AI Agent Development Projects in Greater Noida
AI Agent Development Projects in Greater Noida
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Aparna Soneja
AI Agent that transforms Trello sprint data into a report
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Sahil Roy
pro
AETHER: AI-Generated Luxury Brand Identity Project
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Jagwinder Singh
AI Agent Tutor Mobile App An AI personal tutor mobile application designed for learners of all ages, from students to professionals. The app provides personalized guidance, explanations, skill development, and interactive learning across multiple subjects and topics. Key Features: > AI tutor conversations for learning any topic > Personalized learning paths based on user goals and skill level > Support for academics, professional skills, coding, languages, and general knowledge > AI explanations, summaries, and concept breakdowns > Practice exercises, quizzes, and knowledge improvement tools > Voice and text-based learning interactions > Learning history and progress tracking > Adaptive AI responses based on user behavior Key Contributions: -- Developed a cross-platform mobile learning experience -- Integrated AI/LLM technology for real-time tutoring interactions -- Implemented secure authentication and data management -- Optimized performance and user experience across devices Outcome: Created an AI learning companion that enables users of all ages to learn, improve skills, and access personalized education anytime through a mobile-first experience.
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Ayush Shukla
You finish building something for a client: Now you have to explain it to someone who doesn't know what a webhook is. I built Runbook AI Agent — a Notion agent that turns your raw dev notes into a complete client handoff doc in seconds. It generates: → Plain-English breakdown of what the system does → Step-by-step daily operations guide → Troubleshooting table for every failure mode → Maintenance schedule with task owners → Quick Reference Card your client can bookmark Try it → https://www.notion.so/marketplace/custom-agents/runbook-builder-client-control-center (https://www.notion.so/marketplace/custom-agents/runbook-builder-client-control-center)Any client. Any system. Any industry. Your handoff done in seconds🚀
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Ajay Bidyarthy- AI Full Stack Developer
I offer AI, data science, analytics, software development, cloud computing, cybersecurity, and digital transformation services for startups and enterprises. My expertise includes machine learning, generative AI, big data analytics, business intelligence, web and mobile app development, IoT solutions, and enterprise automation. I also provide consulting, staffing, and industry-specific solutions for healthcare, finance, retail, insurance, energy, and supply chain businesses.
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Rahul Rawal
Natural Language Workflow Editing Title: "Editing AI Workflows Using Chat" Description: "Demo of RAPR AI's chat-based workflow editor — modifying a live workflow and adding nodes through natural language. No manual config, just conversation.
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Md Aabid Hussain
Aiva Backend Development for AI Virtual Assistant
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Chirag Sharma
AI Real Estate Concierge: Closing the Speed-to-Lead Gap
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Sparsh Rajput
Built an autonomous AI sales prospecting system that researches companies, identifies decision-makers, extracts lead information from the web, and generates personalized cold outreach emails using AI. The platform automates hours of manual prospecting work into a single workflow.
