Launching Built-in NLP for Messenger and Sunsetting Bot Engine (beta)

27 Jul 2017 entities, news

We have a few updates to share with you today - most exciting is the launch of Built-in NLP for Messenger, launching with Messenger Platform 2.1 just released today.

By testing and learning from our Bot Engine beta, we determined that it made the most sense to refocus on pure NLP to make it accurate, reliable and scalable for everybody. As a result, we’re sunsetting Bot Engine and will deprecate the Stories UI for new apps starting today. We will also stop serving requests to the associated /converse endpoint on February 1, 2018.

Built-in NLP

Over the past year, we have received a lot of questions and feedback on how to integrate Wit.ai NLP into bots for Messenger. Currently, if you are leveraging an NLP API, it is an additional layer that adds both latency and complexity. We believe almost every bot should use NLP in some way to create delightful experiences. Today, we are excited to make this easier by integrating Wit directly into the Send/Receive Messenger API.

When Built-in NLP is enabled, it automatically detects meaning and information in the text of messages that a user sends, before it gets passed to the bot. This first version can detect the following entities: hello, bye, thanks, date & time, location, amount of money, phone number, email and a URL. This is the first step in bringing NLP capabilities to all developers. Learn more.

Sunsetting Bot Engine

Most of you may know that we created Bot Engine at the beginning of 2016 to help developers build text-based conversational bots. At that time, NLP was still new to many, the bot ecosystem was small and developers did not have the tools we have today (e.g. Chatfuel, Botpress, etc.).

Bot Engine was designed for complex text-only transactions because messaging platforms did not have GUI (Graphical User Interface, like webviews) elements then. The idea was to replace forms with conversations. However for many use cases, a dialog does not provide the pleasant user experience you get with a GUI (constant visual feedback, ability to modify previous choices, etc.).

That’s why in the last year, the ecosystem has shifted towards a mix of NLP and GUI elements to produce a user experience on par with native and web apps. For instance, Messenger has introduced quick replies, menus and even web view. As a result, Bot Engine and its emphasis on text-only bots has become somewhat obsolete.

Upon reviewing the top apps using Stories, we’ve mainly seen apps using 1-turn stories. These FAQ-like apps can easily be achieved with our NLP endpoint (/message) because it’s about understanding the question and then mapping the user intent to an answer that can be stored outside of Wit. Example here. These apps don’t need the power and complexity of Stories (having to do 4 calls on average to /converse to get to an answer as opposed to 1 single call for /message). The recommended migration is to use /message and code on your side to manage the conversation and link to the answers that would be stored in your database.

The numbers talk for themselves. Since the launch of Bot Engine in 2016, we have seen our community grow from 20,000 to more than 100k developers. Most of them build bots for Messenger, Slack, Telegram, and other platforms and use our NLP API (/message). Currently, more than 90% of the Wit API calls are coming from our NLP API.

This is why we are deprecating Bot Engine and the Stories UI today, and will stop serving requests to the associated /converse endpoint on February 1st 2018 to give developers enough time to migrate affected apps. Please check our GitHub tutorial for more details.

We want to make NLP work really well, at scale. This lets developers focus on building the best possible user experience, be it conversational, or hybrid NLP/GUI. This is why we have scaled our /message endpoint to make it easy to programmatically interact with Wit.

Moving forward, we are working on:

  • improving the quality of our NLP by leveraging cutting-edge algorithms developed at Facebook
  • making it easy to share, reuse, and collaborate on entities from the community
  • helping other platforms leverage our NLP API behind the scenes

As always, feel free to reach out if you have any questions, comments, or suggestions.

Team Wit