What challenges did UiPath face before AI implementation?

Healthcare organizations face inefficiencies and high costs in manual summarization of voluminous medical records, lengthening prior authorization turnaround and impacting clinical decisions. Manual processes are time-consuming, inconsistent in quality, and prone to errors, requiring costly rework and delaying clinical workflows.

What was the impact of the AI solution?

Saved up to 40 minutes per patient referral. Improved accuracy and standardization of summaries, reducing errors. Deployed with a major healthcare payer achieving 23% faster document processing and cost savings.

Source

GCPProductionEvidence: Medium50/100

UiPath Medical Record Summarization AI Agent Powered by Google Cloud Vertex AI and Gemini Models

Use case typeClinical documentationUpdated Jun 13, 2026

UiPath developed a generative AI-based Medical Record Summarization AI agent to automate the summarization of voluminous medical records, leveraging Google Cloud Vertex AI and Gemini 2.0 Flash model. The agent provides clinician-level, multi-point summaries with traceable citations, using retrieval-augmented generation (RAG) technology to process unstructured medical data. It reduces prior authorization turn-around time by up to 50%, saves up to 40 minutes per referral, and cuts summary completion time from 45 minutes to just minutes. The solution improves accuracy and standardization of medical summaries, reducing errors and enabling better clinical decision making. It is already deployed by a major healthcare payer, reporting 23% faster document processing times and significant cost avoidance.

Organization: UiPath
Industry: Healthcare
Location: United States
Published: April 2025

Reported outcomes

Time: +23%

Time & speed

Time: Up to 40 minutes

Catalog median for time & speed deployments: +59% across 138 reported metrics. Compare benchmarks →

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

Normalized claim

Time: 50% decrease

UiPath newsroomApr 9, 2025Press releaseInferred claimMedium evidence strength

Reduced prior authorization processing time by up to 50%.

Normalized claim

Time: 40 minutes decrease

UiPath newsroomApr 9, 2025Press releaseInferred claimMedium evidence strength

Saved up to 40 minutes per patient referral.

Normalized claim

Time: 23% increase

UiPath newsroomApr 9, 2025Press releaseInferred claimMedium evidence strength

Deployed with a major healthcare payer achieving 23% faster document processing and cost savings.

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

Customer: UiPath
Provider: GCP
Maturity: Production
Linked source: UiPath newsroom

It is already deployed by a major healthcare payer, reporting 23% faster document processing times and significant cost avoidance

Customer identity supportedSource describes one deploymentMaturity supported

Primary read

Use case focus

Showing 2 of 2

1Generative AI summarization
2AI-assisted clinical documentation

UiPath built a generative AI agent using Google Cloud Vertex AI and Gemini models.
The agent uses RAG technology to handle unstructured medical records and produces structured, standardized summaries quickly and accurately.
The agent was developed with clinical input to ensure quality and relevance in healthcare settings.

Technologies

Google Cloud Vertex AI Google Cloud Gemini 2.0 Flash

Saved up to 40 minutes per patient referral.
Improved accuracy and standardization of summaries, reducing errors.
Deployed with a major healthcare payer achieving 23% faster document processing and cost savings.

Architecture

The solution integrates Google Cloud Vertex AI and Gemini 2.0 Flash models with UiPath Agent Builder to provide a generative AI agent that performs multi-point, clinician-level summarization of medical records using retrieval-augmented generation (RAG) technology.

Sources & evidence1

Evidence: Medium50/100Evidence strength