What challenges did Sara Assicurazioni face before AI implementation?

Automate claims ingestion and document analysis for vehicle glass damage. Reduce manual processing while improving data quality and handling missing/incorrect data and anomalies.

What was the impact of the AI solution?

The article states HCLSoftware customers reported productivity gains up to 60% and reduced operating costs up to 15%. Sara Assicurazioni plans to expand workflow functionality so most claims can be completed automatically based on Bedrock-driven recommendations.

Source

ExpandedEvidence: Low35/100

HCL Workload Automation + AWS Step Functions for document-based claims analysis with Amazon Bedrock and Textract (Sara Assicurazioni example)

Use case typeIntelligent document processingUpdated Jun 13, 2026

Sara Assicurazioni, an Italian insurance company, uses HCL Workload Automation for claims ingestion and document review. The workflow uses Amazon Textract to extract claim information from documents, AWS Step Functions to orchestrate a call to Amazon Bedrock Knowledge Bases with RAG, and AWS Lambda/S3/SNS for routing and notifications. The article says the approach helps inspect vehicle glass damage claims for missing or incorrect data, anomalies, and claim approval logic so that most claims can be completed automatically.

Organization: Sara Assicurazioni
Industry: Insurance
Location: Italy
Published: May 2024

Reported outcomes

−60%

costCost savings

−15%cost

Strategic outcomes

Speed & agilityAutomated claims processing workflowNew product / capabilityAdded AI-driven claims analysis capabilityCustomer experience & trustImproved claims data quality and review handlingScale & capacityExpanded workflow for broader automation

Why do we believe this?Outcome claims, sources, and evidence checks

Normalized claim

Cost: 60% decrease

AWS Partner NetworkMay 29, 2024Partner storyInferred claimLow evidence strength

The article states HCLSoftware customers reported productivity gains up to 60% and reduced operating costs up to 15%.

Normalized claim

Cost: 15% decrease

AWS Partner NetworkMay 29, 2024Partner storyInferred claimLow evidence strength

The article states HCLSoftware customers reported productivity gains up to 60% and reduced operating costs up to 15%.

Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks

Customer: Sara Assicurazioni
Provider: AWS
Maturity: Unknown
Linked source: AWS Partner Network

No explicit deployment-stage evidence found.

Customer identity supportedSource describes one deploymentMaturity evidence evaluated

Primary read

Use case focus

Showing 3 of 4

1Claims Processing Automation
2Document Intelligence
3Workflow Orchestration

Automate claims ingestion and document analysis for vehicle glass damage.
Reduce manual processing while improving data quality and handling missing/incorrect data and anomalies.

Data is submitted into the workflow and attachments are stored in Amazon S3 by AWS Lambda.
Amazon Textract extracts claim data from documents.
AWS Step Functions calls Amazon Bedrock Knowledge Bases using retrieval augmented generation to enrich prompts.
Foundation-model output is stored back in S3 and AWS Lambda routes the claim either for automatic processing or to Amazon SNS for manual review notifications.

Technologies

AWS Step Functions Amazon Textract Amazon Bedrock Amazon Bedrock Knowledge Bases AWS Lambda Amazon S3 Amazon SNS HCL Workload Automation

The article states HCLSoftware customers reported productivity gains up to 60% and reduced operating costs up to 15%.
Sara Assicurazioni plans to expand workflow functionality so most claims can be completed automatically based on Bedrock-driven recommendations.

Architecture

Customers submit claims data. AWS Lambda pulls attachments and stores them in Amazon S3. Amazon Textract extracts claim information, which is submitted to an AWS Step Functions workflow that calls Amazon Bedrock Knowledge Bases for RAG enrichment. The augmented prompt is sent to a Claude foundation model; output is stored in S3. AWS Lambda then pushes the data to a Document Management System, and a Claim Router Lambda either auto-processes it or sends an Amazon SNS notification for manual processing. The workflow is orchestrated by HCL Workload Automation.

Sources & evidence1

Evidence: Low35/100Evidence strength