You will get AI-Powered Quotation Generator to Create Professional PDF Proposals
Project details
Manually creating quotations takes up time and leaves too much room for inconsistency. I built this Quotation Generator to solve that it’s a clean, streamlined tool designed for businesses that want to send out professional, accurate proposals fast.
What makes this project different is that it's not just a form or template it's a full web app built with Streamlit and Python. It comes with an admin panel where you can easily manage your pricing, company info, and quotation formatting. I’ve also added optional GPT integration to help generate polished service descriptions if needed, but everything stays under your control.
I can make sure it works exactly how you need it.
What makes this project different is that it's not just a form or template it's a full web app built with Streamlit and Python. It comes with an admin panel where you can easily manage your pricing, company info, and quotation formatting. I’ve also added optional GPT integration to help generate polished service descriptions if needed, but everything stays under your control.
I can make sure it works exactly how you need it.
Language
EnglishWhat's included $250
These options are included with the project scope.
$250
- Delivery Time 2 days
- Number of Revisions 2
- Number of Hours of Work 30
About Sam
Software Developer
Walkersville, United States - 6:27 am local time
I build production systems, from a published Obsidian plugin with 5,000+ users to a multi-exchange trading bot handling live orders across Robinhood and Schwab.
What I do best:
- Automation & API Integration: Multi-brokerage trading systems with real-time risk controls, ETL pipelines processing 2.8M+ records, fault-tolerant batch processing with retry logic and failover
- Full-Stack Web Apps: React/Next.js frontends, Flask/FastAPI backends, Supabase/PostgreSQL databases. End-to-end from schema design to CI/CD deployment
- Data Science & ML: Scikit-learn classifiers, PySpark pipelines on HPC clusters, feature engineering, bias-elimination techniques. Built a UFC prediction model hitting 78% accuracy
- Cloud Infrastructure: Azure (Data Factory, DevOps pipelines, Key Vault, NSG), AWS, Docker, GitHub Actions. Automated IaC provisioning at an enterprise internship
Shipped projects:
- Storyteller Suite: TypeScript/React Obsidian plugin, 5,000+ users, 78+ PRs merged, modular architecture with YAML persistence and cross-platform support
- Multi-Exchange Trading Bot: Python system integrating Robinhood & Schwab APIs with order management, extended-hours trading, dry-run mode, and automated reporting
- UFC Fight Predictor: Full-stack ML app with dual-model bias elimination, Flask API, Azure deployment, 7,500+ fight dataset
- AI-Powered Study Platform: RAG pipeline with LangChain, FAISS/ChromaDB vector stores, FastAPI microservices, Row-Level Security
- Batch Geocoding Tool: React SPA with multi-provider fallback, exponential backoff, Haversine distance calculations
Stack: Python, TypeScript/JavaScript, React, Next.js, Flask, FastAPI, PostgreSQL, Supabase, Azure, AWS, Docker, Scikit-learn, PySpark, Git
Certs: Azure Fundamentals (AZ-900), AWS Cloud Practitioner
Penn State Data Science senior.
Steps for completing your project
After purchasing the project, send requirements so Sam can start the project.
Delivery time starts when Sam receives requirements from you.
Sam works on your project following the steps below.
Revisions may occur after the delivery date.
Revision
If you have any revisions based on the scope of your package, I will address them promptly. Once you are satisfied and approve the delivery, the project is complete!