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The Generative Conversational AI Platform

We're proud to be considered the de-facto standard platform for conversational AI by our community of developers.

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Natural Language Understanding

Powerful language understanding APIs

We benchmark and fine-tune the latest NLP models specifically optimized for domain-specific, contextual and goal-oriented conversations.

Our Language Understanding engine is not only the most advanced, but also the easiest to use for developers.

NLU Documentation
1 2 3 4 5 6 7 8 9 10 11 12 import axios from 'axios' import trainData from './train_data.json' const hostname = "http://localhost:3200" const trainUrl = hostname + "/v1/train" const { data } = await axios.post(trainUrl, { ...trainData, password: "123456" }) console.log(data) // Prints { modelId: "fk2j-9394-0kfj-g385-76dj" }
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import axios from 'axios'import trainData from './train_data.json'const hostname = "http://localhost:3200"const trainUrl = hostname + "/v1/train"const { data } = await axios.post(trainUrl, {  ...trainData,  password: "123456" })console.log(data) // Prints { modelId: "fk2j-9394-0kfj-g385-76dj" }

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 import axios from 'axios' const hostname = "http://localhost:3200" const modelId = "<PUT MODEL ID HERE>" const predictUrl = hostname + "/predict/" + modelId const { data } = await axios.post(predictUrl, { password: "123456", utterances: ["Fly to Dubia please"] }) // data.spellChecked: "Fly to Dubai please" // data.intents: [{ name: 'book_flight', confidence: 0.98 }, ...] // data.slots: { destination: { canonical: "DXB", source: "Dubai" } } // data.entities: [ { entity: "airport", canonical: "Dubai" } ]
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import axios from 'axios'const hostname = "http://localhost:3200"const modelId = "<PUT MODEL ID HERE>"const predictUrl = hostname + "/predict/" + modelIdconst { data } = await axios.post(predictUrl, {  password: "123456",  utterances: ["Fly to Dubia please"]})//  data.spellChecked: "Fly to Dubai please"//  data.intents: [{ name: 'book_flight', confidence: 0.98 }, ...] //  data.slots: { destination: { canonical: "DXB", source: "Dubai" } }//  data.entities: [ { entity: "airport", canonical: "Dubai" } ]

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 { "language": "en", "intents": [ { "name": "book_flight", "contexts": [ "global" ], "utterances": [ "book flight", "book flight to [quebec](destination)", "let's go to [new york](destination) tomorrow", ], "slots": [{ "name": "destination", "entities": [ "airport" ] }] }, { "name": "hello", "contexts": [ "global" ], "slots": [], "utterances": [ "good day!", "good morning", "holla", "bonjour", "hey!", "hi", "hello" ] } ], "contexts": [ "global" ], "entities": [ { "name": "airport", "type": "list", "fuzzy": 0.9, "values": [ { "name": "JFK", "synonyms": [ "New York City", "New York" ] } ] } ] }
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{  "language": "en",  "intents": [    {      "name": "book_flight",      "contexts": [ "global" ],      "utterances": [        "book flight",        "book flight to [quebec](destination)",        "let's go to [new york](destination) tomorrow",      ],      "slots": [{ "name": "destination", "entities": [ "airport" ] }]    },    {      "name": "hello",      "contexts": [ "global" ],      "slots": [],      "utterances": [ "good day!", "good morning", "holla", "bonjour", "hey!", "hi", "hello" ]    }  ],  "contexts": [ "global" ],  "entities": [    {      "name": "airport",      "type": "list",      "fuzzy": 0.9,      "values": [        {          "name": "JFK",          "synonyms": [ "New York City", "New York" ]        }      ]    }  ]}

Robust Natural Language Processing, one simple API

Botpress exposes a simple API for training, and one for prediction. No need for an ML expert, pipeline configuration, or hyper-parameters.

Automatic spelling corrections to better understand users.

Id i'd
like to go to
Nwe Yrok New York
tomorrow
pleaze please
.

Accurately determine the user’s intent from their utterance.

I’d like to go to Barcelona tomorrow morning
book_flight 93%
.

Automatically identify the language being used.

I’d like to go to Barcelona tomorrow morning
English 93%
.

Like Airport code from a city name, or Date from ‘tomorrow morning’ - To create actional information from the user utterances.

I’d like to go to
New York AIRPORT:JFK
leaving from
Quebec AIRPORT:YQB
tomorrow morning DATE: 01/02/2022T08:00:00
Please

Automatically gather key information to complete the user’s request.

I’d like to go to
New York DEST
leaving from
Quebec DEPAR
tomorrow morning DATE
Please

Messaging API

Easily connect to any Messaging Channel

We actively maintain integrations with the most popular messaging services including Facebook Messenger, Slack, Microsoft Teams and Telegram.

Looking to embed a chat window on your website or in your mobile application? Botpress Webchat is a feature-rich chat that can be embedded anywhere.

Channels Documentation
Microsoft Teams logo
Facebook Messenger logo
Telegram logo
Slack logo

Conversation Studio

Automate multi-turn conversations

Building a conversational experience that customers will love is hard, even when equipped with the best NLU technology. That’s why we created the Conversation Studio: a powerful visual tool to build “awesome-by-default” conversations.

Built for Developers

Building a chatbot with Botpress feels no different than building any other type of application.

Git-friendly

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Everything is stored in files and made for easy Git versioning, from the NLU models to the workflows designed in the Conversation Studio and its content.

Extend with Javascript

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Developers can extend  Botpress by building custom integrations using our powerful Botpress SDK.

Botpress SDK Documentation

Enterprise-ready

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Botpress Enterprise provides out-of-the-box integrations with many enterprise software and industry-standard security protocols such as SAML and LDAP.

Learn more about Botpress Enterprise

Everything is stored in files and made for easy Git versioning, from the NLU models to the workflows designed in the Conversation Studio and its content.

Botpress Enterprise provides out-of-the-box integrations with many enterprise software and industry-standard security protocols such as SAML and LDAP.

Learn more about Botpress Enterprise

Case Studies

How businesses use Botpress to build better chatbots


“Botpress is the centerpiece of ASISPO, helping us to understand patients’ questions and to give them the right contextualized and personalized answer.”


-Thomas Gouritin, Co-Founder, ASISPO

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“Botpress provides a great backbone of the software solution that we provide for our customers.”

-David Mika, Innovation and Digital Transformation, VR Bank

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“The Botpress platform is extremely easy to use and has all of the necessary functionalities that we require to bring automations to our customers”

-Valerio Lombardi, CEO, engineon

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