Automated Political Graphics SaaS

I’m building a web-based SaaS that generates polished political campaign graphics on demand. The core goal is straightforward: help candidates and staff create eye-catching visuals without relying on a full design team. For launch, the platform only needs to output social-media-ready artwork, specifically formatted for Facebook, Instagram, and WhatsApp.

Here’s what I need from you:

1 ⃣
Multi-Tenant Architecture
Roles & Permissions: Role | Access | Notes —|—|— Super Admin | Manage Admin
accounts, set User limits | Desktop/Web app Admin (Leader/Politician) | Upload
templates, create Users, generate campaigns | Desktop/Web app User (Worker) |
Upload photo, view generated posters, download/share | Android app
Authentication & Authorization - JWT Tokens - Role-based Access Control (RBAC) -
Optional OAuth2.0 for future scalability
Tenant Isolation Options - Option A: Schema per tenant (more secure, easier data
isolation) - Option B: Shared DB with TenantID (cost-efficient, easier to scale) -
Recommendation: Shared DB + TenantID for MVP
2 ⃣
Android App – User Workflow
Steps: 1. Login → JWT token 2. Upload photo - Auto crop & face alignment -
Background removal - Skin tone normalization 3. View generated posters 4. Download /
share
Photo Preprocessing Stack: - Face Detection → OpenCV/Dlib / Azure Face API - Auto
Crop → YOLO / MediaPipe FaceMesh - Background Removal → U²Net / RemBG /
Adobe API - Skin Tone Normalization → GAN-based model
Output: Normalized portrait stored in S3 / Cloud Storage
3 ⃣
Admin App – Template Management
Template Upload - PSD / CorelDRAW - Parse layers → psd-tools for PSD - Identify
placeholders: - Leader Photo - User Photo - Text layers - Store metadata in DB -
Campaign text stored with template reference
Poster Generation - Generate posters for each User - Variations: Backgrounds, Fonts,
Colors
4 ⃣
AI Graphic Generation Pipeline
Pipeline Flow: Template + Leader Photo + User Photo + Campaign Text → AI
Processing → Generated Posters → Storage (S3)
AI Processing Details - Place photos → blending + borders → background variations -
Text styling → font/color variation - Variations → generate 50+ unique images per user
AI Models & Tools Task | Tool / Model —|— Background Variation | Stable Diffusion XL
+ ControlNet Compositing / Blending | OpenCV / PIL Font/Color Variation | Custom ML
rules Face Alignment | Dlib / MediaPipe
GPU Requirements - Minimum: NVIDIA T4 / RTX 4090 - Recommended: A10 / A100
(bulk generation)
5 ⃣
Queue Management & GPU Scaling
Components: - Redis + Celery or RabbitMQ / Kafka - Each Admin → job queue - GPU
workers: - Pull jobs - Batch inference - Push results to S3 - Scheduling: Round-robin per
Admin
6 ⃣
Backend & API Design
Tech Stack - Node.js → REST APIs (Admin/User management, Auth) - FastAPI
(Python) → AI microservices (poster generation, preprocessing) - PostgreSQL → multi
tenant DB - Storage → S3 / MinIO (images + templates)
Security - HTTPS everywhere - AES-256 encrypted storage for photos - RBAC →
prevent cross-tenant leaks - Content moderation → NSFW / abusive templates
Key Development Challenges
1. PSD/CorelDRAW parsing complexity
2. GPU load balancing & cost optimization
3. AI outputs consistency
4. Queue fairness (multiple Admins)
5. Security → tenant data isolation, encryption
6. Content moderation → avoid misuse
MVP Recommendation: - Shared DB + TenantID - Cloud GPU (AWS/GCP A10) - PSD
upload first, skip CDR initially - Basic AI pipeline → API-based preprocessing