Freelance AI Engineers in New Delhi

Freelance AI Engineers in New DelhiFreelance AI Engineers in New Delhi

Projects People

AKASH VASHISHTHA

proDelhi, India

Versatile Fullstack Engineer | Web & Mobile Expert

$50k+: Earned

5x: Hired

5.0: Rating

89: Followers

Top

Versatile Fullstack Engineer | Web & Mobile Expert

Cover image for Légacie Phase 1

Légacie Phase 1

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6

Cover image for Realm - Social Media Platform for Music Producers and Artists

Realm - Social Media Platform for Music Producers and Artists

1

109

Cover image for TestBest | LSAT® Prep & Tutoring

TestBest | LSAT® Prep & Tutoring

2

136

Cover image for AI Platform Stabilization and Enhancement for Kaie

AI Platform Stabilization and Enhancement for Kaie

3

99

proGhaziabad, India

Full Stack Developer | AI Tool, Web App, MVP & SaaS Products

$10k+: Earned

4x: Hired

4.9: Rating

21: Followers

Full Stack Developer | AI Tool, Web App, MVP & SaaS Products

Cover image for Innovation Intelligence Platform

Innovation Intelligence Platform

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12

Cover image for AI Search Optimization Platform

AI Search Optimization Platform

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13

Cover image for Flight Booking Platform

Flight Booking Platform

1

12

Cover image for Digital Business Card Platform

Digital Business Card Platform

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9

proNew Delhi, India

Mobile App Architect • React Native Expert • 50+ App Shipped

$1k+: Earned

1x: Hired

5.0: Rating

12: Followers

Mobile App Architect • React Native Expert • 50+ App Shipped

Cover image for GymCare Management System Development

GymCare Management System Development

1

8

Cover image for Rizz AI: Image Generation App Development

Rizz AI: Image Generation App Development

1

7

Cover image for Voice-First Productivity App Development

Voice-First Productivity App Development

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3

Cover image for Development of AthleteOS AI Fitness Platform

Development of AthleteOS AI Fitness Platform

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6

Building MVPs for startup founders with clean UX in a week.

1x: Hired

5.0: Rating

58: Followers

Building MVPs for startup founders with clean UX in a week.

Cover image for Tenderseal - AI-Driven Tender Management Platform Development

Tenderseal - AI-Driven Tender Management Platform Development

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1

Cover image for Reqwest - Designing an Efficient API Testing Platform

Reqwest - Designing an Efficient API Testing Platform

3

3

Cover image for SpongebobLabs - AI Research Lab Website Development

SpongebobLabs - AI Research Lab Website Development

1

5

Cover image for SaaSking AI - Enterprise Website Redesign

SaaSking AI - Enterprise Website Redesign

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1

Jagwinder Singh

Full Stack Developer

Full Stack Developer

Cover image for AI Tattoo Generator App

AI Tattoo Generator App

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0

Cover image for AI Dating App

AI-powered dating companion

AI Dating App AI-powered dating companion that helps users improve their dating profiles, generate personalized conversation starters, and craft engaging replies using AI. It acts like a virtual “dating wingman,” helping users get better matches and more meaningful conversations on dating apps. - AI matchmaking analyzes user interests, behavior, and preferences to suggest highly compatible matches. - Smart conversation starters and AI-generated prompts help users break the ice and improve engagement. - AI-based profile verification and moderation detect fake profiles, scams, and inappropriate content for safer dating. - Personalized recommendations adapt over time based on swipes, chats, and interaction patterns to improve match quality. - Sentiment and compatibility analysis provide insights into communication styles and relationship potential.

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1

23

Cover image for 🛥️ AI Yacht Booking Platform

🛥️ AI Yacht Booking Platform (Web + Mobile App) A luxury yacht booking platform that allows users to discover, compare, and book yachts for events, vacations, and private charters. The system includes a responsive web app and cross-platform mobile application with real-time availability, AI-powered recommendations, and secure payments. User App (Web + Mobile) - Yacht discovery with filters (location, price, capacity, amenities) - AI-powered yacht recommendations based on user preferences and behavior - Interactive yacht detail pages with gallery & specs - Real-time availability calendar - Secure checkout & booking confirmation - Trip history & cancellations Owner Dashboard - Add/manage yacht listings - Set pricing & availability - View booking requests - Earnings analytics - AI-based pricing suggestions based on demand, seasonality, and booking trends Admin Panel - User & listing management - Booking approvals & dispute handling - Platform analytics - AI insights for demand forecasting and platform optimization Impact (sample metrics) - Faster yacht discovery with AI suggestions - Reduced booking friction via chatbot assistance - Higher conversion rate due to personalization - Better pricing efficiency for owners Delivered a scalable, luxury-focused booking experience enhanced with AI-driven personalization and intelligence, connecting yacht owners and customers in a seamless digital ecosystem.

