Freelancers using LangChainFreelancers using LangChain
ProjectsPeople
Anmol Baranwal's avatar
Anmol Baranwal
India
Technical Writer (1.5M+ reads) & Open Source Developer
$10k+
Earned
23x
Hired
53
Followers
BUILDSHIP_EXPERT

expert

HIRED_BY_YC_EXPERT

Hired

Technical Writer (1.5M+ reads) & Open Source Developer
Cover image for Technical Writing for Copilotkit | 40k+ views
Technical Writing for Copilotkit | 40k+ views
1
79
Cover image for Technical Writing for Encore | 30k+ views
Technical Writing for Encore | 30k+ views
1
15
Cover image for Technical Writing for Encore | 30k+ views
Technical Writing for Encore | 30k+ views
0
6
Cover image for Technical Writing for Opire | 60k+ Views
Technical Writing for Opire | 60k+ Views
0
19
LangChain(1)
Yossuf Yahia's avatar
Yossuf Yahia
Egypt
Ai Agent Developer | Fullstack Developer
$5k+
Earned
2x
Hired
5.0
Rating
11
Followers
Ai Agent Developer | Fullstack Developer
Cover image for AI-Powered Operations & Audit Management Platform Development
AI-Powered Operations & Audit Management Platform Development
0
3
Cover image for AI Hearing Platform for Smarter Hiring
AI Hearing Platform for Smarter Hiring
1
18
Cover image for AML Compliance Ai Assistant
AML Compliance Ai Assistant
1
8
Cover image for Audio e-commerce
Audio e-commerce
0
7
LangChain(3)
Garreth Dottin's avatar
Garreth Dottin
proMiami, USA
AI and eCommerce expert with experience working at Amazon.
$5k+
Earned
1x
Hired
2
Followers
AI and eCommerce expert with experience working at Amazon.
Cover image for AI Automation for Elite Design Brand
AI Automation for Elite Design Brand
1
1
Cover image for AI powered recommendations
AI powered recommendations
0
3
Cover image for Dermalogica
Dermalogica
0
1
Cover image for AI Chatbots Upselling For You
AI Chatbots Upselling For You
0
0
LangChain(1)
Trashu Vashisth's avatar
Trashu Vashisth
Delhi, India
Building Production-Grade AI Agents & RAG Systems
14
Followers
Building Production-Grade AI Agents & RAG Systems
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.
0
36
Cover image for Developed a full-stack RAG-based E- Commerce
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
231
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 Built an intelligent RAG-based chatbot
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
297
LangChain(5)