CDW Marketing strategy

CDW Marketing strategy and Proof-of-Concept (POC) deployment plan.

Strategic marketing and technical partnership proposal. CDW, as a major IT solutions provider, can leverage its deep enterprise relationships to position Equitus KGNN's AI capabilities as the solution to complex compliance, fraud, and identity verification challenges within AMN Healthcare's WorkWise platform.

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I. CDW Marketing Strategy: "The Trusted Engine for Compliant Healthcare Agility"

The core message should focus on risk mitigation, operational efficiency, and accelerating time-to-staff—all critical concerns for large healthcare systems using mobile staffing solutions like AMN's WorkWise.

1. Target Audience and Value Proposition

Target Audience	Primary Pain Point	CDW + Equitus Value Proposition
AMN Healthcare / WorkWise Product Team	Need to enhance platform security, automate compliance, and maintain a competitive edge through advanced features.	Platform Modernization & Risk Reduction: Seamlessly integrate AI/ML for automated, real-time compliance checks (KYC/FCU), reducing manual audit burden and enhancing the WorkWise security posture (SOC 2 Type II, HIPAA alignment).
Hospital/Health System Executives (CFO/CIO)	High costs of non-compliance, credentialing delays, and risk of fraud from temporary staff.	Cost & Speed Optimization: Accelerate the time-to-deploy a fully-vetted nurse by automating KYC (Know Your Clinician) and FCU (Fraud/Compliance Unit) checks, turning a compliance bottleneck into an operational advantage.
Data Architects/Engineers at AMN/Client	Need a robust, scalable, and compliant data pipeline to enable future AI features.	AI-Ready Infrastructure: CDW provides the certified cloud infrastructure, and the Data Architect/Engineer ensures the data governance and architecture are immediately ready for AI deployment in a HIPAA-compliant environment.

2. Marketing Pillars

Pillar	Strategy	Deliverable/Placement
Thought Leadership	Position CDW/Equitus as pioneers in "AI-Native Healthcare Compliance."	White Paper: "The Future of Credentialing: Using AI to Achieve Zero-Trust Compliance in Mobile Healthcare Staffing." (Posted on CDW.com and co-branded with Equitus).
Solution-Focused	Directly address the complexity of cross-state licensing, background checks, and identity verification for mobile workers.	CDW.com Solutions Page: "CDW's Compliance Accelerator for WorkWise: AI-Driven KYC and FCU." Includes a 2-minute video demo of the AI in action.
Sales Enablement	Give CDW Account Executives a compelling, quantifiable case for implementation.	Interactive ROI Calculator: Show expected reduction in manual verification time and potential fine avoidance due to proactive FCU (Fraud Control Unit) flagging.
Executive Briefing	Host a private, virtual event with key WorkWise/AMN leaders and top healthcare clients.	Webinar: "Achieving Real-Time Compliance in Contingent Labor with Equitus KGNN and CDW." (Featuring the Data Architect explaining the POC's technical and security integrity).

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II. Proof-of-Concept (POC) Deployment: "Compliance-as-a-Data-Service"

The POC must be surgically focused on demonstrating immediate, measurable value by solving a critical compliance and identity pain point within the WorkWise ecosystem.

1. POC Title and Goal

• Title: "AI-Powered Real-Time Mobile Nurse Credential Verification & Fraud Detection"

• Goal: Demonstrate a 90% reduction in manual review time for a selected subset of high-risk clinician compliance checks (KYC/FCU) by deploying the Equitus KGNN AI model on a secure, CDW-provisioned cloud environment integrated with a mock or anonymized WorkWise data feed.

2. The Data Architect / Engineer's Role

The CDW-Equitus Data Architect/Engineer is central to this POC, as they bridge the gap between compliance regulations and scalable AI.

Phase	Architect/Engineer Responsibility	Key Deliverables
1. Data Architecture & Governance	Define the secure data flow (ETL/ELT) from a segregated WorkWise environment to the Equitus KGNN deployment, ensuring all PHI/PII data is pseudonymized or anonymized in compliance with HIPAA.	HIPAA-Aligned Data Flow Diagram; Equitus KGNN Input Schema.
2. AI Environment Setup	Provision and configure the necessary cloud services (e.g., AWS SageMaker, Azure ML, or a secure private cloud environment) with appropriate security controls (VPC, encryption, multi-factor access).	SOC 2 Type II / HIPAA-Ready Cloud Deployment with all data at rest and in transit encrypted.
3. Model Training & Integration	Collaborate with Equitus data scientists to fine-tune the Knowledge Graph Neural Network (KGNN) model on test data (e.g., cross-referencing nurse licenses, sanction lists, and identity documents) and establish the API endpoint for real-time scoring.	Testable API Endpoint for WorkWise to query. Initial FCU/KYC Accuracy Metrics.
4. POC Execution & Reporting	Monitor the data pipeline for integrity, track the performance metrics (speed, accuracy), and lead the technical readout for the AMN/WorkWise team.	Final POC Report with quantifiable metrics (time savings, risk score reduction) and a blueprint for full-scale production deployment.

3. Key AI-Enabled Use Cases for the POC

The AI deployment, facilitated by the Data Architect, would focus on three compliance vectors:

1. Compliance (Credentialing):

   • AI Function: Automated, real-time cross-referencing of license numbers, certification expiration dates, and state-specific board sanctions across multiple public and proprietary healthcare databases.

   • POC Metric: Time to confirm all necessary credentials for a nurse across three different states (). Compare to current manual time ().

2. KYC (Know Your Clinician) / Identity Verification:

   • AI Function: Using AI/ML for biometric verification (if applicable) and cross-checking submitted documents (ID, passport, etc.) against known fraud databases and watchlists. The KGNN can identify hidden connections between applicants who share addresses or phone numbers but use different identities.

   • POC Metric: Detection of pre-vetted synthetic or falsified identity in the test data set with a precision rate.

3. FCU (Fraud/Compliance Unit) Risk Scoring:

   • AI Function: Assigning a dynamic, real-time risk score to a mobile nurse profile based on the aggregation of all data points (license history, employment gaps, past alerts, geographical movement). Flagging profiles above a pre-defined risk threshold for immediate human review.

   • POC Metric: Reduction in False Positives for "high-risk" flags by compared to current rule-based systems.

This strategy ensures CDW leverages its infrastructure and service expertise, Equitus KGNN showcases its cutting-edge AI, and the dedicated Data Architect/Engineer provides the necessary technical trust and compliant foundation for AMN Healthcare to confidently adopt the solution at scale within their WorkWise platform.