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21

Cover image for AI Customer Service Automation Platform

AI Customer Service Automation Platform An intelligent AI-driven customer support platform that automates and streamlines customer service across multiple channels. It helps businesses deliver faster, smarter, and more consistent support by combining AI chatbots, ticket automation, and omnichannel communication in one unified system. The platform uses NLP and machine learning to understand customer queries, provide instant responses, and intelligently route complex issues to human agents. It reduces workload, improves response times, and enhances customer satisfaction. Key Features: - AI Chatbot for 24/7 instant customer support - Omnichannel support (chat, email, social media, WhatsApp) - Smart ticketing with auto-categorization and routing - AI agent assist with reply suggestions and insights - Workflow automation for repetitive tasks - Sentiment analysis for priority handling - Self-service knowledge base integration - Multilingual support for global users - Real-time analytics and performance dashboards - Easy integrations with CRM and third-party tools This platform enables businesses to scale customer service efficiently while reducing costs and improving overall customer experience through automation and AI intelligence.

2

3

221

Trashu Vashisth

Building Production-Grade AI Agents & RAG Systems

12: Followers

Building Production-Grade AI Agents & RAG Systems

Cover image for Built a highly scalable Retrieval-Augmented Generation

Built a highly scalable Retrieval-Augmented Generation (RAG) chatbot designed to interact with private datasets/PDFs. Unlike standard LLMs, this system minimizes hallucinations by retrieving real-time context from a local knowledge base before generating responses. Key Features: Semantic Search: Implemented Vector Embeddings to perform high-speed similarity searches across thousands of document chunks. Smart Retrieval: Integrated a retrieval pipeline using LangChain to fetch the most relevant context for user queries. Source Citation: Configured the bot to provide source references from documents, ensuring data transparency and accuracy. Optimized Performance: Used FAISS/Chromadb for efficient vector storage and retrieval.

4

295

Cover image for The Problem: Sales teams waste 60%

The Problem: Sales teams waste 60% of their time researching leads instead of closing them. The Solution: I built a custom Agentic AI Pipeline that automates deep-dive business intelligence and lead scoring. Key Technical Highlights: Multi-Agent Architecture: Built using CrewAI, featuring a 'Business Intelligence Specialist' (for real-time research) and a 'Senior Sales Director' (for strategic scoring). High-Speed Intelligence: Powered by Llama 3.3-70B for near-instant reasoning and decision-making. Real-time Web Scoping: Integrated Tavily AI to fetch live revenue data, employee counts, and market positioning. Enterprise Storage: A robust SQLite backend to manage lead pipelines with a sleek Streamlit dashboard. Smart Throttling: Engineered custom rate-limiting and token-trimming logic to ensure 99.9% uptime even under heavy API constraints. How it works: Simply enter a company name and URL. The AI agents scour the web, analyze the company's "AI potential," calculate a priority score (0-100), and even write a personalized sales pitch—all in under 30 seconds.

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25

Cover image for I built a professional, end-to-end

I built a professional, end-to-end AI Receptionist system designed to automate clinic appointment management. This isn't just a chatbot; it's an AI Agent that can reason, use tools, and manage a live database autonomously. Key Contributions: Agentic Reasoning: Integrated CrewAI with Llama 3.3 (Groq) to enable the agent to understand complex user intents (Booking vs. Cancellation) and relative time (e.g., "next Tuesday at 3pm"). Autonomous Tool Use: Developed custom Python tools that allow the agent to verify real-time availability in a SQLite database and execute atomic transactions without human intervention. High-Performance Backend: Built a robust API using FastAPI to handle asynchronous requests between the AI agent and the database. Premium Dashboard: Designed a modern, Glassmorphic UI using Tailwind CSS that provides a real-time sync of the clinic’s schedule. The Result: A seamless, hands-free system that reduces administrative overhead by 100%, allowing clinic staff to focus on patients while the AI handles the entire scheduling lifecycle. Tech Stack: Python, CrewAI, Groq API, FastAPI, SQLite, Tailwind CSS

