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Unified AI Co-Pilot for Care Teams

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Industry

Healthcare Provider/Hospital System

Challenge

Disconnected systems and data silos kept care teams from accessing a single, AI-driven view of each patient.

Results

Delivered a unified AI co-pilot environment in six months, cutting care plan time by 50% and improving accuracy across workflows.

Key Service

Healthcare AI Factory

6
Months from Kickoff to Enterprise Deployment
-50%
Care Plan Creation and Documentation Time
40%
Improvement in Accuracy Across Authorization Workflows

Our goal wasn’t another dashboard or automation layer. It was to give every care manager the same real-time view, the same guidance, and the confidence that AI was working with them, not around them.

Evan Roth

Managing Director @ Productive Edge

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About the Client

Our client is a large integrated care delivery organization serving millions of patients through hospitals, clinics, and virtual care programs. They operate across diverse care settings with a strong emphasis on care coordination and quality improvement. The team sought to leverage AI to support clinicians and care managers with real-time insights, automate documentation, and improve the accuracy and speed of service planning.

The Challenge

The organization had invested heavily in analytics and automation, but each initiative lived within its own silo. Care managers, clinicians, and administrators lacked a unified view of member data and AI-driven insights. Duplicated systems, manual documentation, and inconsistent processes made it difficult to scale innovation or measure results. Leadership wanted a faster, more connected way to operationalize AI — one that brought structure and standardization without disrupting the human side of care delivery.

The Solution

Productive Edge partnered with the organization to implement the Healthcare AI Factory, creating an end-to-end framework for building, deploying, and managing AI solutions. The effort began with mapping twelve core workflows across care management, service planning, and authorization processes. The team unified EHR, CRM, and scheduling data into an interoperable data layer and introduced AI co-pilot capabilities through prebuilt components from the Boost Foundry. These co-pilots surfaced real-time insights and decision guidance directly within existing workflows. Observability dashboards, governance rules, and human-in-the-loop mechanisms ensured transparency and compliance from the start.

The Results

Within six months, the organization deployed a fully functional AI co-pilot environment that improved care plan accuracy and documentation efficiency. Care plan creation time dropped by 50%, and authorization decisions became more consistent across teams. The unified AI and data foundation now supports ongoing innovation, enabling the organization to expand co-pilot functionality into additional service lines without requiring the rebuilding of core components. The Factory model continues to guide new initiatives, ensuring that every improvement builds upon the last.

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