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Gaurry Sharma
Smart Agent Chat - AI
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shivankar patra
Relationship Advisor: AI-Powered Guidance
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Jai Tiwari
GitHub - JAI0705/Fake-news-classification
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Aparna Soneja
AI agent for project planning, estimation & resourcing
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Jagwinder Singh
AI Resume Screening | Candidate Ranking System | AI HR Recruiter | ATS CV/Resume Optimization 𝗢𝘃𝗲𝗿𝘃𝗶𝗲𝘄 Recruiters often spend hours manually reviewing resumes, comparing candidate qualifications, and identifying the best fit for open positions. To address this challenge, I developed an AI-powered Resume Screening and Candidate Ranking Platform that automates candidate evaluation, improves hiring efficiency, and reduces recruitment time. 𝗖𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲 Traditional recruitment processes involve reviewing hundreds of resumes for a single position. This manual approach is time-consuming, inconsistent, and often results in qualified candidates being overlooked. Recruiters needed a solution capable of quickly analyzing resumes, matching them against job requirements, and generating reliable candidate rankings. 𝗦𝗼𝗹𝘂𝘁𝗶𝗼𝗻 I built an intelligent recruitment platform that leverages Artificial Intelligence and Natural Language Processing (NLP) to automate resume analysis and candidate assessment. 𝗞𝗲𝘆 𝗳𝗲𝗮𝘁𝘂𝗿𝗲𝘀 𝗶𝗻𝗰𝗹𝘂𝗱𝗲: - ATS-compatible resume parsing for PDF and DOCX files - Automated extraction of skills, experience, education, certifications, and contact information - AI candidate matching based on job descriptions - Intelligent candidate scoring and ranking system - Semantic skill matching using NLP techniques - Automated shortlist generation for recruiters - Recruiter dashboard for managing applications and rankings - Bulk resume processing for high-volume recruitment - Interview recommendation system based on candidate fit - Fair and consistent evaluation framework to reduce manual bias 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁 𝗣𝗿𝗼𝗰𝗲𝘀𝘀 The platform was designed with scalability and accuracy in mind. The workflow begins by parsing uploaded resumes and extracting structured candidate data. AI models then compare candidate profiles against job requirements, analyzing technical skills, years of experience, educational background, and industry relevance. A ranking engine generates compatibility scores and presents candidates in order of suitability. Recruiters can review detailed scoring insights, compare applicants, and make faster hiring decisions. 𝗥𝗲𝘀𝘂𝗹𝘁𝘀 The solution significantly improved recruitment efficiency and candidate discovery. 𝗢𝘂𝘁𝗰𝗼𝗺𝗲𝘀 > Reduced manual resume screening time by up to 80% > Accelerated candidate shortlisting process > Improved recruiter productivity and hiring speed > Increased consistency in candidate evaluation > Enabled processing of hundreds of resumes within minutes > Enhanced talent identification through AI-driven matching 𝗖𝗼𝗻𝗰𝗹𝘂𝘀𝗶𝗼𝗻 This AI recruitment platform transforms traditional hiring workflows by automating resume screening, ranking candidates intelligently, and helping recruiters identify top talent faster, more accurately, and at scale.
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Ajay Bidyarthy- AI Full Stack Developer
Ajay Bidyarthy is the Founder and Chief Executive Officer of Blackcoffer and an AI Engineer with expertise in developing intelligent, scalable solutions using Machine Learning, Generative AI, and advanced chatbot systems. He designs and builds AI-powered applications—ranging from conversational agents to data-driven automation—by leveraging modern frameworks and cutting-edge technologies.
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Jagwinder Singh
✈️ AI Aviation Platform Developed an AI aviation mobile platform that unifies real-time flight tracking, predictive analytics, and flight booking into a single ecosystem. The goal was to streamline air travel management by improving accuracy, speed, and decision-making across the entire journey. Problem Statement Users today rely on multiple disconnected tools: one app for flight tracking, another for booking, and separate sources for delays, weather, and gate updates. This fragmentation leads to delayed or inconsistent flight information, inefficient planning, and a lack of intelligent guidance when booking flights. Solution Built a unified aviation platform that consolidates live flight tracking, AI-based predictions, and flight search/booking into one intelligent system. The platform serves as a real-time travel assistant, offering end-to-end visibility from booking to arrival. Core Features - Real-time global flight tracking with interactive map - AI delay prediction using weather, route, and historical data - Flight search with price comparison and smart recommendations - Live alerts for delays, gate changes, cancellations, and price drops - Airport insights including congestion levels and reliability scores - Personalized dashboard with trip history and upcoming travel timeline Challenges Handled high-frequency real-time flight data efficiently, ensured consistency across multiple aviation providers, improved prediction accuracy despite incomplete datasets, and managed complex airline API integrations with varying reliability. Key Learnings Real-time systems require strong caching and streaming strategies. Combining weather, historical, and live data significantly improves prediction quality. UX clarity is essential when presenting dense aviation information. External API reliability directly impacts system stability.
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