Healthcare Provider Automates Referrals and Prior Authorization
An FDE squad embedded for 12 weeks deployed an AI agent across EMR and CRM systems to automate referral and prior-authorization workflows end to end.
Read the case studySemiconductor / Manufacturing · Global
The client is one of the world's largest semiconductor manufacturers: a global business whose fabs, test floors, and automation systems run continuously, and whose tolerance for downtime is measured in seconds, not hours. Anonymized here at the client's request, the company designs and builds precision hardware that the rest of the technology industry depends on.
Like most enterprises of its scale, its software estate was not built in one place or one decade. It was accumulated through years of mergers and acquisitions. Each acquired business arrived with its own toolchain, its own conventions, and its own mission-critical applications, many written in Visual Basic 6 and still wired directly into the equipment on the manufacturing floor. The result was a portfolio of high-value, high-risk components that nobody wanted to touch and nobody could afford to lose.
Mounting technical debt from years of mergers and acquisitions had concentrated into six critical Visual Basic 6 components. These were not peripheral utilities. They sat on the hot path between the company's software systems and its precision hardware. As the business pushed to scale automation and throughput, those six components became the ceiling everything else hit.
The team brought us four interlocking problems:
The bar was unforgiving: modernize the architecture, unlock scalability, and remove the automation bottleneck, all without changing a single observable behavior at the hardware boundary. 100% functional parity was not a nice-to-have. It was the entire mandate.
We did not start by writing code. We started by understanding the code that already existed. A general-purpose AI coding assistant operates at the snippet level and has no model of a twenty-year-old application; our platform is purpose-built for legacy modernization and works at the method, module, and architecture level. That distinction is what made parity achievable at this scale.
The engagement ran as a phased, turnkey modernization with four guiding principles:
"We had been quoted multi-year rewrites that all carried the same fine print: we couldn't promise the new system would behave exactly like the old one. ConvertEdge inverted that. Parity was the starting constraint, and the differential harness proved it on every commit. That is what let us put hardware-adjacent code into production without holding our breath."
Principal Software Architect, anonymized at the client's request
The deliverables fell into four categories: assessment and documentation outputs, a modern target architecture, the six converted components themselves, and the differential test harness that made 100% parity demonstrable rather than merely claimed.
A complete software bill of materials and dependency graph across all six components, surfacing hidden couplings the team had never had a full picture of.
Auto-generated documentation that reads as if an architect had been with the application since day one: functional specs, technical design, and integration maps for the hardware interfaces.
A target architecture, microservices decomposition, framework choices, and a step-by-step, risk-ordered migration plan, so the team knew exactly what to modernize, in what order, and at what effort.
A security-vulnerability map of the legacy code plus a running gap report and to-do list that tracked every piece of business logic from "identified" to "converted and parity-verified."
The six VB6 components were mapped onto a modern, service-oriented .NET stack, decomposing the monolithic, tightly coupled originals into independently scalable services with clean REST boundaries, while preserving the exact wire-level behavior at the hardware interface.
This was the keystone of the engagement. The QA Agent auto-generated unit, integration, and regression tests; our QA specialists refined them and ran them against live servers. The harness drove identical inputs through the legacy VB6 component and the new .NET service in parallel and compared every output, byte for byte. A differential check only passed when modern behavior matched legacy behavior exactly, including the hardware-protocol edge cases nobody had documented. Parity stopped being a claim and became a gate that every commit had to clear.
The headline numbers tell the operational story, but the strategic outcome was bigger. With the six components modernized, the automation roadmap that had been blocked for years was unblocked. The new .NET services scale horizontally where the VB6 originals could not, and the team finally has documentation, an SBOM, and a regression suite for code that had been a black box since the acquisitions that brought it in.
Most importantly, none of this came at the cost of stability. Because parity was enforced on every commit, the hardware-adjacent components went to production without a single behavioral regression at the equipment boundary, exactly the risk the client had been most afraid of.
The Assessment Agent ingested a representative slice of the estate and returned technical-debt analysis, an architecture-drift map, security findings, and prioritized modernization hotspots, turning an opaque VB6 black box into a planned program of work in days.
We generated functional and technical documentation, an SBOM, and integration maps, then produced the .NET target architecture and a migration plan that ordered the six components by blast radius: lowest-risk first, hardware-adjacent last.
The Modernization Agent automated roughly 70% of the conversion, emitting converted code, a gap report, a to-do list, and pull requests. Our engineers and the client's architects reviewed every PR and carried the remaining business logic over by hand.
The QA Agent generated test suites that specialists refined and ran against live servers. Differential checks confirmed legacy-to-modern parity for every component (with approximately 2x faster test creation than a manual approach) before anything was accepted.
Components were promoted to production in risk order, each behind a final human-in-the-loop approval. The hardware-adjacent components shipped last, verified clean by the differential harness, completing the migration with zero behavioral regressions.
Outcomes from other engagements where the constraint was real and the result was production, not a roadmap.
An FDE squad embedded for 12 weeks deployed an AI agent across EMR and CRM systems to automate referral and prior-authorization workflows end to end.
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