# EnateAI

Over the past few months at Enate we've been releasing more and more AI-driven features to help tackle the grind of first email management: sorting, classifying and extracting data from them, then expanding out into analysing incoming documents to help with that.

Now, we're taking a really significant step forward and are expanding our AI capabilities with the release of 'EnateAI - AIAnalyst'. With this, you can seamlessly integrate AI-driven activities throughout your business processes.

{% embed url="<https://enate.cdn.spotlightr.com/watch/MTY0ODMwMw==>" %}

AI Analyst's capabilities can navigate through complex service workflows to carry out time-consuming tasks for you like invoice matching, change of directors, and payment reconciliation. These areas, traditionally bogged down by extensive manual effort, are getting a major efficiency boost from Analyst, handling a significant portion of the workload with minimal human intervention. Click below to check it out

{% content-ref url="/pages/Zt0gasNflKb0pCVlT4tj" %}
[EnateAI - AI Analyst (Beta)](/enate-help/enateai/enateai/enateai-ai-analyst.md)
{% endcontent-ref %}

AI Analyst builds on top of the work we've already done in the Email space, with a number of AI integrations to support how you can more easily deal with incoming emails, turning unstructured data into structured data, fast and adding extra insights into the information you can get from your mails.

{% content-ref url="/pages/MfpimVjX9xcigLH18WAr" %}
[EnateAI for Email](/enate-help/enateai/enateai/enateai-for-email.md)
{% endcontent-ref %}

In addition to turning unstructured email & data into structured data, EnateAI for IDP is also available to automatically extract relevant data from the Files attached to incoming emails, so that this data can be used in further processing of the work item, saving your agents time and effort.

{% content-ref url="/pages/IWZDZIl8uhIn9Qh9e6lf" %}
[EnateAI for IDP - Document Extraction](/enate-help/enateai/enateai/enateai-for-idp-document-extraction.md)
{% endcontent-ref %}

There's also EnateAI options to analyze these incoming email attachments and automatically classify them, applying tags that can be used to optimize any ongoing processing downstream specific to that document type, particularly to help highlight the right files for things like external automation routines to work with. You can read more about this in the EnateAI - Document Classifiction section.

{% content-ref url="/pages/tJsqmS4IvO01EslU8yaw" %}
[EnateAI - Document Classification](/enate-help/enateai/enateai/enateai-document-classification.md)
{% endcontent-ref %}

All these integrations are available at the flick of a switch in [**Enate's Marketplace**](/enate-help/builder/builder-2021.1/integrations-marketplace.md).

## What are the AI models used by EnateAI?

Enate's AI integrations use either GPT4o or GPT4o-mini. For more information on these AI models use the links listed below:

* [​GPT4o​](https://ai.azure.com/catalog/models/gpt-4o)
* ​[GPT4o-mini​](https://ai.azure.com/catalog/models/gpt-4o-mini)

<br>


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.enate.net/enate-help/enateai/enateai.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.