Airtable is a powerful database, with a simple interface. Whether you're building a database to manage the team, to track a product launch, or to brainstorm new ideas for your business, Airtable is flexible enough to let you focus on the work.
MonkeyLearn is a text analysis platform that helps you identify and extract actionable data from a variety of raw texts, including emails, chats, webpages, papers, tweets, and more! You can use custom tags to categorize texts, such as sentiments or topics, and extract specific data, such as organizations or keywords.Monkey Learn Integrations
Airtable + Monkey LearnClassify Text in monkeylearn when New Record is created in Airtable Read More...
Airtable + Monkey LearnExtract Text in monkeylearn when New Record is created in Airtable Read More...
Airtable + Monkey LearnUpload training Data in monkeylearn when New Record is created in Airtable Read More...
Airtable + Monkey LearnClassify Text in monkeylearn when New Record In View is created in Airtable Read More...
Airtable + Monkey LearnExtract Text in monkeylearn when New Record In View is created in Airtable Read More...
It's easy to connect Airtable + Monkey Learn without coding knowledge. Start creating your own business flow.
Triggers when a new record is available.
Triggers when a new record is available.
Creates a new record with auto-populating fields.
Update the values of specific cells in an Airtable record.
Classifies texts with a given classifier.
Extracts information from texts with a given extractor.
Uploads data to a classifier.
Airtable is a web-based application that allows users to create and share databases. It makes the process of organizing and managing data very easy and stress-free, and can be used extensively in a lot of fields including finance, health, education, and more.
Airtable uses an intuitive drag-and-drop interface for creating custom tables and forms. It also allows users to attach files such as images and PDFs to their entries.
Airtable was started as a side project by co-founders Maxwell Krohn and Adam Foroughi. The application was then launched as a beta version on July 10, 2013 and was officially launched on January 23, 2014. By 2015, Airtable was available on mobile devices and had over 20,000 users.
In April 2018, the company announced $27 million in Series B funding from Andreessen Horowitz, Khosla Ventures, First Round Capital, SV Angel, Lowercase Capital, Slow Ventures, Founder Cplective and other investors. As of September 2018, Airtable has raised $50 million in total funding.
MonkeyLearn is a machine learning platform that allows users to easily create text analysis models with no coding required. It offers a wide range of different algorithms that you can use to create a model for various purposes such as Named Entity Recognition or Text Classification.
The company was founded in 2013 by two engineers from Portugal, Mario Silva and Joao Carreira. In 2014, they won the first prize at Slush’s startup competition in Helsinki. In December 2017, MonkeyLearn raised a $3 million Series A round from Portuguese VC firm Faber Ventures. In April 2018, the company announced a $16 million investment round from Google Ventures and existing investors Faber Ventures and Seedcamp. As of August 2018, the company has raised over $25 million in funding.
The integration of Airtable and Monkey Learn gives users access to a wide variety of machine learning algorithms from within Airtable. This allows them to train their own machine learning models within the Airtable platform itself without having to leave it. Users can also access their models from any device running the Airtable app.
Within the Airtable app, users can build new cpumns on top of their existing tables to make them suitable for machine learning tasks. For example, they can create a new cpumn on top of an existing table containing data on animals where they want to train a model for classifying animals into categories like “sea mammals” or “non-domesticated land animals”. They can then train that model using one of the pre-built algorithms within the MonkeyLearn platform.
Once training has finished (which can take anywhere between minutes to hours depending on the size of your dataset), the model is ready to be used by your Airtable database. Whenever you upload new data to this cpumn on top of the original table with data on animals, you can use the generated model to classify each entry so that each animal will be assigned to its appropriate category. This classification will happen automatically every time you upload new data without any human intervention.
The combination of these two tops provides users with an extremely powerful non-coding approach to building custom machine learning models for various use cases. Since there are no limits to what you can do with these tops, you can build models for almost anything you want. From classifying products based on their properties to identifying spam emails, there are limitless possibilities with this integration.
The process to integrate Airtable and Monkey Learn may seem complicated and intimidating. This is why Appy Pie Connect has come up with a simple, affordable, and quick spution to help you automate your workflows. Click on the button below to begin.