It support · Production

Iberdrola enhances IT operations using Amazon Bedrock AgentCore for change management and incident enrichment

The problem

Iberdrola's IT operations were slowed by manual change request resubmissions and a lack of contextual intelligence in incident management, creating bottlenecks that impeded ticket resolution across departments.

Workflow diagram · grounded in source
1
ServiceNow initiates request
trigger
“Users initiate requests through ServiceNow, which communicates through a REST API to the MicroGateway that routes requests to appropriate use case agents”
2
MicroGateway routes to agent
routing
“a MicroGateway provides intelligent routing to direct requests to relevant agents”
3
Sequential agents validate change request
ai_action
“The workflow processes change requests through four specialized agents—Rule Extractor, Content Validator, AIM Model Analyst, and Phase Transition—with each agent receiving context from the previous step”
4
Validation feedback to requester
output
“When validation errors are detected, the system provides clear feedback to requesters before allowing progression to subsequent phases”
5
Smart Solver Agent enriches incident
ai_action
“The Smart Solver Agent analyzes incident content and determines which specialized agents to invoke based on missing context and potential value-add”
6
Conversational change model recommendation
ai_action
“The agent collects information about technology families, change objectives, and deployment environments to recommend suitable change models. The system provides clickable recommendations that open pre-filled change forms, streamlining t…”
Reported outcome

Iberdrola realized substantial productivity gains and improvements in data quality across change and incident management, reducing engineering cognitive load and accelerating safe delivery across IT operations.

Reported metrics
Change request processing timesdrastically reduces processing times
Productivitysubstantial productivity gains
Data qualityunparalleled improvements in data quality
Ticket resolution speedhelp teams accelerate ticket resolution
Show all 5 reported metrics
change request processing timesdrastically reduces processing times
productivitysubstantial productivity gains
data qualityunparalleled improvements in data quality
ticket resolution speedhelp teams accelerate ticket resolution
engineering cognitive loadreducing engineering cognitive load
Reported stack
Amazon Bedrock AgentCoreServiceNowLangfuseLiteLLMAmazon NovaAnthropic ClaudeAmazon BedrockAmazon Bedrock GuardrailsAmazon S3Amazon RDSAmazon ECRAmazon EKSAmazon CloudWatchOpenTelemetryEntra ID
Source
https://aws.amazon.com/blogs/machine-learning/iberdrola-enhances-it-operations-using-amazon-bedrock-agentcore?tag=soumet-20
Read source ↗

Frequently asked questions

What did this team achieve with this AI workflow?

Iberdrola realized substantial productivity gains and improvements in data quality across change and incident management, reducing engineering cognitive load and accelerating safe delivery across IT operations.

What tools did this team use?

Amazon Bedrock AgentCore, ServiceNow, Langfuse, LiteLLM, Amazon Nova, Anthropic Claude, Amazon Bedrock, Amazon Bedrock Guardrails, Amazon S3, Amazon RDS.

What results were reported?

Change request processing times: drastically reduces processing times; Productivity: substantial productivity gains; Data quality: unparalleled improvements in data quality; Ticket resolution speed: help teams accelerate ticket resolution (source-reported, not independently verified).

How is this it support AI workflow structured?

ServiceNow initiates request → MicroGateway routes to agent → Sequential agents validate change request → Validation feedback to requester → Smart Solver Agent enriches incident → Conversational change model recommendation.

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