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How Can AI Help Businesses Save Time, Reduce Work, and Get More Customers?
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Cookies, Craft & New Possibilities. 🍪
Exploring new concepts, visual languages, and possibilities with AI — without the typical generative look.
Direction, craft and attention to every frame.
The macro shots of the cookie texture almost don't read as AI at all, which I'm guessing was the whole point. What's your process for avoiding that generic AI sheen everyone's gotten tired of?
I built DocuMind — a financial document automation platform for Chartered Accountants
One thing I noticed while working on financial-document workflows was that a lot of a CA's time can go into repetitive document processing rather than actual professional decision-making.
So I started building DocuMind — a tool designed to automate the repetitive parts of working with financial documents.
💡 The idea
A CA uploads a financial document such as a bank statement, and DocuMind handles the mechanical processing:
Document → Extraction → Normalization → Transaction Processing → Rules → Validation → Structured Output → Excel
Instead of manually going through large documents and preparing the same data repeatedly, the system converts the information into structured, usable outputs.
What I built:
- PDF/document extraction
- OCR for scanned documents
- Transaction extraction and normalization
- Python-based rule processing engine
- Data validation and reconciliation
- Automated Excel generation
- Database-backed document management
- Authentication and user-level document access
- RAG/AI assistant architecture for document Q&A
- Local AI support through Ollama for privacy-sensitive workflows
- React frontend + FastAPI backend
Architecture:
React Frontend
↓
FastAPI Backend
↓
Document Processing Orchestrator
↓
Extraction / OCR
↓
Normalization
↓
Transaction Processing
↓
Rule Manager
↓
Validation & Reconciliation
↓
Structured Results
↓
Excel / CA-ready Output
The AI layer is intentionally not responsible for deterministic calculations.
Python handles things that should be predictable and reproducible, while AI/RAG is used where natural-language understanding and document interaction actually add value.
Why I'm building it:
I recently discussed the idea with a CA and got an important piece of feedback:
The goal shouldn't be to replace the CA's professional judgment — it should be to eliminate the repetitive work around it.
That changed the direction of the product.
I'm now refining DocuMind around workflow automation, accuracy, traceability, privacy, and useful outputs rather than trying to make AI “diagnose” financial information.
What's next:
I'm currently working on:
Improving the CA-focused workflow
Better document extraction
More robust validation
Source/page-level traceability
Better Excel outputs
Testing the workflow with real CAs
Expanding into additional financial-document workflows
Eventually building a more complete AI-powered document assistant
This project has been a great learning experience because I'm not just building features — I'm learning how to turn a real-world problem into a software architecture.
Tech Stack:
Frontend: React, Vite, Tailwind CSS
Backend: Python, FastAPI
Database: SQLite, SQLAlchemy
Data Processing: pandas, openpyxl
Documents: PyMuPDF, pypdf, Tesseract OCR, Tabula
AI/RAG: Ollama, ChromaDB, Sentence Transformers
Authentication: JWT
Deployment: Local-first architecture, with cloud deployment planned for later
I'm currently open to freelance and full-time opportunities in:
Full-Stack Development · Backend Development · Python/FastAPI · React · AI Automation · Document Processing · SaaS Development
Building products that solve boring, expensive problems is what I want to do more of. 🚀
#BuildInPublic #FullStackDevelopment #Python #FastAPI #React #AI #Automation #SaaS #Freelance #SoftwareDevelopment #ProductDevelopment
Just wrapped up building flux/, an interactive UI with real-time WebGL rendering, custom GLSL shaders, and scroll-driven animation, built entirely from scratch with vanilla JS, what do you think?
It's been a super fun shift for me, most of my background is Python automation, AI integration, and data pipelines, but diving into frontend/UI work like this has been genuinely rewarding.
Link's in my portfolio if you want to see it in action. Always open to talk automation, AI integration, or interactive web work.
The vanilla JS route is the part I would defend - straight to GLSL instead of inheriting a scene graph you never needed. The one that caught me on scroll-driven work was portrait: visible width is 2*z*tan(fov/2)*aspect, so at 0.75 aspect you see less than half of what you...