Wildmind AI
A full-stack generative AI SaaS platform combining image, video, music, ad, song, and product generation in a unified creative studio — with an intelligent assistant, integrated payments, and a credits-based economy.
A full-stack generative AI SaaS platform combining image, video, music, ad, song, and product generation in a unified creative studio — with an intelligent assistant, integrated payments, and a credits-based economy.
Creators and businesses needed to work across multiple disconnected tools — one for images, another for video, another for music — with no unified workflow, no shared asset library, and no intelligent orchestration layer. Every provider had a different API, different pricing model, and different quality profile. Building on top of them required constant re-integration.
The challenge was to build a single platform that abstracted all of this complexity — giving users a seamless creative studio while giving the business full control over provider routing, cost management, and quality optimization.
We designed and built Wildmind AI from the ground up — a multi-tenant SaaS platform with a unified generation studio, an intelligent assistant that orchestrates multi-step creative workflows, a credits-based economy with Razorpay integration, and a provider abstraction layer that routes requests to the optimal AI model based on task type, cost, and latency.
Unified interface for image, video, music, ad creative, song, and product generation — all from a single workspace with shared asset management.
A conversational assistant that understands creative intent, gathers requirements, proposes workflows, and executes multi-step generation pipelines on behalf of the user.
Abstraction layer routing requests across Fal AI, Runway ML, MinMax, BFL Flux, and OpenAI — with automatic fallback, cost optimization, and latency monitoring.
Flexible credit system with Razorpay integration, subscription tiers, usage tracking, and real-time balance management across all generation types.
Bull-based job queues handling 2,000+ daily AI requests with priority lanes, retry logic, and real-time status updates via WebSockets.
Automated S3 pipeline managing 10,000+ media assets with CDN delivery, thumbnail generation, and organized per-user asset libraries.
Microservices architecture with a NestJS API gateway, async job queues, Redis caching, and PostgreSQL with Prisma ORM. The frontend is a Next.js App Router application with Redux Toolkit for state management and real-time updates via WebSockets.
Platform handles 500+ simultaneous users with sub-second response times on the UI layer and async processing for generation tasks.
Provider routing and Redis caching reduced average generation response latency by 40% compared to direct single-provider integration.
Unified adapter pattern reduced time to integrate a new AI provider from weeks to days — a 60% reduction in onboarding effort.
Queue-based microservices process 2,000+ daily generation requests with 99.9% completion rate and automatic retry on transient failures.