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.
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Lang.ai
Score8.5 out of 10
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Lang.ai is a text analysis tool used to make customer support agents more efficient, offering tools like better categorized support interactions for automating manual agent tasks like routing, triage, and prioritization, with the goal of cutting average time to ticket resolution.
Best suited for large organizations, availability of usage of more than one language in a specific API call. Moderately suited for small and mid sized organizations as the pricing is on a higher end
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
I've been using Lang.ai in my business for a few months now and it's been great. It's especially useful in scenarios where I need to quickly process large amounts of data, such as customer surveys or sales reports. It can handle text, numbers and images really well. For more complex tasks like natural language processing, Lang.ai is also a great choice.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
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
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
We haven't used other products. Our experience with Azure, whilst not meeting our needs this time around, was positive, educational and insightful. This was the first time that we had considered using an AI tool to manage and manipulate our data and we were unsure of the capabilities.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
I recently compared Lang.ai with Glassbox, GetFeedback, and Watson Studio by IBM. I found that Lang.ai is the most comprehensive AI-based platform for automated customer feedback analysis. It has features like natural language processing, sentiment analysis, and emotion detection which are not available on the other platforms. Furthermore, Lang.ai's user interface is intuitive and easy to use, making it my top choice for automated customer feedback analysis.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
