Health Tech Firm Experiences 50% Faster Migration With Agentic AI Automation

The client needed to transition more than 5,500 healthcare facilities to a new scheduling system without disrupting 24/7 critical operations. Any downtime or data issue could directly impact patient care, so the migration had to be both fast and highly reliable. At the same time, they had to maintain complete data fidelity across complex configurations and over a year of historical records, with no room for loss or inconsistency.

They also had to preserve and automate integrations with 70+ vendors across different integration types, ensuring that existing connections continued to work as expected. Alongside this, they needed to guarantee seamless authentication and access continuity so users could move to the new environment without login issues or security gaps during the transition.
The client adopted Agentic AI-based tooling to manage data, configuration, integration, and security migration in a controlled, automated way. Intelligent discovery capabilities were used to automatically extract action items, data mappings, and rules from transcripts, reducing manual analysis and accelerating planning for the migration. 

SQL agents were introduced to run quicker SQL queries to support metadata-driven ingestion across the medallion architecture, helping streamline how data moved and was organized. In parallel, requirements-driven data modeling automation delivered comprehensive data structure definitions so the target environment could accurately mirror the source. 

To shorten the full migration cycle, AI agents were used to drive validation activities and generate DevOps Terraform scripts and data reconciliation scripts. This end-to-end automation helped accelerate execution while maintaining strong checks on quality, configuration integrity, and data accuracy throughout the migration journey. 

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Clients cite strong leadership, responsiveness, and reliable delivery. Partners point to engineering depth, SME coverage, and a steady focus on outcomes over activity.

Tech Stack:

AAVA, AWS RDS PostgreSQL, Microsoft Azure, Azure SQL DB, Azure Data Factory, Power BI

Business Impact

The migration timeline was reduced from 36 months to 18 months, delivering a complete migration of all customers to Schedule X with an acceleration of more than 50% while keeping operations running. 

The program is expected to deliver over 40% savings on migration costs, achieving better efficiency without compromising on quality or thoroughness. 

Agentic AI-powered automation is expected to provide 100% confidence in mitigating migration risks, strengthening trust in both the process and the final outcome. 

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