Customer
Healthcare process automation was critical for this leading U.S. healthcare services provider specializing in network-enabled care delivery and point-of-care mobile applications. The organization employs 6,000+ people and supports a nationwide network of 160,000+ providers serving 100M+ patients.
Business Objective
The customer needed to:
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Reduce turnaround time (TAT) for client-facing healthcare processes
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Improve work quality and minimize manual error rates
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Automate high-volume, repetitive transactions
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Scale operations efficiently across a large provider network
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Reduce operational cost dependency on manual work
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Integrate multiple systems to ensure seamless data and workflow continuity
The goal was to build a scalable, AI-driven automation layer supporting large-scale clinical and administrative operations.
Scope of Services
BXI Technologies partnered with the customer to:
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Deploy AI agentic agents to automate repetitive healthcare tasks
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Integrate workflows across six core enterprise systems
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Build and deploy automation across 16 end-to-end processes
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Implement 49 production bots to minimize manual intervention
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Standardize and streamline client-facing workflows
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Deliver a scalable automation framework supporting 1.32M+ annual transactions
This created a centralized digital operations model that reduced process cycle time and improved SLA performance.
Benefits
The transformation delivered:
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Significant reduction in turnaround time (TAT)
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Improved accuracy and consistency across healthcare workflows
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Enhanced operational efficiency with AI-driven agents
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Better utilization of workforce through FTE savings
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Streamlined workflows across six integrated systems
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Improved SLA adherence for client operations
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Automation at scale for multiple high-volume processes
Impact
- 1,320,000+ automated transactions annually
- 97,000+ FTE hours saved each year
- 6 systems integrated
- 49 production bots deployed
- 16 processes automated end-to-end
This resulted in faster client delivery, reduced operational cost, and improved healthcare process automation at scale.
