AI Driven Advanced Analytics. Reasoning based Sequential Agents. Connect to any database - o3-mini/deepseek-r1 / gemini-flash-2.0.
Published: February 14, 2025
Try it Free 👉 tigzig.com (Mobile/ Web). Open Source
- Full 1 Hour Video on YouTube
Build and Deploy AI Driven Advanced Analytics with Reasoning & Sequential Agents: Live App
AI Advanced Analytics App (Open Source) - Multi (Sequential) Agents. Try it 👉 tigzig.com Connect to any database - o3-mini/deepseek-r1 / gemini-flash-2.0.
- Want to try it quickly?
Use the "Sample" functionality to auto-upload a sample file. No DB credentials needed.
What are the Advanced Analytics capabilities?
- Multi-step agent flow. Analysis plan by reasoning models, execution by GPT-4o
- Choice of reasoning model: Gemini Flash 2.0, o3-Mini, DeepSeek-R1.
What about data connections?
- Connect to any remote database or upload a file.
- No database? Not to worry- Temporary Postgres DB created on-the-fly
Debugging?
Execution logs , Agent reasoning view
- What are the BAU Functionalities?
Natural Language (NL)-to-SQL, NL-to-Python: Statistical Analysis & Charts, Interactive Tables with quick Stats
Demoed Examples
- Bank Credit Cards: Modeling Data Mart creation + Customer Profile (1M-row Customer Table & 10M Transactions Table on AWS RDS MySQL).
- Weighted Score-Based Ranking of Indian credit card issuers
Covered in Video, in addition to demo:
- Query failures, live debugging, performance & cost considerations
- High Level architecture & API Flows
- Agent setups and orchestration.
Want to clone, deploy, modify?
- 1 primary repo, 3 backend repos, 6 Flowise Agent Schemas + Tool Schemas
- Step-by-step deployment guide + how to deploy app with Cursor using natural language prompts.
How was it built?
- Built with Cursor AI - my top AI-coding tool
- AI Backend: Flowise AI - My top LLM App platform.
- Python Charts/Stats: E2B on Flowise
- UI: React, TypeScript, Vite, Shadcn.
- DB Connections: Custom built FastAPI servers.
- Deployment: Vercel (main site), Hetzner (via Coolify for FastAPI & Flowise)
- On-the-fly PostGreSQL DBs: Neon (blazing fast, great API's, ideal for LLM apps).
- Auth: Auth0 (experimental)
- Workflow: Make.com for Auth records (experimental)
Video Guide
Caveats
Prototype (working version)
YouTube Time Stamps
Click on time-stamp (in YouTube description) to jump direct to section of interest
Build and Deploy AI Driven Advanced Analytics with Reasoning& Sequential Agents: Live App
- 00:00:00 - Quick Overview of Capabilities
- 00:02:08 - Connect to DB & Analyze: Modeling Data Mart & Customer Profile Summary
- 00:06:43 - File Upload & Analyze: India Bank Ranking - Credit Cards
- 00:09:21 - Sequential Agent Framework: Setups & Orchestration
- 00:15:02 - Performance Considerations (Quality, Speed, Reliability, Latencies, Agent Backend, SQL Call Failures, Database Server, API Call Failures, Error Catching, Validations)
- 00:23:09 - Cost Considerations
- 00:29:49 - Live Error Debugging
- 00:37:37 - High Level Architecture & API Flows
- 00:45:08 - Deployment Guide & GitHub Repo Walkthroughs
- 00:58:19 - App Functionalities - How to Have Cursor Explain it.
- 01:01:05 - Top Resources
- 01:01:51 - End
GitHub Repos & Schemas
- Main Repo
- FastAPI Server : SQL DB Connect
- FastAPI Server: Neon Database
- FastAPI : LLM API Calls Proxy Server
- Sequential Agents Schema - Flowise
In docs folder in Main Repo, including JSON for Database Connect Tool.