In Progress
AI Database Agent
Ask a database a question in plain English and get back a validated, schema-aware SQL answer — built and documented version by version, from a simple Text-to-SQL prototype to a secured, RAG-augmented, tool-calling agent.
.NETASP.NET CoreSQL ServerQdrantOllamaNext.js
The problem
Natural-language database interfaces are easy to demonstrate but considerably harder to make reliable. The system needs to understand database structure, generate useful SQL, validate generated queries, control execution, and provide useful answers without blindly trusting model output.
Engineering focus
- LLM orchestration
- Schema discovery
- Natural-language to SQL
- SQL validation and security
- RAG and semantic search
- Tool calling and agent workflows
- Observability and evaluation
- Production architecture
Architecture
user > show pending orders from Dubai this month
→ agent: schema discovery
→ agent: SQL generation
→ validator: query approved
→ SQL Server: execution
→ result: 42 rows · 118 ms
Roadmap
Build roadmap
01Public content siteLive
02Flagship project — AI Database AgentIn build
03Accounts & auth — SQL ServerPlanned
04Subscriptions & billingPlanned
05SaaS — hosted agentPlanned
06CoursesLater