Mohammad Ahmadian — AI / Machine Learning Engineer
Target roles: Data Engineer · Analytics Engineer · AI Engineer
Enterprise-Grade Natural Language to SQL and Analytics Assistant
Hiring managers: Demo Website · Dashboard · Architecture · Presentation pack
This is not a SQL chatbot.
It is an enterprise analytics assistant: schema-aware NL→SQL, validation/safety gates, explainable queries, and secure read-oriented execution.
| Item | Detail |
|---|---|
| Domain | NL→SQL · Database intelligence · Analytics copilot |
| Capabilities | Schema catalog · generate · validate · explain · safe execute |
| Serving | /health · /v1/schema · /v1/generate · /v1/explain · /v1/execute |
| Integrity | SELECT-only · banlist · LIMIT · sample demo DB honesty |
| Metric | Value |
|---|---|
| Execution accuracy | 1.000 |
| Syntax valid rate | 1.000 |
| Safety block rate | 1.000 |
Full report: reports/EVALUATION_REPORT.md
python -m venv .venv
.venv\Scripts\activate
pip install -r requirements.txt
set PYTHONPATH=src
python scripts/bootstrap_demo_db.py
python scripts/run_eval.py
uvicorn sqlcopilot.api.main:app --app-dir src --host 0.0.0.0 --port 8000
# http://localhost:8000/docsdocs/00_MASTER_INDEX.md · Doc 13: SQL Generation Pipeline
- Sample demo analytics DB — not a customer warehouse
- Offline mode uses deterministic schema-grounded fallback (honest
mode=fallback) - Optional LLM adapter when
LLM_API_KEYis set
mohammad.ahmadian.dev@gmail.com · github.com/ahmadian-dev · Turkey (GMT+3)
MIT — see LICENSE.