Meet Newton X
Skyrocketing email productivity through AI
At Newton, we’ve always believed in creating products that embody zen through simplicity and ease of use. We think that people are far more focussed and productive when you equip them with a platform having the right balance of minimalism and functionality. Part of our philosophy has also been to help make the world a better place by re-imagining the future. And as we continue to evolve, our dedicated team endeavours to maintain this as our benchmark. One of the many ways we keep this practical is by incorporating valuable user feedback, research, and the latest in technology which allows us to keep pushing the envelope. Today we would like to introduce to you a new platform that (in our humble efforts) epitomizes email productivity. But how can minimalism step up to the next level without compromising on practical functionality? Actually, it was a no-brainer. We made minimalism meet AI. Now, all that is left is for you to meet X.
End of the age of Inbox
While others saw more panes in an email app as better for productivity, we saw that less is actually more. Eventually we saw that least is best. Thus, in a bold but decisive move, we decided to scrap the inbox. Completely. We saw enormous potential in the evolution of email into something more contemporary and more meaningful in today’s context. Over the years, technology and social behavior has been evolving. It was only a natural step to bring email up to speed with things. It was obvious that if we wouldn’t do it, somebody else eventually would. The impressive ability of our machine learning gave us the confidence to remove what most people would otherwise term as quintessential to email. The Inbox list was no longer required as Newton could now understand, sequence and anticipate the user’s desired actions with astonishing accuracy. However, this would all be possible only after a week of regular email usage with Newton. A week will give Newton enough cycles to study, in order to learn and determine the exact usage patterns.
We were able to take minimalism to the next level by only showing the most necessary and relevant information. The idea was to make all information and interface elements highly contextual. Opening the app instantly fires the state-of-the-art algorithm and displays a single go ahead button. This master button would simply present the most relevant emails that need to be read first. All this of course is only possible after the user’s pattern has been ascertained after using the app (It works immediately for users who have already been using Newton). As per our study, the AUC (Area Under Curve) was about 0.98, after the first week of usage. However, we observed that this continued to grow exponentially with further usage.
Cut-to-the-chase Conversations
In today’s time, the concept of reading is prehistoric. It has never really evolved since the time we invented written language. Our intention was to make understanding and assimilation of information faster. Understanding the crux of a message is key when it comes to emails (especially those important work ones). Newton X will allow you to glide through conversations by showing you no more than a gist of what is said. You will also be able to see paraphrasing where possible. It can even visually render quantitative data if any. This can be an incredibly powerful tool to have for today’s fast-paced, cut-to-the-chase lifestyles. Other than increasing productivity, it will also fill in the void of today’s growing need to tailor for short attention spans. Also, our groundbreaking algorithm promises to take the word spam out of the dictionary. We have verified repeated success of not finding any spam in emails while using Newton X. That in itself can be a staggering victory for most users.
Lean-back Compose
Imagine a compose interface that actually gives you a lean-back experience. It promises to make composing an email more distraction-free, smarter and much faster. This is by far our favorite feature. Not only can you use Newton to compose without a keyboard, but it can also help you to actually compose the email itself- Think word suggestions to sentence suggestions to even paragraph suggestions! What’s even better is that, it can be set to auto-reply to emails while you’re busy with more important tasks at hand. Honestly, we ourselves were surprised and thoroughly impressed when we started using it at first. The experience is heady and extremely gratifying (read: addictive). In fact, these days we have been exceptionally productive at work. As bots talk to bots, it gives us far more time to deal with the valuable human aspects of interaction at work. This, we believe, could be a disruptive and game-changing trend. It’s refreshing to know that you do not need to engage in routine and mundane conversations anymore.
The cost of brilliance
Beta testing for Newton X has been a complete success (Partly because, the beauty of minimalism also rests in the fact that it drastically reduces any occurrences of bugs). Our amazing team has put in months of love, sweat and tears into making this platform come to life. We truly believe that this platform can bring unprecedented value to the user’s life. All this of course comes for a price (we prefer to look at it as the confidence in the user for an exchange of value). We are offering Newton X at a subscription cost of $99.99 per year. Honestly, that’s a small price for the sheer value it brings to the table. This is something that will help keep us afloat with recurring development and server related overheads. Oh, and as a token of gratitude for our existing users, we’ll be offering the same at $85.99 per year instead. Like always, you can start a free trial before taking the plunge. So once again, we welcome the tech community and all users to come with an open mind and experience the future of email.
Just in case you’re curious, here’s what some influencers and visionaries had to say about our private beta:
Note: Our engineering team will be following up with another post giving a detailed explanation on how our machine learning was developed and how the various algorithms actually work.