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Cover image for An autonomous AI system that

An autonomous AI system that turns a simple voice command into a deep-dive research report in seconds. No typing, no manual searching. Key Highlights: Voice Control: Uses Speech-to-Text for hands-free research triggers. Multi-Agent Intelligence: Powered by CrewAI & Llama 3.3 (Groq) to find, verify, and summarize live web data. Voice Synthesis: Delivers an instant audio summary via ElevenLabs. Automated Export: Generates a professional PDF report automatically. Tech Stack: CrewAI, Groq, ElevenLabs, Streamlit, DuckDuckGo API.

1

63

Websites & automations. AI-native workflow, design-led.

$5k+: Earned

9: Followers

Websites & automations. AI-native workflow, design-led.

Cover image for NanoMech: The Real-Time Multimodal AI

NanoMech: The Real-Time Multimodal AI Trading Assistant 📈🤖 Built for the Gemini Hackathon Traders know that in the market, seconds equal dollars. By the time you switch between your chart, your analysis tools, and your risk calculator, the candle has already moved, and your setup is gone. I wanted to fix this. For the Gemini Hackathon, I built NanoMech—an AI that sits on top of your screen, sees exactly what you see, and gives you a complete trade plan in seconds. No API keys required, and no leaving your chart. 💡 The Solution NanoMech runs as two frameless, transparent overlays on top of any trading platform. It uses Google Gemini 2.5 Flash's multimodal vision capabilities to visually read your screen and deliver instant insights. Overlay 1: Market Analysis Trend: Analyzes bullish/bearish market structure and moving average crossovers. Liquidity: Evaluates order book depth, bid/ask walls, and support/resistance zones. Momentum: Breaks down candlestick patterns, volume behavior, and price velocity. Overlay 2: Trade Setup & Risk Management AI-Extracted Targets: Instantly provides Entry Price, Target Price, and Stop Loss. Live CALC Engine: Calculates Risk Amount ($), Position Size (Units), and Risk-to-Reward (R:R) Ratio. Everything updates live as you type in your desired risk percentage. 🛠️ How It Works (Under the Hood) Vision-to-Text Processing: Captures the screen in real-time using the mss library and sends the raw screenshot to Google Gemini 2.5 Flash via the Google GenAI SDK. Prompt Engineering: Engineered strict structured prompts using [ANALYSIS] and [TRADE] tags to force the LLM to output reliably parseable price data. Regex Extraction: Uses regex to pull the exact Entry, Target, and Stop prices from the AI's response and wire them directly into the local risk calculator. Custom Desktop UI: Built always-on-top transparent overlays using Python's Tkinter, utilizing threading to keep the UI fully responsive during API calls. Hands-Free Scanning: Integrated a global hotkey (Ctrl+A+I) and an Auto Mode that scans the chart every 20 seconds. 🧗‍♂️ Challenges Overcome Structured LLM Outputs: Getting an LLM to consistently return prices in a parseable numeric format is notoriously tricky. We solved this with rigorous prompt engineering and robust fallback handling. Thread-Safe UI: Tkinter isn’t thread-safe. We engineered a solution to route all UI updates through root.after() callbacks from the active analysis thread. UX/UI Friction: Tuning the transparency and colors so the text remains readable across both dark and light chart themes, while ensuring our global hotkeys didn't conflict with native trading platforms. 🚀 What We Learned & What's Next This project proved just how incredibly capable Gemini 2.5 Flash is at visual reasoning. It accurately identified complex candlestick patterns, moving averages, and volume spikes from a raw image alone. The Roadmap for NanoMech: Voice Output: Speaking the trade setup aloud for a 100% hands-free experience. Multi-Monitor Support: Allowing users to select which screen the AI tracks. Cloud Hosting: Running NanoMech as a scalable web service on Google Cloud Run. Trade Logging: Automatically tracking how the AI's setups perform over time. 💻 Built With Python | Google Gemini 2.5 Flash | Google GenAI SDK | Google Cloud | Tkinter | mss | pillow | Regex Ready to try it out? Check out the code and run it yourself: https://github.com/omshukla24/NanoMech

