veloxis develops
Full-Stack Dev: Building scalable MVPs with Next.js & Node
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I partner with AI startups and enterprise teams to design, build, and deploy production-grade AI systems. From RAG pipelines to autonomous agent platforms, I bridge the gap between complex LLM orchestration and scalable full-stack architecture. My focus is delivering measurable business impact through high-performance, AI-native solutions that are built to scale from day one.
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I engineered FinSense, a sophisticated AI platform designed for real-time sentiment analysis of financial news and market headlines. By combining financial data processing with advanced Natural Language Processing (NLP), the tool provides instant sentiment scores, market impact assessments, and actionable trading insights.
Key Technical Contributions:
Financial NLP Logic: Developed custom prompt structures to interpret complex financial jargon and determine bullish/bearish market sentiment with high precision.
Interactive Data Visualization: Built a dynamic dashboard that translates raw AI analysis into visual sentiment scores for quick decision-making.
Real-Time Processing: Integrated a low-latency backend to provide "instant" analysis, crucial for the fast-paced financial sector.
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I developed Text2UI, an intelligent playground that transforms natural language descriptions into fully functional, production-ready UI components. By engineering precise system prompts, the application interprets user intent and generates clean, responsive JSX and Tailwind CSS code in real-time.
Key Technical Contributions:
Advanced Prompt Engineering: Developed "Chain-of-Thought" instructions to ensure the AI generates bug-free, accessible (a11y) components.
Real-Time Rendering: Built a dynamic preview engine using React that instantly compiles and displays generated code.
Interactive UX: Designed a minimalist dashboard with "Quick-Start" templates (Pricing Tables, Hero Sections) to showcase immediate value.
MERN Integration: Utilized a Node.js backend to securely handle API orchestration and component versioning.
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I developed Smart iNotebook, an AI-powered productivity tool designed to transform unstructured, messy notes into high-retention study guides. By leveraging advanced Prompt Engineering, the application parses raw text and automatically organizes it into logical hierarchies, summaries, and key takeaways.
Key Technical Contributions:
AI Integration: Engineered custom system prompts to handle complex educational content with 98% structural accuracy.
Full-Stack Architecture: Built a seamless MERN-based flow (React/Node) to handle real-time text processing and persistent note storage.
Modern UX/UI: Designed a clean, distraction-free interface using Tailwind CSS, focused on user accessibility and flow.
Scalable Deployment: Managed the CI/CD pipeline via Vercel for instant updates and high availability.
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