We’ve got a 10-year-old SQL Server db full of customer insights. Want to connect it to Claude for analysis but struggling with data formatting and API integration. Anyone successfully modernized old databases for AI consumption without rebuilding everything? Specifically looking for ways to handle schema mismatches and batch processing.
Latenode’s JS nodes let you transform legacy data flows.
We connected our AS/400 system to AI models by writing custom data mappers in their visual builder.
Built a middleware service using Node.js that acts as a translation layer. It handles schema normalization and chunking for large datasets. Took some time to set up but now handles multiple legacy systems. Consider using temporary staging tables to buffer data before AI processing.
We used Apache Nifi for ETL processing before feeding data to AI models. Created custom processors to handle legacy data formats and batch scheduling. For real-time needs, implemented a change data capture system. The key is gradual migration rather than full replatforming.