What is Dialogflow and what are its top alternatives?
Dialogflow is a conversational AI platform that allows developers to build and deploy chatbots and virtual agents across various channels. It leverages natural language processing and machine learning to understand and respond to user queries in a conversational manner. Key features include multi-language support, integration with popular messaging platforms, and the ability to create custom intents and entities. However, Dialogflow has limitations such as pricing based on usage and lack of advanced customization options.
- Microsoft Bot Framework: Microsoft Bot Framework is a comprehensive tool for building and deploying bots across multiple channels. Key features include extensive language support, integration with Azure services, and robust analytics capabilities. Pros include tight integration with Microsoft ecosystem, while cons include a steeper learning curve compared to Dialogflow.
- IBM Watson Assistant: IBM Watson Assistant is an AI-powered virtual agent platform with features like multi-channel support, integration with Watson APIs, and built-in analytics. Pros include enterprise-grade security and scalability, while cons include higher pricing for advanced features.
- Amazon Lex: Amazon Lex is a service for building conversational interfaces using voice and text. Key features include integration with AWS services, built-in speech recognition, and scalability. Pros include seamless deployment with AWS infrastructure, while cons include limited customization options compared to Dialogflow.
- Wit.ai: Wit.ai is a natural language processing tool acquired by Facebook. It offers features like entity recognition, language understanding, and integration with Facebook services. Pros include ease of use and strong community support, while cons include limited platform integrations.
- Rasa: Rasa is an open-source conversational AI platform with features like customizable dialogue management, natural language understanding, and integration with various channels. Pros include full control over data and models, while cons include more technical expertise required compared to Dialogflow.
- Pandorabots: Pandorabots is a chatbot development platform with features like multilingual support, analytics, and integrations with popular messaging platforms. Pros include a user-friendly interface, while cons include limited customization options for complex bots.
- TARS: TARS is a chatbot building platform with features like drag-and-drop interface, analytics, and integration with marketing tools. Pros include easy deployment and A/B testing capabilities, while cons include pricing based on conversations.
- SAP Conversational AI: SAP Conversational AI is a chatbot development platform with features like multi-language support, integration with SAP products, and bot builder tools. Pros include seamless integration with SAP ecosystem, while cons include limited third-party integrations.
- Botpress: Botpress is an open-source chatbot platform with features like visual flow builder, NLU engine, and integrations with popular messaging platforms. Pros include full control over code and data, while cons include less user-friendly interface compared to Dialogflow.
- Flow.ai: Flow.ai is a conversational AI platform with features like multi-channel support, analytics, and integrations with CRM tools. Pros include intuitive interface and customer service integrations, while cons include limited customization options for complex bots.
Top Alternatives to Dialogflow
- 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
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
It combines artificial intelligence (AI) and sophisticated analytical software for optimal performance as a "question answering" machine. ...
- 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. ...
- Twilio
Twilio offers developers a powerful API for phone services to make and receive phone calls, and send and receive text messages. Their product allows programmers to more easily integrate various communication methods into their software and programs. ...
- Twilio SendGrid
Twilio SendGrid's cloud-based email infrastructure relieves businesses of the cost and complexity of maintaining custom email systems. Twilio SendGrid provides reliable delivery, scalability & real-time analytics along with flexible API's. ...
- Amazon SES
Amazon SES eliminates the complexity and expense of building an in-house email solution or licensing, installing, and operating a third-party email service. The service integrates with other AWS services, making it easy to send emails from applications being hosted on services such as Amazon EC2. ...
- Mailgun
Mailgun is a set of powerful APIs that allow you to send, receive, track and store email effortlessly. ...
Dialogflow alternatives & related posts
Amazon Lex
- Easy console9
- Built in chat to test your model6
- Great voice2
- Easy integration2
- Pay-as-you-go1
- English only6
related Amazon Lex posts
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.
Microsoft Bot Framework
- Well documented, easy to use18
- Sending Proactive messages for the Different channels3
- Teams0
- LUIS feature adds multilingual capabilities2
related Microsoft Bot Framework posts
Dear All,
We are considering Chat BOT implementation. However, we are not sure which tool gives what features and when we need to choose. (listing, comparison of Microsoft Bot Framework Vs Power Virtual Agents) Can you please provide the same?
IBM Watson
- Api4
- Prebuilt front-end GUI1
- Intent auto-generation1
- Custom webhooks1
- Disambiguation1
- Multi-lingual1
related IBM Watson posts
- High Performance32
- Connect Research and Production19
- Deep Flexibility16
- Auto-Differentiation12
- True Portability11
- Easy to use6
- High level abstraction5
- Powerful5
- Hard9
- Hard to debug6
- Documentation not very helpful2
related TensorFlow posts
Google Analytics is a great tool to analyze your traffic. To debug our software and ask questions, we love to use Postman and Stack Overflow. Google Drive helps our team to share documents. We're able to build our great products through the APIs by Google Maps, CloudFlare, Stripe, PayPal, Twilio, Let's Encrypt, and TensorFlow.
