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Can you give some more info on the results? Meaning, correctness, completeness, etc... Would you use it for e.g. tax information? Because if wrong, you could

• rashidae 1y ago
  We're using AI to write the boring integration code that moves data from System A to System B. The actual data processing is deterministic code that's tested like any critical system. Correctness: 100% schema mapping accuracy after human validation. We've never had a data type mismatch or field misalignment make it to production. The AI suggests mappings at ~85% accuracy, humans catch and correct the remaining 15%. Completeness: Zero data loss incidents. We run reconciliation reports comparing source record counts to destination. Any discrepancy fails deployment. Most common issue: the AI initially missing compound key relationships, which we catch in testing. Tax/Financial Data: Yes, we handle financial data for several clients, including: QuickBooks to data warehouse pipelines (invoice/payment data) Payroll system integrations Revenue reconciliation between CRM and accounting Our approach for sensitive data: AI generates the integration logic, never sees actual records Test with synthetic data matching production schemas Run parallel processing for 1-2 cycles to verify accuracy Maintain full audit logs of all transformations Human sign-off required before production cutover