New Integrations - EnateAI for Email
Last updated
Last updated
In Enate Marketplace, we've been making some big advances in the AI space and have added a number of GPT-driven integrations to support your users with their day to day activities.
We can now offer EnateAI, a zero-configuration GPT option supplied by Enate which uses our own Azure hosted OpenAI Instance for the GPT3 Engine. This instance is shared with anyone that enables EnateAI so if you have high volume/high demand then you may be better off configuring your own Azure OpenAI instance and using an Azure Open AI Adapter Version. The configuration of the EnateAI adapters is super simple and is a mere click of a button to enable.
We have also added a number of OpenAI adapters that allow you to talk to the OpenAI API (which is open to everyone) directly via your own OpenAI account and API keys. You can also monitor usage of API requests sent via this API in the open AI interface.
And if you'd rather run these patterns via your own Azure platform, our new AzureAI adapters allow you to use your own Azure instance of OpenAI which you can manage and control, providing you with a great deal of control and detail of the information going through the API.
See our main online help section for more detailed explanation about how to set up these integrations.
These adapters are available for the following patterns:
Email Classification - analyzes incoming emails which result in the creation of a new Ticket amd automatically classifies and categorizes the Ticket, saving agents having to do this manually.
Email Data Extraction - brand new pattern that auto-populates important information from incoming emails which are creating new work items into custom cards in your Tickets and Cases, saving agents from having to do this manually.
Thank You Email Evaluation - automatically detects whether incoming emails to a Resolved work item are just simple 'thank you emails', and if so then have them automatically moved back to a state of 'resolved' without agent users having to manually perform such repetitive checks.
Sentiment Analysis - analyzes the content of every incoming email, determines their sentiment - e.g. if they're positive or negative and displays this information to your users to they can determine the sentiment of an email at a glance.
Our GPT email classification pattern analyzes incoming emails which result in the creation of a new Ticket, and automatically classifies and categorizes them. This helps support Agents with more accurate initial routing so by the time they pick it up, it's where it needs to be. In addition to the already existing UiPath Communications Mining adapter, we have now added the following adapters:
EnateAI
OpenAI GPT3
Azure OpenAI GPT3
Check out our dedicated article that shows you how to set this up:
Setting up the Email Classification Pattern
The Email Data Extraction pattern reads the content of incoming emails that result in the creation of new Work Items, and uses the information it extracts to auto-populate values into the custom cards in your Tickets and Cases. This saves Agents the time spent analyzing and transferring the data manually. It is available via the following adapters:
EnateAI
OpenAI GPT3
Azure OpenAI GPT3
Check out our dedicated article that shows you how to set this:
Setting up the Email Data Extraction Pattern
With the 'Is Thank You' pattern, you can automatically detect whether emails arriving in to a Resolved work item are just simple 'thank you emails'. If so, it automatically moves the Work Item back from a state of 'To Do' into a state of 'Resolved' without agent users having to manually perform such repetitive checks. Importantly, the 'Resolved' date of the work item remains as-is, i.e. it is unchanged when EnateAI automatically re-resolves the work item. In addition to the already existing UiPath Communications Mining adapter, we have now added the following adapters:
EnateAI
OpenAI GPT3
Azure OpenAI GPT3
Check out our dedicated article that shows you how to set this up:
Setting up the Thank You Email Evaluation Pattern
GPT's Email Sentiment Analysis pattern can analyse the content of ALL incoming emails and determine if for example they're positive or negative. This assessment can be passed back into Enate Work Manager so that Agents can tell at a glance what the tone of the mail is as headline information as they start to deal with it. In addition to the already existing UiPath Communications Mining adapter, we have now added the following adapters:
OpenAI GPT3
Azure OpenAI GPT3
EnateAI
Check out our dedicated article that shows you how to set this up:
Setting up the Email Sentiment Analysis Pattern
For clarity, here are the trigger points to show when each of these email-related features activate:
Email Classification - triggers for new inoming emails on brand new requests, i.e. ones that will create a brand new Ticket in Enate.
Email Data Extraction - triggers for new inoming emails on brand new requests, i.e. ones that will create a brand new Ticket OR Case in Enate.
Sentiment Analysis - triggers for ALL new incoming emails.
Is Thank You Analysis - triggers for new incoming emails on Resolved Tickets or Cases.
