Hi @gozmike, thanks so much for the kind words and question. We're providing developers the tools to make great conversation experiences that add real value to the companies they work for. We think we're just at the start of this great shift towards chat and natural language conversation, and we want to power it now and into the future. To make that happen, we started with the basics. We built a unique, conversational NLP system that works with messages in sequences instead of isolation, to better understand context and meaning. In end-user trials, people always wanted to go beyond questions and answers to a back-and-forth interaction. That's what we ultimately want to enable. And then we built all the tools that make training such as system possible. The machine learning underneath is sophisticated, and always changing as new techniques come out, but we abstract it away into simple developer tools to let companies focus on their core business, not arcane technology. Finally, we see conversational interactions emerging everywhere--from messaging apps to wearables to IoT--so we enable these applications to be built once and deployed everywhere.

@mishalaskin totally! Init.ai supports a few things on that front. Theres a built-in key-value store where you can store arbitrary data as a conversation progresses. This data can be stored both at the conversation level and at the user level. Since Init.ai lets you run custom code, you also have the flexibility to connect to any existing database, service, or a hosted API like Firebase or the AWS suite. We have a few things in the works as well: we are opening up a REST API soon for even more flexibility and will be enabling self-hosted logic (so you can use whatever database and programming language you'd like directly) as well. For message logs, there's a full debugger which shows you the conversation and how it was processed, and those logs can be exported for re-training. Plus, you can get messages in realtime through webhooks.

@phildionne thanks for the kind words. We agree and we are just getting started!

@moloneymike Thanks Mike! We see conversation as transformative in e-commerce and many many other industries. We're starting with automation, but our approach enables us to work with multi-user conversations and assist sales and support staff as well, so the possibilities are really endless.

@hickmanzackary Hey Zack, all products have their use cases. We built Init.ai to handle conversation flows, understand context (i.e. is “cool" a temperature or another word for “hip"), and integrate tightly with messaging, mobile, or web. We also have a strong developer workflow with versioning, integrated custom logic, etc. Plus soon you will be able to handle multi-user chats or even exchanges where bots monitor conversation and interject as needed. We think the Wit.ai team is great and hope you’ll try our product and let us know.

@markcwebster Hi Mark! Yes, the NLP was built from the ground up and is internal to our platform. Our strategy is to take the most recent advances from the machine learning field, combine and extend them in conversation-specific ways, and then abstract it all into a simple workflow to make it accessible to any company. For a few tasks we use open source tools (like parsing dates, etc) but all the core tech is based on various neural network types capable of handling ongoing conversation (and we're constantly evolving the implementation under the hood). We want to let companies reap the benefits of new language understanding research as it emerges, making the developer experience simpler while improving the end user experience -- all without the company needing to know anything about machine learning itself.

@keithbrisson Can't wait to play around with it.

@leftearpod Hi Jake! Quick answer: we tried building a conversational app on existing tools and none fully suited our needs! Long answer: we see a huge shift taking place right now towards people connecting with each other and with businesses though natural language chat. For consumers, usage of messaging applications has been growing like crazy. For businesses, demand for live chat has been steadily increasing and is dominating other channels for consumer interaction. We're also at this interesting inflection point where computers are starting to be able to join in the conversations. The possibilities there are really amazing -- especially around simplifying information retrieval as the world around us becomes more data-driven and complicated -- and just getting started. We recognized these trends starting a few years ago, when we realized the incredible potential to simplify interacting with complex datasets. And we thought long and hard about what the user experience would need to look like to make that work. Ultimately our goal is to enable simple, powerful, robust interactions that simplify consumers' lives. It's a very UX-driven approach to starting a company that had ended up developer oriented and focused on relatively serious tech.

@harryraymond Hi Harry, thanks for the question! We see chatbots as a subset of conversational interaction -- where the broader term can mean full automation (either natural language or with a more restricted button-based interaction), two or more people talking, or agents helping customers through live chat. We're targeting this broader space in general while enabling companies to build better, higher value bots. These interactions are happening everywhere: messaging platforms like Facebook, Telegram, Kik, etc, embedded with websites and mobile apps, and increasingly through voice on IoT devices. We help companies deploy apps on every channel.

@gkoberger thanks! Can't wait to see what you build. BTW -- we love hosting our docs on ReadMe.io. Great product.

@james_william interesting, what kind of work/bots are you developing? (if you don't mind me asking.)

@david_g Of course. I work for Orderly Health. We are building a conversational agent to help people make healthcare purchases.

@joekuriank Thanks Joe! Can't wait to see what everyone builds!