the text. If you’re interested in natural language processing, this could be the platform for you.

“MonkeyLearn allows software developers and SMEs to easily extract and classify information from text within their applications,” said co-founder Raul Garreta in an interview. 

Fortunately, the platform is accessible to everyone. There’s no need to be an expert programmer or analyst, either. Regardless of your tech competency, MonkeyLearn’s graphic interface makes it efficient and friendly for every user.

It is a tool that, in turn, is flexible and customizable. A user can choose which algorithm to use as the different parameters to train a model.

The MonkeyLearn Team

How does it work

Natural Language Processing together with machine learning technologies are what makes MonkeyLearn so special. It literally lets you teach the software how you want your data to be categorized.

Algorithms learn from experience. Therefore, to teach them to analyze text automatically it is necessary to show examples of texts already analyzed. Once you have a sufficient number of examples, the model can draw conclusions on its own.

Federico Pascual COO and co-founder of MonkeyLearn

Founded in 2014 by Ernesto Rodriguez, Federico Pascual, Martín Alcalá Rubí, Raul Garreta, the startup offers solutions for developers, support and product teams. Over the platform, you can find pre-trained models for different tasks. This way, customers can start using machine learning from the start while gradually familiarizing themselves with the software.

All in all, it offers an easy-to-use interface so that businesses can train their own classifier or extractor to get the task done. In other words, program the machine to extract the desired data, tags and criteria. Once you create the machine learning model, it’s just a matter of putting it to work.

Personalization

On the plus side, the startup is aware that each organization is different. That’s why personalization is one of the most valuable assets the platform provides to clients.

“Custom models are created by the user who must provide examples to the algorithm to train it,” shared the MonkeyLearn team with Contxto.  “These models are usually more accurate since they are trained with the criteria that the user wants to use.”

Even better, if you a seasoned programmer, there’s an API that you can integrate, too! Because of this, it’s possible to use different language programming models like Python, Ruby on Rails, Javascript, PHP and Java. Pretty neat, if you ask me.

Nevertheless, the best part is that the whole process is pretty simple.

3 simple steps

1. Connect your text data. Upload CSV/Excel files or connect through direct integrations, API or Zapier. 
2. Turn your text into tags. Use text analysis models to tag your text. Create your own models or choose between the pre-made ones. 
3. Put your tags to work. Create new information about your business or new workflows in your apps using the tags.

Extract and classify text

MonkeyLearn allows companies to both extract and classify text in order to make an accurate and complete analysis of all the data.

Essentially, classifiers group texts into a category or tags based on the content. In terms of relevant uses, this tool could be extremely helpful when analyzing and responding to client feedback.

“The classifiers are useful to detect if customers are talking positively or negatively (sentiment analysis),” shared MonkeyLearn with Contxto.

Other uses include understanding the topic of discussion (topic analysis), detecting if responses are intended for purchase (intent analysis), among other applications.

Differently, extractors grasp the most important information within the text. These could be keywords as well as names of people, companies and brands. Additionally, information regarding emails, sale prices and other data can also be retrieved.

So basically, with MonkeyLearn it’s possible to find out anything you need about your clientele and audience! After all, customer satisfaction is key to a successful business. Thankfully, MonkeyLearn is here to make that easier.

A spin-off Startup 

MonkeyLearn emerged as a Tryolabs spin-off.

Raúl Garreta, co-founder and CEO at MonkeyLearn

Yup, that’s right, MonkeyLearn began as Tryolabs, another super successful Latin American startup, noticed a similar business opportunity.

Tryolab’s co-founder Raúl Garreta, who is also MonkeyLearn’s co-founder and CEO, identified the need for clients to utilize machine learning for text analysis. 

“Every time we worked on a project for a new client, we had to start over. This included creating the necessary infrastructure, training models from zero, etc.,” shared Garreta.

“From that came the idea of creating a machine learning platform applied to text analysis that was adaptable enough to be used in different situations and that met various needs.”