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101

Cover image for 🐉 Dragon in the Drawer.
A

🐉 Dragon in the Drawer. A child drew a dragon. 💬 And said: “the dragon is mad because the people woke him up… so now he’s burning all the buildings and they’re running.” 🎬 I turned that into a film. ✨ Just a drawing, a sentence, and a name — and it becomes a full story: Character → Story → Animation → Film — ❤️ This project is close to my heart. I built it for a girl named Angel. She was very ill when she was born. Our whole family prayed for her. She survived — so we called her Angel, because that’s what she felt like to us. I haven’t seen her in a while… but I wanted to create something she could feel. — 🌱 Because every child deserves to see their imagination come alive. Not just as drawings… but as stories they can watch, feel, and remember ✨ — Try👇 https://studio.morphic.com/en/workflows/019dca9f-eb8f-7392-b81d-bffe4a8a388f/dragon-in-the-drawer

14

10

593

Cover image for Syntra — AI Productivity Engine

Most

Syntra — AI Productivity Engine Most productivity apps expect you to organize your life. Syntra does it for you ⚡ You start with a messy brain dump 🧠 Syntra converts it into structured tasks, a 7-day plan, and real-time insights — instantly. The interface itself was generated using Paper MCP 🧩 → turning abstract system logic into a fully designed, interactive UI in real time. → bridging idea → structure → interface seamlessly. Try: 🔗 https://syntra-493723.uc.r.appspot.com/ (https://syntra-493723.uc.r.appspot.com/)🔗 https://github.com/omshukla24/Syntra Built with: ⚙️ Next.js + TypeScript 🧠 Google Gemini 2.5 Flash 💾 localStorage (no backend / no DB) 🎨 CSS Modules (no Tailwind) 🎬 Framer Motion 🧩 Paper MCP Runs entirely locally 🔐 No setup. No manual planning. Just chaos → structure → execution 🚀

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533

Cover image for Most designers don’t know why

Most designers don’t know why their work is bad. They just feel it. So I built AUTOPSY ⚡ Upload a design → It tells you what’s wrong Why it fails How to fix it Then shows the fix + the best version with a cinematic reveal 🎬 Same design. No guessing. Try it: https://app.flora.ai/techniques/autopsy #FLORATechnique

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5

314

Data & AI Engineer

Data & AI Engineer

Cover image for Problem:
Many organizations still process invoices

Problem: Many organizations still process invoices manually by reading PDF documents and entering key details (invoice number, vendor, amount, etc.) into systems. This process is slow, error-prone, and difficult to scale, and it also makes it harder to detect duplicate invoices or incorrect totals. Solution: This project builds an automated invoice processing pipeline that converts uploaded invoice PDFs into structured data. It uses OCR to extract text, LLMs to identify invoice fields, validation checks to ensure correctness, and Kafka-based event streaming to manage the processing pipeline. The extracted data is stored in PostgreSQL and visualized through a dashboard, enabling faster, scalable, and more reliable invoice processing.

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3

112

Cover image for A fully local RAG pipeline

A fully local RAG pipeline that transforms your PDFs into a queryable knowledge base using FAISS vector search and Ollama LLMs. No cloud, no API keys - just private, grounded document intelligence running entirely on your machine.

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Cover image for
Problem Statement
Urban traffic management systems

Problem Statement Urban traffic management systems lack real-time, integrated data combining traffic conditions with weather patterns. This results in poor routing decisions, delayed emergency responses, and inefficient traffic flow management. Solution Developed a comprehensive real-time ETL pipeline that integrates traffic APIs and weather data sources, processes millions of data points, and delivers actionable insights through interactive dashboards for traffic management and route optimization.

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26

Cover image for A fully Dockerized real-time IoT

A fully Dockerized real-time IoT ETL pipeline that simulates device telemetry, processes events through MQTT and Kafka, orchestrates workflows with Airflow, and delivers real-time alerts and insights to CRM systems with monitoring via Grafana and Loki.

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