Freelancers using LangChain in DelhiFreelancers using LangChain in Delhi
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Trashu Vashisth's avatar
Trashu Vashisth
Delhi, India
Building Production-Grade AI Agents & RAG Systems
13
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.
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63
Cover image for Developed a production-grade Retrieval-Augmented Generation
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
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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.
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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.
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295
LangChain(5)
Wahid Ali's avatar
Wahid Ali
proGhaziabad, India
Full Stack Developer | MVPs, SaaS & Dashboards for Startups
$10k+
Earned
4x
Hired
4.9
Rating
22
Followers
Full Stack Developer | MVPs, SaaS & Dashboards for Startups
Cover image for AI Search Optimization Platform
AI Search Optimization Platform
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17
Cover image for Flight Booking Platform
Flight Booking Platform
1
16
Cover image for Innovation Intelligence Platform
Innovation Intelligence Platform
1
18
Cover image for Digital Business Card Platform
Digital Business Card Platform
1
13
LangChain(1)
Khushi Mehta's avatar
Khushi Mehta
Delhi, India
Data Scientist & AI Content Specialist | Dashboards • ML App
Data Scientist & AI Content Specialist | Dashboards • ML App
Cover image for BizBot: AI-Powered Business Data Chatbot Development
BizBot: AI-Powered Business Data Chatbot Development
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3
Cover image for Cyber Crime Analysis using Machine Learning
Cyber Crime Analysis using Machine Learning
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1
Cover image for Customer and Sales Insights Dashboard
Customer and Sales Insights Dashboard
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1
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LangChain(1)
Aparna Soneja's avatar
Aparna Soneja
Delhi, India
Full Stack AI & Machine Learning Engineer
$1k+
Earned
1x
Hired
44
Followers
BOLT_EXPERT

Expert

BOLT_MENTOR_EXPERT

Mentor

Full Stack AI & Machine Learning Engineer
Cover image for AI Agent that transforms Trello sprint data into a report
AI Agent that transforms Trello sprint data into a report
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5
Cover image for AI agent for project planning, estimation & resourcing
AI agent for project planning, estimation & resourcing
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11
Cover image for It's finally here 🎬✨ Introducing Sniplyx
It's finally here 🎬✨ Introducing Sniplyx AI — your full AI video editor, not just another clipper. Upload your raw footage and let AI do the heavy lifting: ✂️ Auto viral clips 🎞️ AI B-roll 🎵 AI music & SFX 📝 Auto transcription 🌐 100% browser-based, nothing to install Built this because manual video editing was something I had to do myself but never really knew how to do well, and it took forever. So I built a tool that does the heavy lifting for me. Now it's all in one place, starting at just $2 🙌 Try it out here: https://www.sniplyxai.com
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Cover image for Mentors program. Week 5-7
Mentors program. Week 5-7
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2
24
LangChain(2)
Ajay Bidyarthy- AI Full Stack Developer's avatar
Ajay Bidyarthy- AI Full Stack Developer
Delhi, India
Build production-ready AI applications with Machine Learning
12
Followers
Build production-ready AI applications with Machine Learning
Cover image for Ajay Bidyarthy is the Founder
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.
3
364
Cover image for A multi-tenant architecture is a
A multi-tenant architecture is a software architecture where a single application instance serves multiple customers (tenants) while keeping each tenant's data and configuration isolated. Example Imagine a SaaS CRM platform: - Company A uses the CRM. - Company B uses the same CRM. - Company C uses the same CRM. All three companies share the same application, but: -> Their users only see their own data. -> Their settings, branding, and permissions can be different. -> The platform provider maintains only one codebase.
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110
Cover image for AI Chatbot Application Development
AI Chatbot Application Development
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787
Cover image for I offer AI, data science,
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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113
LangChain(1)
ANIMESH SINGH's avatar
ANIMESH SINGH
Delhi, India
Data & AI Engineer
Data & AI Engineer
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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39
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
116
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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29
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.
1
59
LangChain(1)
Sankalp Shukla's avatar
Sankalp Shukla
Delhi, India
AI Engineer building custom RAG chatbots & automation
New to Contra
AI Engineer building custom RAG chatbots & automation
Cover image for Designed and developed scalable AI-powered
Designed and developed scalable AI-powered APIs that connected Globe Spring's applications, databases, and internal systems. The integration enabled intelligent search, personalized recommendations, chatbot functionality, and automated workflows through secure REST APIs and LangChain orchestration.
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Cover image for Personalized AI Chatbot for Globe
Personalized AI Chatbot for Globe Spring
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Cover image for Designed and developed a custom
Designed and developed a custom AI analytics dashboard for Globe Spring to provide real-time business insights and performance tracking. The platform aggregates sales, customer, and operational data into a single interactive dashboard with AI-powered recommendations and automated reporting. This solution helps decision-makers monitor KPIs, identify trends, and make faster data-driven decisions.
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Cover image for Developed an AI-powered workflow automation
Developed an AI-powered workflow automation system for Globe Spring using n8n, Zapier, and OpenAI to automate order processing, email notifications, and CRM updates.
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42
LangChain(2)