Smart AI Syllabus Generator Development
Budget: $1,500 – $3,000 USD
AI SaaS MVP – Build a Smart Syllabus Generator for University Professors (LLMs, APIs, Custom Workflows)
We're developing an MVP for a next-gen SaaS platform that helps university professors automatically generate, update, and enhance course syllabi using AI. The platform will allow professors to upload existing syllabi or input course details and receive a fully updated version with improved content, aligned resources, recommended learning activities, and more—based on live web research, academic database integration, and instructional design best practices.
This is a hybrid AI system using a mix of private-cloud-hosted LLMs and API access to tools like OpenAI, DeepSeek, Perplexity, Consensus, YouTube, Amazon, and SCOPUS. We need an experienced AI developer (or small team) who understands multi-agent workflows, can set up smart content pipelines, and knows how to orchestrate LLMs in a cost-efficient way. Frontend should be minimal and functional, with user authentication, template customization, and bilingual support (English/Spanish). This is not a low-code or no-code project—we’re looking for someone fluent in AI architecture, backend development, and platform thinking.
MVP Project Overview
An AI-Powered Syllabus Generator, Content Updater, and Enhancer for University Professors
We are building a production-ready MVP for a SaaS, a powerful AI-powered workflow automation system specifically designed for University Professors. This application will help professors automatically update, enhance, and modernize their course syllabi using cutting-edge AI tools, instructional design best practices, and rich research integration.
What We're Building
The AI Assistant enables professors to either:
• Automatically generate or update a syllabus (hands-off), or
• Walk step-by-step through a guided AI-enhanced customization flow.
Behind the scenes, the platform:
• Conducts deep, topic-specific academic research via API integrations with platforms like Consensus, Perplexity, SCOPUS, YouTube, Amazon, etc.
• Performs content classification and analysis based on instructional design principles and course duration.
• Repackages results into a clean, updated, professional syllabus with templates and personalization options.
What This Is NOT
This is not a simple ChatGPT wrapper or prompt-to-pdf tool.
If you’re a low-code enthusiast using tools like V0, Lovable, Bolt, Bubble, or 8n8, this is not the right project for you.
We are looking for AI engineers who can build hybrid intelligent systems, preferably using platforms like Cursor, Windsurf, or Tempo, who understand:
• Multi-agent workflows
• Custom LLM orchestration
• Backend logic at a code level
Core AI Functionalities Required
Context-Aware Information Retrieval
Web + API Research Automation
Syllabus Structuring & Repackaging via LLM Templates
Smart Suggestions (Books, Learning Activities, Quizzes, Case Studies)
Voice Prompt Support (Whisper API or equivalent)
Multi-step AI-driven conversation flows
Bilingual UX (English & Spanish)
Instructor-centric UX with customizable settings
Architecture Overview
This will be a hybrid AI architecture, combining:
• Local AI Models (Private Cloud)
For general content handling, memory, and cost optimization.
Suggested: LLaMA 3, Mixtral 8x7B via RunPod, etc.
• External LLMs & Agents (for deep reasoning & scraping)
Suggested: GPT-4o, DeepSeek, Claude 3.5, Gemini 1.5, Perplexity Pro.
• Vector DBs & Retrieval Systems
Suggested: LlamaIndex + ChromaDB
• Workflow Memory & Logging
Track decisions, inputs, and recommendations across user sessions.
Tech Stack Suggestions (Open to Feedback)
• Voice Processing: OpenAI Whisper / AssemblyAI
• Local AI Runtime: RunPod / AWS / Google Cloud (GPU-based)
• Data Layer: Supabase, PostgreSQL, or MongoDB
• Notifications: Firebase, Twilio
• Backend: FastAPI / Flask
• Authentication: JWT / OAuth + 2FA
• LLM Cost Optimization Strategy: Route light tasks locally, heavy tasks externally.
Development Roadmap
Phase 1: Architecture & MVP Build
• Propose 2 architectural design options with costs
• Implement core AI processing flow
• Basic UI/UX + AI chat-based interaction
Phase 2: Workflow Automation & Customization
• Complete AI integrations
• Enable memory, feedback loops, and document processing
• Add output templates and branding support
Phase 3: Optimization & Intelligence Layer
• Real-time suggestions
• Quizzes & resources generator
• Scheduled syllabus refresh option
• Usage tracking, LLM usage analytics, and feedback scoring
Security & Access Control
• Multi-user roles (Admins, Managers, Analysts, Professors)
• Audit logs for all AI-assisted actions
• Role-based permission controls
• Option to share/publicly publish syllabi to a community pool
Who We're Looking For
• Experienced AI developer or small dev team
• Proficient in custom LLM integrations and orchestration
• Familiar with cloud infrastructure for private AI
• Ability to work with APIs like Perplexity, Consensus, SCOPUS, YouTube, Amazon
• Experience building agentic workflows from scratch
• Can deliver both backend + clean, minimalist frontend
Bonus if you have:
• Experience training or fine-tuning LLMs
• Knowledge of instructional design principles
• Experience working with Latin American EdTech or multilingual SaaS apps
• Ability to consult on long-term tech stack sustainability
Ready to Build Something Truly Transformative?
