Pega Agentic AI Email Bot: Turning Emails into Intelligent Business Outcomes

[RameshSangili]

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Pega Agentic AI Email Bot: Turning Emails into Intelligent Business Outcomes

Introduction

Emails remain one of the most common and unstructured channels through which customers interact with enterprises. Customers ask questions, submit requests, provide details, and attach documents—all in free‑form text. Traditionally, this creates operational overhead, manual triage, and delayed responses.

In this article, I showcase a Pega Agentic AI Email Bot that demonstrates how Pega can act as the enterprise brain, orchestrating AI-driven understanding, decisioning, and case creation—all from a single inbound email.

This demo highlights how Pega’s agentic capabilities go far beyond simple automation, enabling context-aware reasoning, knowledge-driven responses, and end-to-end case orchestration.

Demo: https://players.brightcove.net/1519050010001/default_default/index.html?videoId=6393102810112

High-Level Architecture: Pega as the Agentic Brain

At the heart of this solution is Pega Platform, which orchestrates specialized AI agents responsible for:

• Understanding natural language email content

• Retrieving answers from enterprise knowledge

• Creating structured business cases

• Processing and mapping data from unstructured documents

• Applying business rules and guardrails

Pega coordinates these agents through its case management, decisioning, integration, and AI capabilities, ensuring outcomes are explainable, governed, and production‑ready.

Use Case 1: Intelligent Responses from Pega Knowledge Articles

Scenario

A user sends an email asking multiple questions, such as:

• Loan payment options

• Criteria for insurance eligibility

These questions are based on knowledge articles hosted in Pega.

How Pega Agentic AI Handles This

• The email is ingested by the Pega Email Bot.

• Pega’s AI agent analyzes the email intent and identifies multiple knowledge-related questions.

• Relevant knowledge articles in Pega are retrieved.

• A single, coherent response is generated and sent back to the user.

Key Value

• Eliminates manual service agent intervention

• Ensures consistent, governed answers

• Fully traceable to enterprise knowledge sources

Why Pega Stands Out

This demo highlights why Pega is uniquely positioned for Agentic AI in the enterprise:

• Orchestration-first: Pega coordinates agents instead of acting as a standalone chatbot

• Case-driven: Every interaction results in a governed business outcome

• Explainable & compliant: Decisions are transparent and auditable

• Multi-channel ready: Email today, chat and voice tomorrow

• Enterprise-grade AI: Not just answers, but actions

Closing Thoughts

The Pega Agentic AI Email Bot demonstrates how enterprises can meet customers where they already are—email—while still delivering intelligent, automated, and governed outcomes.

By combining:

• AI reasoning

• Knowledge management

• Document processing

• Case orchestration

Pega truly becomes the agentic brain of the enterprise.

Enjoyed this article? See more similar articles in Pega Cookbook - Recipes series.

[Arunkumar_Velmurugan]

Can you please share your configuration?

I am facing some issues with Agentic email processing. Even when the email body contains the correct information, case classification does not work consistently. Sometimes, only an Email Triage case is created, and the actual business case is not created.

I would also like to stop automatically sending a response to the customer when an Email Triage case is created.

Has anyone faced similar issues? If so, could you share the configuration or best practices that helped resolve them?

[RameshSangili]

Could you please ensure the Agent configuraiton for Agentic Email bot has the following items configured correctly?

1. Agent Instructions
2. Agent Case types

Thanks,

Ramesh

[Arunkumar_Velmurugan]

Thank you for the response.
Yes, I am able to create the case.

I have a few more questions:

1. How do we control what data is extracted from incoming emails? Currently, only few fields are being extracted. Is this controlled only through the agent instructions, or is there a way to map fields from the email to the case creation screen? Where can we configure this mapping?

2. When an automatic reply is sent after case creation, do we have control over what the Pega GenAI Agent sends to the customer? For example, can we customize the acknowledgment email content that is sent when a case is created?

[RameshSangili]

1. I think we can refine through Agent Instructions to extract all the fields. Could you please shed more light if the extraction is on the email or attachments?

2. I hope yes, but never tried out.

[Arunkumar_Velmurugan]

Regarding question 1, the extraction is from the email body, not from the attachments. We are trying to understand how we can control which fields are extracted from the incoming email and mapped to the case fields.

Regarding question 2, I noticed that the auto acknowledgment email sent by the Pega GenAI Agent is not always the same. The agent seems to generate a different response template each time a case is created. How can we control the content and format of this customer response? Is this also managed through the Agent Instructions, or is there another configuration available for the acknowledgment email template?

Thank you for your help.

[RameshSangili]

Regarding 1st point - If the fields are available on the email body, then it should be straight forward to extract the data and map it to Case Data model as long as the Agent Instructions are clear. I was able to extract the Embedded Page and PageList from the attachments from both attachments and email body.