Data Migration Between Legacy Systems with UiPath

Two systems, no interface, no export option

Moving from an old line-of-business application to a new system, there was neither an API nor a usable export. Manually transferring thousands of records would have taken weeks and been error-prone—with high risk for the go-live.

The target vendor and implementer offered CSV templates for new records only—not a full stock migration from the legacy system. Parallel operation was not affordable short term; the cutover date was fixed because licences and maintenance contracts were expiring.

Purchasing, production, and shipping teams kept working in the legacy system while the project team already planned training on the new application. Any delay in data transfer would have pushed go-live and caused double-maintenance cost.

Data quality and traceability

The migration had to be traceable: which record was transferred when, and did source and target values match? Deviations should be detected and documented rather than slipping unnoticed into the new system.

Historical quirks—old part numbers, inconsistent units, duplicate vendor master records—were known and must not be copied silently. Audit and operations demanded reconciliation reports per wave and a clarification list before production switch.

Without audit-ready logs it would be impossible later to tell whether an error came from legacy data, mapping, or manual rework. That increased pressure for an automated yet controlled approach.

RPA instead of custom development – a pragmatic choice

Custom interface development was not economical: both systems were closed, and the legacy vendor no longer provided support. RPA through the UI was the only path that met timeline and budget.

The robot also had to tolerate minor UI changes and wait times; the manufacturer could not risk weeks of downtime. Hence pilot waves, idempotent runs, and clear abort criteria instead of a big-bang approach.

Compared with manual entry, RPA had to be not only faster but reproducible: the same record should land identically in the target on rerun—a prerequisite for IT and business sign-off.

UiPath reads and writes via the UI

A UiPath robot reads the records through the legacy system's screens, validates them against defined rules, applies the field mapping, and enters them into the target system—also via the GUI. This makes migration possible even though neither system offers a technical interface.

Delivery builds on process automation with RPA and legacy modernization—a typical pattern when interfaces are missing, as we outline in the RPA vs API integration comparison.

“Without an API we still had to move on schedule. UiPath turned the UI into a bridge—with a log per record, not Excel and hope.”

Validation, mapping, and reconciliation

Required fields, formats, and value ranges are checked before writing. After each run the robot produces a reconciliation report comparing source and target; deviations go to a clarification list instead of the production system.

Mapping rules were documented with business and IT: which source fields map to which targets, default values for gaps, which records are deliberately excluded. Mapping changes went through versioned configuration, not ad-hoc robot edits.

Key-user spot checks after each wave ensured business plausibility—the robot delivers consistency; people review exceptions and edge cases.

Controlled, repeatable process

The migration ran in several waves: first a small pilot set, then larger batches overnight via the Orchestrator. Every record was logged so reruns stayed safe and idempotent. Delivered by Groenewold IT Solutions in East Frisia.

The Orchestrator scheduled runs outside core hours; on failure the process stopped with notification to IT and project lead rather than leaving half-finished records in the target. Legacy production stayed undisturbed.

Budget and effort can be weighed using the automation cost calculator versus manual migration; similar projects appear in our automation references.

Operations, monitoring, and handover

“Migration does not end with the last record—we needed runbooks for who updates the robot after UI changes and how clarification cases are closed.”

After acceptance, IT received documentation on selectors, exception handling, and escalation. A shadow run before final cutover compared samples automatically with manual checks. Made in Germany from Leer/East Frisia—close coordination on site, not anonymous remote-only rollout.

A fast move without weeks of typing

Instead of manual entry, the robot handled the bulk of records overnight. The go-live happened on schedule; deviations were documented and cleaned up before launch.

Key users spent time on clarification and business sign-off, not repetitive typing from the legacy system. Double maintenance between old and new shrank to the technically unavoidable minimum.

Project lead had daily transparency on progress, error rate, and open clarification items—no black box during critical migration weeks.

Reference for RPA data migration

The project shows how data migrations between systems without an interface can be handled with UiPath alone—with validation, mapping, and an audit-ready log.

For mid-market and manufacturing the pattern transfers: when neither API nor export exists, GUI RPA plus controlled waves and reconciliation reports. More examples in the automation hub and legacy modernization projects.

Long term a follow-up project can build real interfaces—until then RPA delivers a safe transition without go-live risk from manual mass entry.