That’s how in 2013 Garreta contacted Federico Pascual, now COO and co-founder, to start developing MonkeyLearn’s commercial concept. Needless to say, this ideation turned out to be quite successful.

“Prior to our first meeting, I didn’t know anything about machine learning. However, as I conducted my research, I found myself growing more and more interested in the potential of Natural Language Processing,” shared Pascual.

During that same year, MonkeyLearn also collaborated with Gonzalo Saveedra, the startup’s head of engineering.  

 Business model

Currently, the MonkeyLearn business model involves a software service (SaaS) with a monthly freemium subscription. Various memberships exist, so there is plenty to choose from.

Free plan

This is MonkeyLearn’s unlimited-time offer! It’s perfect for those clients looking to delve into the text analysis world. Check out all the perks this plan has:

• Queries: 300 queries (analysis) per month.
• Custom Models: Up to 1 custom model.
• API speed: Low. Up to 6,000 texts for analysis per minute.
• Model size: small. Classifiers can be trained with up to 1,000 training examples and extractors with up to 150 examples.
• Support: low priority.

Team Plan

After falling in love with the free version, then upgrading is a must. This more advanced package has even more material to offer. For example, more abilities to analyze queries with increased speed and train models with more samples.

• Queries: 1,000 queries (analysis) per month.
• Custom models: up to 3 custom models.
• API speed: medium. Up to 6 thousand texts for analysis per minute.
• Model size: medium. Classifiers can be trained with up to 1000 training examples and extractors with up to 150 examples.
• Support: low priority.

Business plan

Now, this is the plan everybody should have, at least in my opinion. It offers premium features, such as SLA, workflows, and analytics.

Nevertheless, the best part is that it is 100 percent customizable for each customer’s needs. Additionally, when it comes to support, these subscription members are the top priority.

What is MonkeyLearn doing now? 

After years of working on its product-market fit, MonkeyLearn found the perfect way to scale and produce its solution. 

Nowadays, MonkeyLearn has tech unicorns from Silicon Valley as customers. Needless to say, its client portfolio is growing rapidly. Plus, the startup recently closed a seed round that will allow it to grow the team, expand the business and better the product. 

Plans for the future

With a very promising future ahead of it, the startup has two main priorities.

The first of them is to make the platform even friendlier. Seeking a quality UX, MonkeyLearn wants to make the platform even easier and faster to use. Plus, new functionalities may be on their way.

“We are believers that low complexity, monotonous and boring work should not be done by people, machines must do it,” said MonkeyLearn. “People should focus on tasks of greater added value, which require more knowledge and experience.” 

As a result, partners can automate processes and save resources, which certainly provides added value.

Furthermore, the startup seeks to increase integrations with other companies. Even though these two are the main plans for the future, customer satisfaction is always of importance.

By listening to its customers, not only is MonkeyLearn constantly generating new ideas, but also innovating.

Funding

Over the years, MonkeyLearn has raised several investment rounds. The most recent one was a seed round in July 2019 with Uncork Capital and Bling Capital as investors.

It has also worked with angel investors like Des Traynor and Eoghan McCabe of Intercom. Plus, Henry Ward from Letter and Howie Liu representing Airtable, Alex Solomon from PagerDuty, as well as Anthony Goldbloom from Kaggle and Google.

Before that, MonkeyLearn had already received another three rounds of investment. These pre-seed rounds were led by investors such as 500 Startups together with other American, Swedish and Uruguayan angel investors.

Thoughts

In my opinion, MonkeyLearn‘s software will definitely help your company get the insights it needs to improve its service. The best part of it all is there’s no need to spend days or even weeks reading or analyzing complicated texts.

For many, this reduces long processes to just a few hours. Clearly, MonkeyLearn has developed quite the solution.

If you would like to know more go on and visit MonkeyLearn’s website!

-CZ