Alternatives to Dialogflow logo

Alternatives to Dialogflow

Amazon Lex, Microsoft Bot Framework, IBM Watson, TensorFlow, and Telegram Bot API are the most popular alternatives and competitors to Dialogflow.
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What is Dialogflow and what are its top alternatives?

Give users new ways to interact with your product by building engaging voice and text-based conversational apps.
Dialogflow is a tool in the Chatbot Platforms & Tools category of a tech stack.

Top Alternatives to Dialogflow

  • Amazon Lex

    Amazon Lex

    Lex provides the advanced deep learning functionalities of automatic speech recognition (ASR) for converting speech to text, and natural language understanding (NLU) to recognize the intent of the text, to enable you to build applications with highly engaging user experiences and lifelike conversational interactions. ...

  • Microsoft Bot Framework

    Microsoft Bot Framework

    The Microsoft Bot Framework provides just what you need to build and connect intelligent bots that interact naturally wherever your users are talking, from text/sms to Skype, Slack, Office 365 mail and other popular services. ...

  • IBM Watson

    IBM Watson

    It combines artificial intelligence (AI) and sophisticated analytical software for optimal performance as a "question answering" machine. ...

  • TensorFlow

    TensorFlow

    TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API. ...

  • Telegram Bot API

    Telegram Bot API

    Bots are third-party applications that run inside Telegram. Users can interact with bots by sending them messages, commands and inline requests. You control your bots using HTTPS requests to our bot API. ...

  • Messenger Platform

    Messenger Platform

    With bots and live-messaging tools, you can create a custom experience for your unique audience. ...

  • Api.ai

    Api.ai

    API.AI is a natural language understanding platform that makes it easy for developers to design and integrate intelligent, robust conversational user interfaces into mobile, web applications, and devices. ...

  • Botkit

    Botkit

    It is an open source developer tool for building chat bots, apps and custom integrations for major messaging platforms. ...

Dialogflow alternatives & related posts

Amazon Lex logo

Amazon Lex

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Build conversational voice and text interfaces, using the same deep learning technologies as Alexa
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PROS OF AMAZON LEX
  • 7
    Easy console
  • 4
    Built in chat to test your model
  • 2
    Easy integration
  • 2
    Great voice
CONS OF AMAZON LEX
  • 3
    English only

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Arthur Boghossian
DevOps Engineer at PlayAsYouGo | 3 upvotes 路 38.7K views

For our Compute services, we decided to use AWS Lambda as it is perfect for quick executions (perfect for a bot), is serverless, and is required by Amazon Lex, which we will use as the framework for our bot. We chose Amazon Lex as it integrates well with other #AWS services and uses the same technology as Alexa. This will give customers the ability to purchase licenses through their Alexa device. We chose Amazon DynamoDB to store customer information as it is a noSQL database, has high performance, and highly available. If we decide to train our own models for license recommendation we will either use Amazon SageMaker or Amazon EC2 with AWS Elastic Load Balancing (ELB) and AWS ASG as they are ideal for model training and inference.

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Microsoft Bot Framework logo

Microsoft Bot Framework

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Connect intelligent bots that interact via text/sms, Skype, Slack, Office 365 mail and other popular services
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PROS OF MICROSOFT BOT FRAMEWORK
  • 16
    Well documented, easy to use
  • 2
    Sending Proactive messages for the Different channels
CONS OF MICROSOFT BOT FRAMEWORK
  • 1
    LUIS feature adds multilingual capabilities

related Microsoft Bot Framework posts

IBM Watson logo

IBM Watson

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A question-answering computer system capable of answering questions posed in natural language
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PROS OF IBM WATSON
  • 2
    Api
  • 1
    Prebuilt front-end GUI
  • 1
    Intent auto-generation
  • 1
    Custom webhooks
  • 1
    Disambiguation
CONS OF IBM WATSON
  • 1
    Multi-lingual

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TensorFlow logo

TensorFlow

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Open Source Software Library for Machine Intelligence
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PROS OF TENSORFLOW
  • 24
    High Performance
  • 16
    Connect Research and Production
  • 13
    Deep Flexibility
  • 9
    Auto-Differentiation
  • 9
    True Portability
  • 2
    Easy to use
  • 2
    High level abstraction
  • 1
    Powerful
CONS OF TENSORFLOW
  • 8
    Hard
  • 5
    Hard to debug
  • 1
    Documentation not very helpful

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Conor Myhrvold
Tech Brand Mgr, Office of CTO at Uber | 8 upvotes 路 1.2M views

Why we built an open source, distributed training framework for TensorFlow , Keras , and PyTorch:

At Uber, we apply deep learning across our business; from self-driving research to trip forecasting and fraud prevention, deep learning enables our engineers and data scientists to create better experiences for our users.

TensorFlow has become a preferred deep learning library at Uber for a variety of reasons. To start, the framework is one of the most widely used open source frameworks for deep learning, which makes it easy to onboard new users. It also combines high performance with an ability to tinker with low-level model details鈥攆or instance, we can use both high-level APIs, such as Keras, and implement our own custom operators using NVIDIA鈥檚 CUDA toolkit.

Uber has introduced Michelangelo (https://eng.uber.com/michelangelo/), an internal ML-as-a-service platform that democratizes machine learning and makes it easy to build and deploy these systems at scale. In this article, we pull back the curtain on Horovod, an open source component of Michelangelo鈥檚 deep learning toolkit which makes it easier to start鈥攁nd speed up鈥攄istributed deep learning projects with TensorFlow:

https://eng.uber.com/horovod/

(Direct GitHub repo: https://github.com/uber/horovod)

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In mid-2015, Uber began exploring ways to scale ML across the organization, avoiding ML anti-patterns while standardizing workflows and tools. This effort led to Michelangelo.

Michelangelo consists of a mix of open source systems and components built in-house. The primary open sourced components used are HDFS, Spark, Samza, Cassandra, MLLib, XGBoost, and TensorFlow.

!

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Telegram Bot API logo

Telegram Bot API

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HTTP-based interface created for developers keen on building bots for Telegram
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PROS OF TELEGRAM BOT API
  • 9
    Integrating with other services
  • 7
    Getting customized notifications and news
  • 5
    Creating custom tools like GitHub bot
  • 4
    Easy setup
  • 4
    Creating private/public bots
  • 4
    Great documentation which is easily understandable
  • 1
    Easily manageable
CONS OF TELEGRAM BOT API
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    Messenger Platform logo

    Messenger Platform

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    Tools to help you build your bot and reach 900 million people around the world
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    PROS OF MESSENGER PLATFORM
    • 1
      Clean and Simple Communication
    CONS OF MESSENGER PLATFORM
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      Api.ai logo

      Api.ai

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      Conversational interface platform for apps, devices, bots, and services.
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      PROS OF API.AI
      • 3
        55
      CONS OF API.AI
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        Botkit logo

        Botkit

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        Building Blocks for Building Bots
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        PROS OF BOTKIT
        • 2
          Relatively easy to understand and help/active community
        CONS OF BOTKIT
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