BigML reaches 200,000 users!

Posted by

Nowadays AI has become a mainstream concept thanks to the incredible media craze about the topic. Not a day goes by without sensational news warning that AGI is right around the corner and perhaps even secretly already here. The click baiting and investor FOMO is palpable. Historically, the AI space has a tendency to become very frothy periodically with loaded expectations that inflate private company valuations and stock prices which, in turn, attract even more attention and more dollars. It’s the typical technology hype cycle only on steroids.

At BigML, we have chosen to stay away from the all sizzle and little steak PR acrobatics all along. This meant sticking to our guns by promoting real life use cases of Machine Learning implemented on top of our platform, the keyword being Machine Learning and not AI

Today, we’re proud to share that BigML’s pioneering multi-tenant Machine Learning-as-a-Service offering has reached a new milestone of 200,000 users. What is of special note is the fact that this has taken place completely organically through word of mouth and online discoverability resulting in thousands of users across the globe finding valuable ways to gain insights from their data.

Since 2011, many factors have been driving this organic adoption of BigML:

  • From the get go, we embraced product-led growth by allowing anyone with a valid email to sign up for BigML to experience the software for themselves first hand eliminating the need to navigate big downloads, painful setup/installation routines or mandatory sales demos that do not necessarily reflect the prospect’s reality.

  • The continuous interest in Machine Learning both from education institutions and the business world fueled by continuous advancements in algorithmic research and software improvements that further stoke the fire. Fittingly, BigML platform has also continually improved making it more comprehensive. Whereas the early versions of BigML only featured simple decision trees, we now support many more resources like OptiML that automatically builds fine-tuned models and workflow automation options while abstracting infrastructure layer concerns from the end-user. More competent models and custom workflows translate to higher business impact.

  • Despite adding many new capabilities, our product development team has managed to do so without compromising the initial promise of making Machine Learning easy and beautiful for everyone. The core flow and architectural design of the BigML Dashboard and API have remained the same throughout.

  • Finally, we have built complementary services to accelerate platform adoption through a mix of affordable education programscertifications, and top-notch customer support.

At BigML, we remain as excited as Day 1 in serving our community with each passing year and helping Machine Learning drive more and more business efficiencies and innovations in almost every corner of the global economy.

Late to the party? Get started today…

Regardless of your level of Machine Learning experience, you can get started with the BigML platform by taking advantage of the following resources:

  • If you sign up for BigML you will receive a 14-day FREE Trial period that you can use to experience the platform first-hand.

  • FREE Education videos: Unlike the typical online Machine Learning courses that force feed you lots of theory, BigML education videos focus on the key concepts without getting too deep into the underlying math instead you get to learn about each BigML resource by example. To boot, these videos assume no prior background in Machine Learning.

  • BigML Lite for Small Businesses or Pilot Projects: Larger businesses usually require their own dedicated instances of BigML due to internal rules or preferences but for SMBs or a single business unit of a large organization, it makes more sense to deploy BigML Lite at a fraction of the cost of a standard private deployment and gain speed to market.

Now it’s your turn to take action and step into the amazing world of Machine Learning!

Leave a comment