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I’m currently building at the intersection of AI, backend engineering, and blockchain.
🤖 AI / GenAI: Building LLM-powered applications, RAG pipelines, AI agents, workflow automation, and experimenting with model fine-tuning.
⚙️ Backend: Designing scalable APIs and distributed systems using Python, FastAPI, Node.js, PostgreSQL, Redis, Kafka, and AWS.
🔗 Blockchain: Building and contributing to Web3 infrastructure across Ethereum, Solana, Cardano, and other ecosystems.
I’m particularly interested in building production-ready AI products and developer tools that solve real-world problems.
Currently open to collaborating with founders, startups, and teams building ambitious products.
@sachin ruhil RAG pipelines paired with FastAPI and Kafka can cover a lot of production use cases. I’d be curious how you’re approaching evaluation and observability for the agent workflows.
The network for creativity
Join 1.25M professional creatives like you
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Creatives on Contra have earned over $150M and we are just getting started
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Built my new portfolio with Figma and Lovable.
I wanted it to feel very internet-native, so I added things like personalized cursors and the ability to see other people in the shared file — leaning into that chronically-online, always-in-a-design-tool feeling 🙃
I also wanted the site to share a little more of who I am beyond the work, with personal photos, a notebook for thoughts, and a running list of things I’m reading and watching.
Such a unique experience, amazing work!
This is my AI Customer Support and Lead Generation Agent, built with n8n.
The workflow starts when a customer sends a message. The AI Agent understands the customer's request and responds automatically.
It also uses conversation memory to maintain context during the conversation.
When a customer wants to place an order, the agent collects important details such as their name, phone number, email, service, quantity, and requirements.
Finally, the customer's information is automatically saved into Google Sheets as a new lead.
This automation helps businesses handle customer inquiries and organize leads without manual work.
Agents are amazing. Building & using them is a genuine wise career choice in my opinion.
AI Digital Marketing Strategy Architect Design (Draft 1 of Project)
AI Digital Marketing Strategy Architect application. Here is a high-level overview of the project's architecture and features:
Core Functionality: The application is a comprehensive 4-phase digital marketing strategy builder that helps users plan, build, and automate their growth engines. It's designed with an elegant, editorial-style interface featuring high-contrast typography and clean layouts.
Phase 1: Foundation: A module for establishing the product's niche, generating detailed target personas using AI, and setting up the foundational tech stack (analytics, landing pages, email lists).
Phase 2: Content Engine: Focuses on organic reach. It includes an interactive SEO topic cluster generator, a visual ContentMap graph to visualize pillar links, and an AI-powered repurposing studio that transforms a single article into multiple formats (threads, LinkedIn posts, video scripts).
Phase 3: Growth & Acceleration: Built for paid and organic scale. Features a paid ad testing matrix with AI "Scale vs Kill" rules, an organic social winner analysis simulator, and an Answer Engine Optimization (AEO) readiness auditor.
Phase 4: Scale & Automation: Focuses on workflow automation. Includes a visual Zapier/n8n pipeline builder, a live lead simulator for AI-personalized email drafting, and an A/B testing loop optimizer.
Technical Architecture: A full-stack application utilizing React on the frontend and an Express server on the backend to securely manage Gemini API calls. It persists project state locally, includes preset templates (like SaaS or E-commerce), and offers a robust export engine to generate Markdown or Raw JSON blueprints.
Clean work