Amazon Comprehend is a natural language processing (NLP) service that uses machine learning to find insights and relationships in text. Amazon Comprehend uses machine learning to help uncover insights and relationships in unstructured data. The service identifies the language of the text; extracts key phrases, places, people, brands, or events; understands how positive or negative the text is; analyzes text using tokenization and parts of speech; and automatically organizes a collection of text…
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Google Cloud Dialogflow
Score 7.7 out of 10
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Dialogflow (formerly Api.ai) is a chatbot building tool, designed to give users new ways to interact with digital products by building engaging voice and text-based conversational interfaces powered by AI.
Dialogflow was acquired by Google in 2019.
Specifically, it starts processing millions of documents in minutes by leveraging the power of machine learning without having trained models from scratch. If any of the content contains personally identifiable information not only can Amazon Comprehend locate it but it will also redact or mask it. Using NLP techniques Amazon Comprehend goes well beyond keyword search or rules-based tagging to accurately classify documents. For my task or development, I cannot find any difficulties with Amazon Comprehend.
Indicated for those who have good knowledge of programming and coding in HTML and JSON, that is, it is not suitable for beginners or users without much technical knowledge. It is suitable for those who want to integrate with various platforms, such as Telegram, Webhat, Facebook Messenger, among others. I also recommend it to anyone who needs to create a chatbot in several languages (it is not automatic translation). Recommended to create new projects in CX environment and not in ES.
Amazon Comprehend identifies the language of the text and extracts Key-phrases, places, people, brands or events.
It can build a custom set of entities or text classification models that are tailored uniquely to the organisation's need
Amazon Comprehend's medical can be used to identify medical conditions, medications, dosages, strength and frequencies from sources like doctor's notes, clinical trial reports and patient health records. This service is very good and with well an accuracy or confidence score.
Users benefit from Dialogflow's best User Interface and seamless User Experience. It's very scalable, and there are a lot of customization options to make it even more so. Dialogflow makes it simple to deploy, manage, and maintain chatbots. Artificial Intelligence algorithms make chatbots interactive, making it easier for users and chatbots to communicate and understand each other. Overall, it's a good option for those with little programming experience who want to learn Natural Language Processing.
Dialogflow is a wonderful tool that is helping to design customized chatbots. I personally recommend if you wanna know how it's works give it a try with a free APIs call, you'll love this tool
For natural language processing tasks or techniques, there are many service providers out there in the market such as Azure Cloud Services, IBM Watson and Google Cloud Platform (GCP), but compared with them, Amazon Comprehend is the best service provider in contents of accuracy, speed of processing multilingual text, supporting SDK for most of the languages and well documented.
There is always use cases for both. We still use the other plattforms but each has its own strengths and weaknesses. We, as a contact center implementation partner always use multiple solutions both for ourselves but also for our customers to meet their needs. In the cases we choose Google Cloud Dialogflow is when we need to be able to handle specific follow-up questions from the customer. And for more complicated issues we also use a combination of this and other 3rd party plattforms. We always meet the need of our customers and as specialist and consultants we give expert advice on how to use all these different solutions in the best way possible.
It supports better and accurately as compared with our existing or old implementations. So, we fulfil our needs as per clients' requirements and it will help to grow or improve client satisfaction.
For these specific requirements, we do not require any machine learning engineers or related professionals to hire in our organisation.
None of any negative sides can be affected our business or distract existing clients.
As a partner to multiple contact center plattforms we have always been able to offer Google Cloud Dialogflow along with them because it integrates well with all.
Many businesses want to implement smart ways to have call deflection. Bots that can handle full dialogues with the customer is very intriguing to them because it can fulfill customers requests without using up as many resources
