AI-Powered CSR Proposal Generation & Email Automation System 1. Executive Summary Your organization possesses a CSR donor database (2014–2024) containing CSR donor companies, CSR budgets, focus sectors, past donation amounts, contact emails, and historical engagement records. This data is extremely valuable but currently underutilized due to the manual effort required to create proposals and communicate with donors. This project aims to build a fully automated AI system that leverages the ChatGPT API to generate customized CSR proposals and send them automatically to donor companies via email. The system will integrate your existing donor data, analyze patterns, generate personalized messaging, and manage communication at a large scale. The result will be a complete CSR outreach automation platform designed to increase funding opportunities while reducing manual workload. 2. Project Goals The primary goals of this system are: 2.1 Automation Automatically generate CSR funding proposals using AI. Automatically send proposals to CSR donor companies. 2.2 Personalization Tailor each proposal based on: o CSR focus sector o Company giving history o CSR priority themes o Funding amount patterns o Past engagement with your organization 2.3 Efficiency Remove manual proposal writing. Eliminate repetitive donor email drafting. Scale communication to thousands of CSR companies. 2.4 Enhanced Fundraising Increase CSR donor engagement. Improve response rates with personalized messaging. Unlock hidden opportunities in historical donor lists. 3. Problem Statement Nonprofits face several challenges in fundraising: Manual proposal writing consumes time and delays outreach. CSR companies expect customized, high-quality proposals aligned with their mandates. Large donor datasets (like your 2014–2024 CSR database) cannot be manually processed at scale. Sending personalized emails to hundreds or thousands of CSR companies is nearly impossible manually. Past CSR donors often lapse due to lack of timely communication. This system solves all of these with automation. 4. System Overview The system will combine: 4.1 AI Proposal Generation Using OpenAI ChatGPT API: CSR proposals Concept notes Project outlines Impact reports Customized funding request emails 4.2 Automated Email Delivery Using SendGrid / Amazon SES / Mailgun: Bulk email sending Delivery & bounce tracking AI-generated subject lines Email logs & history 4.3 Existing CSR Donor Database Integration (Your data from 2014–2024) Company name CSR focus area CSR budget Past funding Email contacts This data will drive personalization and segmentation. 5. Detailed Project Scope 5.1 Data Integration Layer The system will import your existing CSR data: CSV / Excel SQL database dump Multiple files (yearly segmented data) Data fields to be mapped: Company Name Contact Person Email Address CSR Budget / Annual CSR Spend CSR Focus Sectors Location Previous donation to your organization Donation year Amount funded Type of project funded Data Cleaning Features: Duplicate removal Invalid email detection Standardization Automated segmentation (in next module) 5.2 CSR Donor Segmentation Engine The system will automatically categorize CSR donors into segments: Segment A: High-Value Repeat Donors Companies who funded 2+ times between 2014–2024. Segment B: High-Potential Donors Companies with: Large CSR budgets Previously funded similar projects Segment C: Sector-Matched Donors Companies whose CSR mandate aligns with your projects. Segment D: New Prospects Companies with CSR budgets but no interaction yet. Each segment receives differently structured AI proposals. 5.3 AI Proposal Generation Module Powered by OpenAI ChatGPT API AI will generate: CSR Funding Proposal Project Concept Note Detailed Technical Proposal Project Introduction Budget Summary Expected Impact Alignment with CSR Act 2013 Sustainability Plan Organization Overview Call-to-Action for Funding Proposal Personalization Factors: Personalization Element CSR sector match Source CSR budget size Company CSR policy Historical CSR data Company region Past donation amount CSR compliance area Your 2014–2024 data Project relevance SDG alignment Your project descriptions AI mapping Proposal Outputs: Email-ready text Downloadable PDF (optional) Stored in database for future reference 5.4 Email Automation System Features: Bulk email sending Throttling to prevent spam flags AI-generated subject lines Custom email body for each company Attach proposal in-text or as a PDF Delivery, open, and bounce tracking Supported Email Providers: SendGrid (recommended) Amazon SES Mailgun SMTP (fallback) Email Logging Includes: Company name Email ID Proposal version Time sent Delivery status Opened or not 5.5 Admin Dashboard Dashboard Features: Upload CSR data View donor list Preview AI proposals Review & edit before sending Send batch emails Track email delivery Read proposal history Download reports 6. System Architecture (Deep Detail) 6.1 Backend Python (FastAPI) or Node.js (NestJS) ChatGPT API integration Email service APIs Proposal generation logic Bulk email queue handling 6.2 Frontend React front-end dashboard Donor list management Template selection & preview Logs view 6.3 Database PostgreSQL / MySQL Tables: o CSR_Donors o CSR_Emails o Proposals o Logs o Templates o API Usage 6.4 Infrastructure Hosted on AWS EC2 / DigitalOcean Docker container support Daily backups Scalable architecture 7. Security Measures Data Security: AES-256 encrypted storage HTTPS everywhere No unnecessary personal data shared with ChatGPT Role-based access control Email Security: SPF, DKIM, DMARC configuration Throttle controls Anti-spam safeguards 8. Development Timeline (Detailed) Week Task Week 1 Week 2 Requirement finalization, system architecture, database schema Backend setup, CSR data import module Week 3–4 ChatGPT integration + prompt engineering Proposal generation engine Week 5 Week 6–7 Email automation + API setup Donor segmentation engine Week 8 Week 9–10 Dashboard development Testing & QA (emails + proposals) Week 11 Week 12 Deployment, documentation Total: 10–12 weeks 9. Deliverables Technical Deliverables Backend API Frontend Dashboard AI Proposal Generator Email Automation Engine CSR Donor Segmentation Database setup Admin control panel Logs & Reporting System Complete documentation Documentation Deliverables API documentation Deployment guide User manual Admin manual 10. Expected Outcomes 10.1 Organizational Benefits 80–90% reduction in CSR proposal writing workload Personalized proposals sent at scale Better communication with past donors Increased conversion rates Better utilization of your 10-year CSR dataset 10.2 Technical Advantages Scalable outreach Reliable email delivery Automated proposal writing Centralized data management Consistent proposal quality