The Business Problem
Every time a growing business adds another tool — whether an e-commerce platform, warehouse management system, accounting package, or marketing CRM — discrepancies begin to fester:
- Platform A says an item is SKU-101; Platform B recorded it as SKU_101_V2; the warehouse knows it only by its EAN barcode.
- Orders get stuck in limbo because tax calculations or shipping line items differ by one penny between platforms.
- Finance and Operations spend hours in end-of-month meetings arguing over whose revenue and inventory reports reflect reality.
Instead of piling on more brittle point-to-point Zapier recipes, the business needed an authoritative reconciliation engine that maintains data truth across systems.
The Architectural Solution
I engineered Sync Evolve as a lightweight, high-performance reconciliation and data governance engine powered by a FastAPI backend, asynchronous background workers, and an intuitive React interface.
ERP / WEB / WMS INGESTION & QUEUE
REDIS / CELERY MATCHING ENGINE
DETERMINISTIC & FUZZY RECONCILED STATE
POSTGRES & ALERTS
1. Ingestion Pipelines with Guaranteed Delivery
Sources emit records via webhooks or scheduled change-data-capture polls. Jobs are queued and acknowledged with idempotency keys, guaranteeing that duplicate webhooks never corrupt data states.
2. Hybrid Matching Algorithms
Records are matched via a layered strategy: first through deterministic key matching (UUIDs, SKU, EAN), falling back to configurable attribute heuristics and fuzzy similarity matching for legacy records with dirty titles.
3. Instant Exception Governance & Observability
Instead of silent failures where records quietly drift, discrepancies are categorized into an actionable triage queue. Operations teams can inspect the diff, approve automated resolution rules, and replay failed synchronization events with one click.
The Business Outcomes
- Drastic Audit Time Reduction: Month-end inventory and revenue reconciliation dropped from 3 days of manual spreadsheet cross-referencing to under 30 minutes of automated verification.
- Prevented Revenue Leakage: Caught and flagged pricing and order currency mismatches before orders were fulfilled at a loss.
- Reliable Foundation: Provided clean, verified master data that unlocked subsequent automation and AI initiatives across the company.