Perfect-Ai
Perfect-AI is a serverless AI tools marketplace built with AWS, where users can buy, customize, and deploy AI tools, while creators can publish and earn. It features a personalized LLM engine, automated AWS workflows (Lambda, DynamoDB, S3, AppSync), and a no-code tool builder that auto-deploys tools. The platform delivers scalable automation, user-specific AI outputs, and revenue analytics, creating a complete AI ecosystem for businesses and creators.
Problem
Most AI tools in the market suffer from: One-size-fits-all outputs (no personalization) No automation or multi-step workflows Lack of integration with cloud services Hard for beginners to create or customize AI tools No marketplace where creators can sell AI tools Perfect-AI wanted a single ecosystem where: Users can buy AI tools like apps. Creators can publish AI tools and earn. The backend automatically creates, deploys, and manages each tool using AWS. A personalized engine ensures each tool adapts to the user’s data.
Solution
I built Perfect-AI as a full AI marketplace + automation engine, powered heavily by AWS. 1. AI Tools Marketplace Users browse & purchase AI tools Dynamic pricing, subscription plans, and upsells Tools install instantly with one click Creators publish AI tools with templates Each tool is powered by backend AWS workflows. 2. Personalized AI Engine Every user gets a personalized environment: Personalized prompts Personalized context Personalized memory User-specific recommendation engine Auto-adjusted LLM behavior based on user style This gives every user a unique AI experience, unlike generic LLM apps. 3. AWS Automation Backend Behind the scenes, the platform uses a fully automated AWS pipeline: AWS Services Used AWS Lambda – runs all automation tasks API Gateway – serverless API endpoints DynamoDB – stores tools, user data, histories S3 – stores tool configs, files, assets SNS & SQS – notifications & task queues EventBridge – schedule automation workflows Cognito – user authentication CloudWatch – logs, monitoring, cost alerts Bedrock / OpenAI API – LLM execution AppSync (GraphQL) – real-time system for some features Automation Features Auto-provisioning of new AI tools Auto-scaling without downtime Auto cost-optimization Automatic deployment pipeline Personalized memory engine per user Role-based access control 4. Tool Builder (No-Code Tool Creator) Creators can build tools using: Custom prompts Template flows API integrations Condition-based logic Input-output mapping The system then auto-compiles the tool and deploys it as a serverless function. 5. Business Analytics Dashboard Tool usage insights Revenue dashboard for creators User behavior tracking Personalized recommendations Cost tracking for AWS resource usage Technical Architecture Frontend Next.js React TailwindCSS Framer Motion Stripe (for payments) Backend Node.js GraphQL (AppSync) AWS Lambda / API Gateway DynamoDB S3 SNS/SQS AI Layer OpenAI GPT-4 / GPT-5 AWS Bedrock (Claude) Custom memory engine Personalized prompt modifier User-profile-based recommendations
Tech Stack
Result
After deployment: :rocket: 1. High Productivity for Users Repetitive work reduced by 60–80% Personalized AI outputs improved accuracy significantly :moneybag: 2. New Revenue Stream for Creators Creators earn by publishing AI tools in the marketplace Automated payouts using Stripe :chart_with_upwards_trend: 3. Fully Scalable AI Platform Serverless architecture → zero maintenance AWS handles load spikes automatically :robot_face: 4. Personalized AI for Every User AI-generated results matched user preferences Better retention & engagement rates