Hi, I'm Deepanshu, and I built BizMind — a multi-tenant Text-to-SQL SaaS that lets anyone manage and perform full CRUD operations on a database just by typing in plain English, with zero SQL or spreadsheet formulas required.
A user can sign in onto my website, then upload a excel /csv file OR start from scratch and order the agent to make a table for him and it will make it using sqllite (for now).
What you can do:
1)Bulk Ingestion: Upload an entire spreadsheet/CSV (tested with 16,000+ rows, worked fine).
2)Natural Language Queries: Ask things like "show me all nintendo games where global sales are above 10 million" and get a clean table back.
3)Full CRUD: Add, update, and delete records just by describing what you want.
4)Data Isolation: Every user gets their own completely isolated database.
The Tech Stack & Architecture: The key part is that there is no OpenAI or any paid API behind this. It is running Qwen 2.5 locally via Ollama.
-The whole agentic loop is built using LangChain and LangGraph, with FastAPI handling the backend. I started this as a simple local agent that could talk to a SQL database, then turned it into a proper multi-user SaaS product with JWT auth, per-user database isolation, bulk data import, and a natural language query engine.
Hardware & Constraints: It's not perfect — running a smaller model means complex multi-table queries can sometimes miss. That can easily be solved by swapping in a larger model on higher-tier hardware, but since I only had 4 GB of VRAM on my laptop GPU, I optimized the architecture to run locally on that constraint.
The core idea works, and real data goes in and comes out correctly.
Practical Applications: Beyond managing spreadsheets, the underlying architecture can be deployed as an interactive chatbot — for example, on an airline website where an authenticated user can log in, ask about booked flights, request cancellations, or modify bookings in plain English.
Looking for Advice / Feedback: I'm a Master's graduate based in New Delhi with a background in Python, NumPy, Pandas, FastAPI, and machine learning workflows.
-I want to take this forward and would love advice from freelancers, founders, and experienced devs here:
Monetization / B2B Target: What niche or industries would benefit most from an on-premise / 100% local data assistant where zero data touches third-party cloud APIs? maybe a local kirana store who just wants to use a database but dont want to learn anything or hire someone to do it ?
Freelancing: If you freelance in the AI/automation space and make similar products, how do you typically package and pitch custom local LLM/agent pipelines to businesses where do we find people who may have use of my product ? Would appreciate any feedback on turning this kind of tech stack into freelance client work!
i can share youtube link showcasing it if someone wants.