Freelance AI Developers in Noida
Freelance AI Developers in Noida
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AKASH VASHISHTHA
pro
Delhi, India
Versatile Fullstack Engineer | Web & Mobile Expert
$50k+
Earned
5x
Hired
5.0
Rating
80
Followers
Top
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Versatile Fullstack Engineer | Web & Mobile Expert
2
Podly.ai - Podcast Transcription Platform
2
149
4
LLM Operator | Watch your AI browse Internet
4
92
2
Bento Station | Restaurant Delivery Toolkit and Applications
2
37
1
PriceRipper - Price Comparison Website
1
74
AI Developer
(4)
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Satya Prakash
pro
New Delhi, India
Mobile App Architect • React Native Expert • 50+ App Shipped
1x
Hired
5.0
Rating
10
Followers
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Mobile App Architect • React Native Expert • 50+ App Shipped
1
Dream Planner - AI-Powered Goal Planning Platform
1
27
1
Kumbh Saathi – AI Pilgrimage Planner
1
7
1
Trippr - AI Itinerary Planner
1
6
1
GymCare Management System Development
1
1
AI Developer
(3)
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Rishi Bajpai
Noida, India
Building MVPs for startup founders with clean UX in a week.
1x
Hired
5.0
Rating
56
Followers
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Building MVPs for startup founders with clean UX in a week.
1
IndiaPharmaHub - B2B Pharmaceutical Supplier Directory
1
0
1
MVP Builders
1
4
2
Reqwest - Designing an Efficient API Testing Platform
2
2
1
SpongebobLabs - AI Research Lab Website Development
1
3
AI Developer
(2)
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Trashu Vashisth
Delhi, India
Building Production-Grade AI Agents & RAG Systems
8
Followers
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Building Production-Grade AI Agents & RAG Systems
1
Developed a production-grade Retrieval-Augmented Generation (RAG) system specifically designed to automate the analysis of complex Environmental, Social, and Governance (ESG) reports. This tool bridges the gap between static LLMs and the dynamic, data-heavy requirements of legal and sustainability compliance. [1 (https://www.youtube.com/watch?v=wkYPcMtwlN8)] Key Features & Capabilities Intelligent Document Processing: Automatically handles large, unstructured PDF/Word ESG reports, extracting critical clauses and metrics in seconds. Fact-Grounded Q&A: Uses a RAG architecture to ensure all answers are strictly based on the uploaded documents, virtually eliminating AI hallucinations. Compliance Mapping: Cross-references internal company data with global frameworks like CSRD, GRI, and TCFD to identify gaps or inconsistencies. Audit-Ready Traceability: Every insight generated includes direct citations and excerpts from the source files, providing a clear "paper trail" for legal teams. Automated Drafting: Capability to draft legal summaries, notices, or internal policy updates based on analyzed ESG risks Note: The 'Slaughter and May' branding in the sidebar is for UI/UX demonstration purposes only, showcasing how the tool integrates into a top-tier law firm's environment. #AI #RAG #LegalTech #ESG #Python #LangChain
1
41
1
Developed a full-stack RAG-based E- Commerce AI chatbot using React.js and Tailwind CSS that suggests the perfect laptop from a live catalog. Integrated ChromaDB with BGE Embedding models to provide highly accurate, context-aware product recommendations and instant technical support." Key Highlights: Smart Laptop Recommendations: Uses Semantic Search to match user needs (gaming, coding, etc.) with real-time specs. Advanced Tech Stack: Powered by LangChain for orchestration and BGE models for superior data retrieval. Modern UI/UX: Built a responsive, clean interface using React.js and Tailwind CSS. Zero Hallucination: Ensures all suggestions are strictly grounded in the available product inventory.
2
1
149
3
Built an intelligent RAG-based chatbot designed to simplify complex financial analysis. In the project demo, the AI deep-dives into Apple’s annual reports, extracting key fiscal metrics and providing real-time insights through natural language queries. It transforms dense financial filings into actionable data using advanced document retrieval
2
3
257
4
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
224
AI Developer
(3)
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Jagwinder Singh
pro
Delhi, India
Full Stack Developer
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Full Stack Developer
0
AI Translation & Communication App
0
0
0
AI Tattoo Generator App
0
0
0
Beauty Editor Selfie Camera Development
0
0
0
Blur Photo Editor App Development
0
0
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(9)
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Shivansh Yadav
Delhi, India
SaaS MVP Expert | 3 MVPs Shipped | Full-Stack Developer
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SaaS MVP Expert | 3 MVPs Shipped | Full-Stack Developer
1
EmailNoob.com AI-Powered Cold Email Personalization
1
9
1
🦜LangSynth: AI-Powered Synthetic Data Generation
1
7
1
IronDressAI: AI-Powered Wrinkle Removal Application
1
237
1
🎨Adistry.art: AI-Powered Ad Creative Generation
1
5
AI Developer
(3)
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Aniket Panchal
Delhi, India
AI & ML Solutions for Real-World Impact 🌐
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AI & ML Solutions for Real-World Impact 🌐
0
🤖 MediBot AI – AI-Powered Medical Chatbot
0
5
0
Dish Decode- Flask Based API for Recipe Extraction from video
0
0
0
Comment Feel - YouTube Comments Sentiment Analyzer Tool
0
21
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Cyril Johnson
Delhi, India
Machine Learning Engineer, Artificial Intelligence Engineer
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Machine Learning Engineer, Artificial Intelligence Engineer
0
Cyril-7/Image-to-Text
0
1
0
Indoor Navigation System Using Augmented Reality (AR)
0
1
0
WhatsApp Bot with Meta Cloud API and Flask
0
2
0
Cyril-7/AI-Generated-Imagery
0
2
AI Developer
(4)
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