What challenges did Myndshft face before AI implementation?

Prior authorization submission and review were slow because data arrived in unstructured documents. Providers needed faster time-to-decision, fewer errors, and lower processing costs. Manual review workflows created workload pressure for clinical teams.

What was the impact of the AI solution?

The solution expedites prior authorization submission and review. It improves access to care and time-to-decision. It reduces data processing errors and costs. It helps providers redeploy clinical resources to care management. It eases physician workload through a faster clinical review process.

Rank#1,278of 3,449

Source

GCPEvidence: Low25/100

Claims Acceleration Suite for Prior Authorization (Myndshft)

Use case typeMedical document automationUpdated Jun 13, 2026

Claims Acceleration Suite expedites prior authorization submission and review by transforming unstructured documents into structured datasets. It uses Document AI and Healthcare NLP API to extract essential clinical and demographic data, then stores structured data in BigQuery, Firestore, and Cloud Healthcare API (FHIR) for near-real-time payer/provider exchange. The solution supports providers in preparing prior authorization requests, activating review workflows, and expediting manual review through Pega Care Management on Google Cloud Marketplace.

Organization: Myndshft
Industry: Healthcare
Location: United States
Published: June 2026

Reported outcomes

Strategic outcomes

Speed & agilityExpedited prior authorization submission and reviewCustomer experience & trustImproved access to care and decision speedCost efficiencyReduced data processing errors and costsEmployee experienceReduced physician workload

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

Customer: Myndshft
Provider: GCP
Maturity: Unknown
Linked source: Google Cloud

No explicit deployment-stage evidence found.

Customer identity supportedSource describes one deploymentMaturity evidence evaluated

Primary read

Use case focus

Showing 3 of 3

1Document Processing
2Workflow Automation
3Healthcare Claims Automation

Prior authorization submission and review were slow because data arrived in unstructured documents.
Providers needed faster time-to-decision, fewer errors, and lower processing costs.
Manual review workflows created workload pressure for clinical teams.

Myndshft built an application and API on Google Cloud to determine whether prior authorization is required and to populate requests with patient clinical and demographic information from the EMR.
Claims Data Activator ingests prior authorization forms and medical documents from Cloud Storage.
Document AI and Healthcare NLP API extract essential data elements from those documents.
Extracted data is stored as structured records in BigQuery, Firestore, and Cloud Healthcare API (FHIR data store) to support interoperable exchange and analytics.
Pega Care Management Application is used to support human-based manual review workflows.

Technologies

Document AI Healthcare NLP API BigQuery Cloud Healthcare API Cloud Storage Firestore

The solution expedites prior authorization submission and review.
It improves access to care and time-to-decision.
It reduces data processing errors and costs.
It helps providers redeploy clinical resources to care management.
It eases physician workload through a faster clinical review process.

Architecture

Claims Data Activator ingests prior authorization forms and medical documents from Cloud Storage, extracts data with Document AI and Healthcare NLP API, and stores the structured output in BigQuery, Firestore, and Cloud Healthcare API (FHIR). The solution also includes an application and API for submission and uses Pega Care Management Application to support manual review workflows.

Sources & evidence1

Evidence: Low25/100Evidence strength