We run a multi-client ERP system (PostgreSQL backend) with 280+ SQL-based reports. Users select reports via Java UI, but we face challenges: high maintenance, limited flexibility, performance bottlenecks, and lack of deeper insights.
Context:
- 10+ years of growing store data (daily additions)
- Multi-client setup → strict data privacy/security required
- Heavy daily reporting usage
Looking for input on:
- Benefits AI can bring to ERP reporting
- Recommended tech stack (LLM, RAG, vector DB, Java integration)
- Handling of parameters & report intent (summary/detail, financial/operational)
- SQL strategy – dynamic AI SQL vs optimized templates
- Extra insights (trends, anomalies, predictions)
- LLM cost management for frequent queries
- Data privacy & security best practices
Would love to hear experiences, recommendations, or case studies.