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This project, along with the AI Toolbox, ElonGPT, and LSB Applied AI Studio, was developed for Elon University and remains their intellectual property.
All source code is maintained in private repositories. Please respect Elon University's property and do not attempt to access, replicate, or distribute these systems without authorization.
Demo access is provided for portfolio demonstration purposes only.
AI-powered business plan generator with parallel agent processing achieving 3-4x speedup. Production-validated by North Glass LLC with comprehensive sections and citation-rich output. [ELON UNIVERSITY PROPERTY - PRIVATE REPOSITORY]
Creating comprehensive business plans is time-intensive and requires expertise across multiple domains: market analysis, financial modeling, operations planning, and risk assessment. Traditional consultants charge thousands of dollars and take weeks to deliver. Entrepreneurs and small businesses need faster, more affordable solutions without sacrificing quality.
The challenge was to build an AI-powered business plan generator that could produce professional, citation-rich business plans in under 60 seconds while maintaining accuracy and comprehensiveness. The system needed to handle complex parallel processing, integrate real-time web research, and ensure quality through automated validation.
I developed an AI-powered business plan generator using FastAPI and OpenAI GPT-4 with a parallel agent architecture. The system employs 7 specialized sub-agents running concurrently via Python asyncio, achieving 3-4x speedup over sequential processing.
A three-phase workflow (clarification → parallel generation → review) ensures quality: input validation, distributed agent execution, and automated scoring (0-10 per section) with regeneration for substandard content. Web search integration provides citation-rich market research, while code interpreter tools enable accurate financial projections. The system was production-validated by North Glass LLC, demonstrating real-world business value.
┌─────────────────────────────────────────────────────────────────┐
│ USER INPUT (via Next.js 15) │
│ Company name, industry, target market, funding needs, vision │
└────────────────────────┬────────────────────────────────────────┘
│
▼
┌─────────────────────────────────────────────────────────────────┐
│ PHASE 1: CLARIFICATION │
│ ┌────────────────────────────────────────────────────────┐ │
│ │ Clarification Agent (OpenAI GPT-4) │ │
│ │ • Validates business concept feasibility │ │
│ │ • Identifies missing information │ │
│ │ • Structures data for downstream agents │ │
│ └────────────────────────────────────────────────────────┘ │
└────────────────────────┬────────────────────────────────────────┘
│
▼
┌─────────────────────────────────────────────────────────────────┐
│ PHASE 2: PARALLEL GENERATION (asyncio) │
│ ┌──────────────────┐ ┌──────────────────┐ ┌───────────────┐ │
│ │ Executive │ │ Market Analysis │ │ Operations │ │
│ │ Summary Agent │ │ Agent │ │ Agent │ │
│ │ • Vision/mission │ │ • Competitive │ │ • Processes │ │
│ │ • Key objectives │ │ landscape │ │ • Supply │ │
│ │ │ │ • Web search │ │ chain │ │
│ └──────────────────┘ └──────────────────┘ └───────────────┘ │
│ │
│ ┌──────────────────┐ ┌──────────────────┐ ┌───────────────┐ │
│ │ Marketing │ │ Financial │ │ Risk │ │
│ │ Agent │ │ Agent │ │ Agent │ │
│ │ • GTM strategy │ │ • Projections │ │ • Mitigation │ │
│ │ • Pricing │ │ • Code │ │ • Compliance │ │
│ │ • Acquisition │ │ interpreter │ │ │ │
│ └──────────────────┘ └──────────────────┘ └───────────────┘ │
│ │
│ ┌──────────────────┐ │
│ │ Appendix Agent │ │
│ │ • Citations │ │
│ │ • Supporting │ │
│ │ documents │ │
│ └──────────────────┘ │
│ │
│ All agents run concurrently via Python asyncio → 3-4x speedup │
└────────────────────────┬────────────────────────────────────────┘
│
▼
┌─────────────────────────────────────────────────────────────────┐
│ PHASE 3: REVIEW & QA │
│ ┌────────────────────────────────────────────────────────┐ │
│ │ Quality Assurance Agent (OpenAI GPT-4) │ │
│ │ • Scores each section 0-10 (completeness, accuracy) │ │
│ │ • Identifies gaps and inconsistencies │ │
│ │ • Triggers regeneration for scores < 7 │ │
│ │ • JSON Schema validation via Pydantic │ │
│ └────────────────────────────────────────────────────────┘ │
└────────────────────────┬────────────────────────────────────────┘
│
▼
┌─────────────────────────────────────────────────────────────────┐
│ COMPREHENSIVE BUSINESS PLAN OUTPUT │
│ • Executive Summary • Market Analysis • Operations Plan │
│ • Marketing Strategy • Financial Projections • Risk Assessment │
│ • Appendix with Citations │
│ Generated in < 60 seconds with citation-rich content │
└─────────────────────────────────────────────────────────────────┘Performance: Parallel execution via asyncio achieves 3-4x speedup over sequential processing. 7 agents run concurrently, reducing total generation time from ~3-4 minutes to under 60 seconds.
Quality: Automated QA agent scores each section 0-10, triggers regeneration for scores below 7, and validates JSON Schema compliance before final delivery.
Integration: Web search (Tavily API) for market research, code interpreter for financial calculations, FastAPI backend with Next.js 15 frontend.
7 specialized sub-agents running concurrently via Python asyncio for 3-4x speedup over sequential processing. Generates comprehensive business plans in under 60 seconds.
Clarification phase validates inputs, parallel generation distributes work across agents, and review phase ensures quality with 0-10 scoring system.
Real-time market research through web search tools provides citation-rich, data-backed insights for competitive analysis and industry trends.
Financial modeling and calculations powered by code execution capabilities for accurate projections and business metrics.
Structured output validation ensures consistent, parseable business plans with guaranteed section completeness and formatting.
Automated review agent scores each section 0-10, identifies gaps, and triggers regeneration for substandard content before final delivery.
Each agent focuses on a specific business plan section, running in parallel for maximum efficiency:
Synthesizes company vision, mission, and key objectives into compelling executive overview
Conducts competitive research, identifies target markets, and analyzes industry trends with web search
Designs operational processes, supply chain logistics, and organizational structure
Develops go-to-market strategy, pricing models, and customer acquisition channels
Builds financial projections, revenue models, and funding requirements using code interpreter
Identifies potential risks, regulatory compliance needs, and mitigation strategies
Compiles supporting documents, citations, and supplementary data for comprehensive reference
FastAPI backend with async/await patterns enables high-concurrency agent orchestration. Python asyncio manages parallel execution of 7 specialized sub-agents. OpenAI GPT-4 with function calling provides agent intelligence and tool use (web search, code interpreter). Pydantic models enforce JSON Schema validation for structured output.
Next.js 15 frontend with TypeScript for type safety. Business plan input forms with validation and user-friendly error handling. Real-time progress indicators during generation. Responsive design for mobile and desktop access.
OpenAI GPT-4 for agent intelligence with function calling. Tavily API for web search and market research. Code interpreter tools for financial calculations and projections. Three-phase workflow ensures quality: clarification, parallel generation, and review.
Azure Container Apps deployment with auto-scaling capabilities. FastAPI documentation endpoint provides interactive API exploration. Production validation by North Glass LLC demonstrates real-world business value.
This project was developed during my time at Elon University as part of their AI initiative, which includes several innovative projects:
All projects are the intellectual property of Elon University and are maintained in private repositories for educational and institutional purposes.
I'm grateful for the opportunity to work on these innovative AI solutions and showcase the technical approaches through this portfolio while respecting the university's ownership and privacy requirements.