A company migrating from a legacy CRM to a new SaaS platform had 180,000 customer records in rough shape: duplicates, outdated addresses, missing VAT numbers that B2B invoicing required. A straight lift and shift would have poisoned the new system from day one. The internal team had no capacity to validate records at that volume.
A staged migration pipeline that processes records in batches. Each batch runs through address validation against a postal API, duplicate resolution with configurable matching logic, and VAT enrichment via a commercial data provider. Records that can’t be resolved automatically get flagged for manual review with full context. Clean records land in the destination with a complete audit trail.
flowchart LR SRC[Legacy CRM<br>180k records] --> BATCH[Batch<br>extract] BATCH --> ADDR[Address<br>validation] ADDR --> DEDUP[Deduplicate] DEDUP --> VAT[VAT<br>enrichment] VAT --> CLEAN[Clean records] VAT --> FLAG[Flagged for<br>manual review] CLEAN --> DEST[New<br>platform]
The entire migration execution, including reprocessing after manual resolution, reconciliation reporting with before/after quality metrics per batch, and a rollback window for the first 30 days. One point of contact throughout - no coordination overhead between a build team and an ops team.
94% of records migrated clean on first pass. The other 6% were flagged for review rather than silently corrupted. Migration finished in the agreed window with zero downtime on the source system. The customer started on the new platform with clean data instead of inheriting years of accumulated garbage.
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