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Azure AI Language

Score8.2 out of 10

9 Reviews and Ratings

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What is Azure AI Language?

Azure AI Language (formerly Azure Cognitive Service for Language) is a managed service to add natural language capabilities, from sentiment analysis and entity extraction to automated question answering. Users can identify key terms and phrases, understand sentiments, and build conversational interfaces into applications. Annotate, train, evaluate, and deploy customizable models without machine-learning expertise.

Categories & Use Cases

Reviews

What users are saying about Azure AI Language.
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Analyze your text in simple steps

Incentivized
Verified User
Professional in Sales (51-200 employees employees)

Use Cases and Deployment Scope

We are a tech company and the application helps in analyzing various kinds of data in form of text in simple ways. It helps building web based applications in easy way. This application can get connected to your data sources and can extract and classify complex text in simpler formats which are easy to understand.

Pros

  • The data is pre configured that means the AI models that are used by features are not customizable. One needs to send data and have to use the output of the feature in our application
  • Availability of customizations in order to adjust some specific requirements
  • Availability of Language studio so that one can avoid coding

Cons

  • The application is hard to use for new users
  • Data Integration is complex in nature
  • For Mid - sized organizations, the pricing is on higher end

Return on Investment

  • Usage of more than one language in one specific API call
  • Question Answering Feature
  • Key Phrase Extraction, hence one need to read the entire phrase to understand the context

Alternatives Considered

WordStat and Google Cloud AI

Other Software Used

Zoho Analytics, greytHR, Microsoft 365

A good experience with the capabilities of AI

Incentivized
Verified User
Advisor (201-500 employees employees)

Use Cases and Deployment Scope

We had a large amount of physical data that needed transferring into a database, into csv format and to analyse the responses and to report in a manner that could be transferred to a geospatial map. We looked to Azure to create a system that would make this an automated process and allow us to gather the data we needed quickly and correctly with the limited resources that we had.

Pros

  • Recognised handwriting
  • recorded data such as names, addresses
  • converted information into a dataset that could be incorporated into many of our systems

Cons

  • It took a while to understand how to use, better user guidance
  • It didn't work on all of our programmes but was good with MS products
  • Setting up forms for recognition requires time and patience

Return on Investment

  • With more time and a longer project using Azure would have had a positive ROI
  • It gave us an insight into the capabilities of AI and will consider using the product in the future