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"Accelerating Intelligent Automation"

in Complex, Regulated Enterprises

Manual workflows, legacy systems, and strict regulatory requirements often burden back-office operations in the insurance, healthcare, and financial services industries. These inefficiencies create significant bottlenecks — slowing claims processing, increasing error rates, and limiting scalability. Despite growing interest in automation, many enterprises struggle to implement solutions that balance compliance, accuracy, and return on investment.

To address these challenges, Hyperscience partnered with Emerj AI Research to publish a white paper exploring how leading organizations are successfully scaling intelligent automation. Hyperscience is a leader in smart document processing, enabling enterprises to convert unstructured data into actionable insights through machine learning. Its platform is designed to streamline complex, document-heavy workflows, maintaining accuracy, compliance, and operational control.

The white paper, drawing on insights from executives at Elevance Health, Cloud Insurance, and Simplyhealth, outlines the technical, cultural, and strategic shifts required to unlock automation’s full potential in regulated environments.

Download the full white paper to explore how leaders are driving growth through:

1. Faster claims processing and fraud detection

Intelligent automation tools can dramatically reduce claims processing times — from days to minutes — while simultaneously detecting anomalies that signal potential fraud.

2. Document and contract analysis at scales

With machine learning, organizations can now accurately extract and analyze data from contracts, regulatory filings, and other unstructured documents.

3. Cross-functional workforce upskilling and retention programs

Insurance and healthcare leaders give in-depth strategies for implementing multi-skilled training and incentive programs to foster the adoption of AI tools and reduce resistance to change.

4. Regulatory compliance through secure, adaptive data models

How enterprises can meet evolving privacy and data protection laws — such as HIPAA, GDPR, and the EU AI Act — by deploying proprietary, self-learning AI models that maintain strict data sovereignty while enabling automation at scale.

Offered Free by: Emerj Artificial Intelligence Research
See All Resources from: Emerj Artificial Intelligence Research