We're looking for someone who is excited to collaborate, iterate fast, and create a product that has the power to reshape how professors worldwide (especially in Latin America) update and deliver their courses.
Let’s build this app together!
We're developing an MVP for a next-gen SaaS platform that helps university professors automatically generate, update, and enhance course syllabi using AI. The platform will allow professors to upload existing syllabi or input course details and receive a fully updated version with improved content, aligned resources, recommended learning activities, and more—based on live web research, academic database integration, and instructional design best practices.
This is a hybrid AI system using a mix of private-cloud-hosted LLMs and API access to tools like OpenAI, DeepSeek, Perplexity, Consensus, YouTube, Amazon, and SCOPUS. We need an experienced AI developer (or small team) who understands multi-agent workflows, can set up smart content pipelines, and knows how to orchestrate LLMs in a cost-efficient way. Frontend should be minimal and functional, with user authentication, template customization, and bilingual support (English/Spanish). This is not a low-code or no-code project—we’re looking for someone fluent in AI architecture, backend development, and platform thinking.
MVP Project Overview
An AI-Powered Syllabus Generator, Content Updater, and Enhancer for University Professors
We are building a production-ready MVP for a SaaS, a powerful AI-powered workflow automation system specifically designed for University Professors. This application will help professors automatically update, enhance, and modernize their course syllabi using cutting-edge AI tools, instructional design best practices, and rich research integration.
What We're Building
The AI Assistant enables professors to either:
• Automatically generate or update a syllabus (hands-off), or
• Walk step-by-step through a guided AI-enhanced customization flow.
Behind the scenes, the platform:
• Conducts deep, topic-specific academic research via API integrations with platforms like Consensus, Perplexity, SCOPUS, YouTube, Amazon, etc.
• Performs content classification and analysis based on instructional design principles and course duration.
• Repackages results into a clean, updated, professional syllabus with templates and personalization options.
What This Is NOT
This is not a simple ChatGPT wrapper or prompt-to-pdf tool.
If you’re a low-code enthusiast using tools like V0, Lovable, Bolt, Bubble, or 8n8, this is not the right project for you.
We are looking for AI engineers who can build hybrid intelligent systems, preferably using platforms like Cursor, Windsurf, or Tempo, who understand:
• Multi-agent workflows
• Custom LLM orchestration
• Backend logic at a code level
Core AI Functionalities Required
Context-Aware Information Retrieval
Web + API Research Automation
Syllabus Structuring & Repackaging via LLM Templates
Smart Suggestions (Books, Learning Activities, Quizzes, Case Studies)
Voice Prompt Support (Whisper API or equivalent)
Multi-step AI-driven conversation flows
Bilingual UX (English & Spanish)
Instructor-centric UX with customizable settings
Architecture Overview
This will be a hybrid AI architecture, combining:
• Local AI Models (Private Cloud)
For general content handling, memory, and cost optimization.
Suggested: LLaMA 3, Mixtral 8x7B via RunPod, etc.
• External LLMs & Agents (for deep reasoning & scraping)
Suggested: GPT-4o, DeepSeek, Claude 3.5, Gemini 1.5, Perplexity Pro.
• Vector DBs & Retrieval Systems
Suggested: LlamaIndex + ChromaDB
• Workflow Memory & Logging
Track decisions, inputs, and recommendations across user sessions.
Tech Stack Suggestions (Open to Feedback)
• Voice Processing: OpenAI Whisper / AssemblyAI
• Local AI Runtime: RunPod / AWS / Google Cloud (GPU-based)
• Data Layer: Supabase, PostgreSQL, or MongoDB
• Notifications: Firebase, Twilio
• Backend: FastAPI / Flask
• Authentication: JWT / OAuth + 2FA
• LLM Cost Optimization Strategy: Route light tasks locally, heavy tasks externally.
Development Roadmap
Phase 1: Architecture & MVP Build
• Propose 2 architectural design options with costs
• Implement core AI processing flow
• Basic UI/UX + AI chat-based interaction
Phase 2: Workflow Automation & Customization
• Complete AI integrations
• Enable memory, feedback loops, and document processing
• Add output templates and branding support
Phase 3: Optimization & Intelligence Layer
• Real-time suggestions
• Quizzes & resources generator
• Scheduled syllabus refresh option
• Usage tracking, LLM usage analytics, and feedback scoring
Security & Access Control
• Multi-user roles (Admins, Managers, Analysts, Professors)
• Audit logs for all AI-assisted actions
• Role-based permission controls
• Option to share/publicly publish syllabi to a community pool
Who We're Looking For
• Experienced AI developer or small dev team
• Proficient in custom LLM integrations and orchestration
• Familiar with cloud infrastructure for private AI
• Ability to work with APIs like Perplexity, Consensus, SCOPUS, YouTube, Amazon
• Experience building agentic workflows from scratch
• Can deliver both backend + clean, minimalist frontend
Bonus if you have:
• Experience training or fine-tuning LLMs
• Knowledge of instructional design principles
• Experience working with Latin American EdTech or multilingual SaaS apps
• Ability to consult on long-term tech stack sustainability
Ready to Build Something Truly Transformative?
We're looking for someone who is excited to collaborate, iterate fast, and create a product that has the power to reshape how professors worldwide (especially in Latin America) update and deliver their courses.
Let’s build this app together!