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—for instance, we can use both high-level APIs, such as Keras, and implement our own custom operators using NVIDIA’s 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’s deep learning toolkit which makes it easier to start—and speed up—distributed deep learning projects with TensorFlow:
(Direct GitHub repo: https://github.com/uber/horovod)
- Powerful, simple, and well documented api148
- RESTful API88
- Clear pricing66
- Great sms services61
- Low cost of entry58
- Global SMS Gateway29
- Good value14
- Cloud IVR12
- Simple11
- Extremely simple to integrate with rails11
- Great for startups6
- SMS5
- Great developer program3
- Hassle free3
- Text me the app pages2
- New Features constantly rolling out1
- Many deployment options, from build from scratch to buy1
- Easy integration1
- Two factor authentication1
- Predictable pricing4
- Expensive2
related Twilio posts
Hi, We are looking to implement 2FA - so that users would be sent a Verification code over their Email and SMS to their phone.
We faced some limitations with Amazon SNS where we could either send the verification code to email OR to the phone number, while we want to send it to both.
We also are looking to make the 2FA more flexible by adding any other options later on.
What are the best alternatives to SNS for this use case and purpose? Looked at Twilio but want to explore other options before making a decision.
Would be great to know what the experience with Twilio has been, especially the limitations/issues with Twilio...
Appreciate any input from users of Twilio and others who have had similar use cases.
Searching for options for SMS that integrates with SiteLink and will allow personalization of text and tracking of both incoming/outgoing messages with reporting (Time, date, call#, etc) Have been looking at Twilio, and seems most leaning toward this. Are there any other options known that integrate into SiteLink? Also looked at Clickatell.
- Easy setup190
- Cheap and simple137
- Easy email integration!107
- Reliable86
- Well-documented58
- Generous free allowance to get you started28
- Trackable25
- Heroku add-on21
- Azure add-on15
- Better support for third party integrations13
- Simple installation6
- Free plan6
- Helpful evangelist staff4
- Great client libraries4
- Great support3
- Better customer support than the competition3
- Great add-ons3
- Nice dashboard2
- Scalable2
- Web editor for templates1
- Cool setup1
- Within integration1
- Easy set up1
- Free1
- Great customer support1
- Google cloud messaging1
- Google analytics integration is not campaign-specific3
- Shared IP blacklist removal takes months1
- Shares IP blacklist removal0
related Twilio SendGrid posts
At StackShare we were discussing how to increase the retention of our newly signed up users. We hypothesized that if we made certain changes to the emails in our on-boarding process we could increase our retention and activation of users.
We decided to use sendwithus because it offered us the ability to A/B test our transactional emails. We also utilized the sendwithus analytics dashboard to gain real time insight into the performance of our email campaigns. Furthermore sendwithus has a Rails gem that allowed us to easily integrate the product into our application. We were also able to integrate sendwithus with our SendGrid account. #ABTestingAnalytics #TransactionalEmail
Nexmo vs Twilio ?
Back in the early days at SmartZip Analytics, that evaluation had - for whatever reason - been made by Product Management. Some developers might have been consulted, but we hadn't made the final call and some key engineering aspects of it were omitted.
When revamping the platform, I made sure to flip the decision process how it should be. Business provided an input but Engineering lead the way and has the final say on all implementation matters. My engineers and I decided on re-evaluating the criteria and vendor selection. Not only did we need SMS support, but were we not thinking about #VoiceAndSms support as the use cases evolved.
Also, on an engineering standpoint, SDK mattered. Nexmo didn't have any. Twilio did. No-one would ever want to re-build from scratch integration layers vendors should naturally come up with and provide their customers with.
Twilio won on all fronts. Including costs and implementation timelines. No-one even noticed the vendor switch.
Many years later, Twilio demonstrated its position as a leader by holding conferences in the Bay Area, announcing features like Twilio Functions. Even acquired Authy which we also used for 2FA. Twilio's growth has been amazing. Its recent acquisition of SendGrid continues to show it.
- Reliable102
- Cheap97
- Integrates with other aws services57
- Easy setup52
- Trackable18
- Easy rails setup2
related Amazon SES posts
We decided to use AWS Lambda for several serverless tasks such as
- Managing AWS backups
- Processing emails received on Amazon SES and stored to Amazon S3 and notified via Amazon SNS, so as to push a message on our Redis so our Sidekiq Rails workers can process inbound emails
- Pushing some relevant Amazon CloudWatch metrics and alarms to Slack
I would like to know how I can implement a transactional email, or if it is possible to do so, like Mailchimp, using Amazon SES. I want to have the flexibility of creating emails like MailChimp, with a bulk email sending capability. Is it as simple with AWS SES as it is with MailChimp? If so, then how can I implement that for my own product? Thanks!
- Quick email integration178
- Free plan148
- Easy setup91
- Ridiculously reliable67
- Extensive apis53
- Great for parsing inbound emails30
- Nice UI25
- Developer-centric22
- Excellent customer support15
- Heroku Add-on12
- Easy to view logs of sent emails4
- Email mailbox management for developers4
- Great PHP library2
- Great documentation2
- Great customer support, love rackspace2
- Better than sendgrid not ask too many question1
- Cost2
- No HTTPS tracking links supported2
- Emails go to spam due to blacklisted IP's of mailgun1
- Cannot create multiple api keys1
related Mailgun posts
We've moved our transactional email away from Mandrill to Mailgun. We had continued using Mandrill after Mailchimp deprecated the service awhile back, because the amount of credits we were offered essentially made it free.
However, following a couple weeks of frequent downtime and poor service transparency from Mandrill, we decided it was time to make the switch. It appears they no longer had any engineers with the ability to identify the core problems.
Mailgun has been more reliable, yet not as reliable as we expected. We still see issues a few times per week with the API failing when we attempt to make a call. The Reporting UI is way better.