Dialogflow
Conversational User Experience Platform
Overview
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HQ Location
United States
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Year Founded
2010
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Company Type
Private
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Revenue
< $10m
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Employees
11 - 50
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Website
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Twitter Handle
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Company Description
Dialogflow is a natural language understanding platform that makes it easy to design and integrate a conversational user interface into your mobile app, web application, device, bot, interactive voice response system, and so on. Using Dialogflow, you can provide new and engaging ways for users to interact with your product.
IoT Solutions
Dialogflow CX
Dialogflow CX is an advanced development suite for creating conversational AI applications, including chatbots, voicebots, and IVR bots. It includes a visual bot-building platform, collaboration and versioning tools, and advanced IVR feature support, and is optimized for enterprise scale and complexity. Dialogflow CX is cross-platform and can connect to your own apps, existing telephony platforms, and digital platforms. Dialogflow CX users have access to Google Cloud Support and a service level agreement (SLA) for production deployments.
Dialogflow CX is an advanced development suite for creating conversational AI applications, including chatbots, voicebots, and IVR bots. It includes a visual bot-building platform, collaboration and versioning tools, and advanced IVR feature support, and is optimized for enterprise scale and complexity. Dialogflow CX is cross-platform and can connect to your own apps, existing telephony platforms, and digital platforms. Dialogflow CX users have access to Google Cloud Support and a service level agreement (SLA) for production deployments.
Key Customers
Motorola, Alpine Electronics, SAIC Motors, CloudCar, SitePoint
Parent Company
IoT Snapshot
Dialogflow is a provider of Industrial IoT analytics and modeling technologies.
Technology Stack
Dialogflow’s Technology Stack maps Dialogflow’s participation in the analytics and modeling IoT Technology stack.
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Devices Layer
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Edge Layer
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Cloud Layer
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Application Layer
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Supporting Technologies
Technological Capability:
None
Minor
Moderate
Strong
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Case Studies.
Case Study
KLM's Innovative Booking and Packing Bot 'BB' Powered by Dialogflow
KLM Royal Dutch Airlines, a global airline serving over 30 million passengers annually, was facing a challenge in providing a personalized and convenient booking experience for its customers. The average customer flies with KLM 1.4 times per year, and many of these customers do not download the airline’s mobile app to book a flight. KLM wanted to create a new entry point for these customers, one that provided opportunities for conversational interactions using voice or text. The goal was to bring warmth and personality to conversations with their customers, enhancing the overall customer experience.
Case Study
Ticketmaster Enhances Ticket Buying Experience with Dialogflow
Ticketmaster, the world's leading live-event ticketing company, was seeking ways to provide faster and more personalized services for ticket buyers. They recognized the potential of natural language processing in enhancing customer experience but had little experience in this field. The challenge was to find a technology that was easy to implement, scalable, and provided a good developer experience. They also needed a system that could understand and respond accurately to the names of thousands of different musical artists, a crucial aspect of their business.
Case Study
Domino’s Enhances Customer Experience with Dialogflow’s Conversational Technology
Domino’s, a global pizza restaurant chain, has been at the forefront of digital innovation, offering customers the ability to order pizzas via 'Dom', an ordering bot available online and through the company’s mobile apps. However, with the changing consumer behavior and the need to innovate, the company faced the challenge of building rich conversational experiences powered by natural language understanding (NLU) and machine learning. The company needed a solution that could scale and accommodate the number of intents needed for a complex ordering process. The challenge was to account for the numerous directions a customer could take when ordering from their extensive menu.
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