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Pega + LangGraph: Self-Healing Agentic AI using A2A
What Is Self-Healing?
In agentic AI, Self-Healing means the system detects and corrects problems in real time — before they cause failures downstream.
Without Self-Healing
 Missing fields |
Manually chased later |
| Invalid data |
Workflow errors or silent failures |
| Impossible loan amounts |
Case enters destined for rejection |
| SLAs start on bad work |
Case managers spend time correcting, not deciding |
A case manager has to catch it, reject it, and chase the customer for a revised application. Too much time for the Case worker to review the information.
With Self-Healing + Pega
 All fields validated |
Pega receives complete, mandatory-field-ready payloads |
| Bad data caught and fixed |
LangGraph corrects issues before the A2A call is made |
| Loan auto-optimised |
$500k on $40k salary → recalculated to $80k, user confirms |
| Full fix log passed to Pega |
Every correction stored as Pega case evidence via A2A |
With Self-healing, recalculated to $80k with clear reasoning, confirmed by the user, and sent to Pega as a single clean case — with the full self-healing log attached as evidence.
Demo: Click here
Enjoyed this article? See more similar articles in Pega Cookbook - Recipes series