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 get fined.

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