Solution built for speed of execution

We carefully considered what the best solution for conversational AI would look like – and then built it. A productive studio combined with a flexible modular architecture powered by our SDK.
‍Start building chatbots in less than a minute.

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Conversation Flow Manager

Manage, update and extend how a chatbot’s conversation should progress based on user inputs.

Third party integrations

Botpress features connectors to all the major chat platforms that you’d expect. See supported platforms.

Multiple language engines

Use the natural language understanding solution that best suit you—no need to be tied to one option.

Content & flow separation

Content and flow management are decoupled to allow management by different teams.

Analytics

Assess user engagement with your chatbots, identify successes to build on, and spot failures to correct.

Human in the loop

Botpress allows human agents to take over the conversation when it moves beyond the chatbot's capabilities.

Modular design

Assemble your chatbot from our collection of specialized, open-source modules. You can also build your own module.

Graphical interface

You shouldn’t have to choose between CLI or GUI. Every feature is available as an API and as a rich graphical interface.

Extensible

Easily build more components for chatbots, and add to the growing pool of common features that are available to developers.

All
in one

Botpress is not competing with other tools. It’s a modular platform that integrates with other popular tools and frameworks easily.

Start Building with Botpress

Architecture
philosophy

Because Botpress doesn’t compete with other platforms, it’s possible for developers to mix and match functionality. For example, you can use the analytics module offered by Botpress, or whatever analytics modules have been created by third parties for their own platforms. You’re not locked in to the Botpress modules—and you’re free to create your own analytics modules, or add custom analytics to the modules you’re already using off the shelf.

We believe this type of open/shared solution is necessary for rapidly creating robust tools. In fact, it’s the normal way that software development ultimately progresses for any new technology, as its market matures. A good analogy is CMSes, which were developed for websites so that developers didn’t have to code everything from scratch—yet still had total control over the design process. Botpress is the equivalent in bot development that a CMS is for a website.

An added advantage of this philosophy in the chatbot space is that any key off-the-shelf feature can be changed by the developer. Even the connectors are open for developers to adapt to the underlying chat platforms, should they need that. We see this openness and modular approach as a part of our overall philosophy of providing the tools needed to create the world’s best chatbots.

In part, this means taking advantage of best practices and tools that are already well-established in software development. Chatbot development of course presents some unique challenges—but these challenges can be solved within the existing software solutions.

Code
tools

Developing software using code is the central activity in software development, and it is no different for chatbots. Not only does building bots with code offer developers unlimited flexibility—it also allows them to make use of the myriad software development tools already available for creating and managing code.

That’s not to say that visual tools aren’t necessary in the process of coding—they are. Many visual tools are essential for making the process of coding efficient. But these should be added to the process, rather than replacing it. Building a chatbot using code has many advantages over using visual tools exclusively—including allowing for professional source code control, and the reuse of functionality. It is impossible to source control graphical-interface-based, no-code tools, because there are no source control concepts such as forking or pull requests built into them. Moreover, reuse of functionality is difficult between bots on these platforms, because copy and paste operations don’t necessarily work.

Solving the content and flow
challenge with Universal Message Markdown

One of the unique challenges for chatbot development is how to deal with the creation and management of content and flow—both in terms of rule-based chatbots, and NLP-based ones. The flow is the rules that determine the path of the conversation, whereas the content is the words and other media that is displayed to the user.
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To build a professional solution for developing chatbots, it’s best to separate the content and flow so they can be managed by different teams. But beyond this pure content and flow separation, another problem is that the content needs to be slightly different on each chat platform to take advantage of the best features of each. The best chatbots will obviously need to make the best use of the features available on every platform.

We solved this problem by inventing Universal Message Markdown (UMM) which allows content managers to not only take care of their content in a professional, transparent and source-controlled way, but also to easily customize it for different messaging platforms, A/B testing, and languages.

We created UMM to be as simple to use as possible—so as part of this effort, we also created visual tools to assist content managers in creating and editing the markup. This allows them to see a visual representation of what they are writing, in text, and in real time. It further simplifies the process of creating great chatbots.

Solution built for speed of execution

Conversation Flow Manager

Third party integrations

Multiple language engines

Content & flow separation

Analytics

Human in the loop

Modular design

Graphical interface

Extensible

All
in one

Architecture
philosophy

Code
tools

Solving the content and flow
challenge with Universal Message Markdown

Product

Solutions

Resources

Company

Solution built for speed of execution

Conversation Flow Manager

Third party integrations

Multiple language engines

Content & flow separation

Analytics

Human in the loop

Modular design

Graphical interface

Extensible

Allin one

Architecturephilosophy

Codetools

Solving the content and flowchallenge with Universal Message Markdown

Product

Solutions

Resources

Company

All
in one

Architecture
philosophy

Code
tools

Solving the content and flow
challenge with Universal Message Markdown