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You will get a production-ready multi-agent AI system with LangGraph or AutoGen
Project details
I build production-ready multi-agent AI systems using LangGraph and AutoGen — frameworks purpose-built for orchestrating autonomous AI workflows.
With 6+ years in AI/ML and deep expertise in LLM-based agent architectures, I design systems where multiple specialized agents collaborate: one researches, another reasons, a third executes — all coordinated through a graph-based state machine.
Every delivery includes:
• Agent workflow design & implementation (LangGraph / AutoGen)
• Tool integration (APIs, databases, web search, custom functions)
• Memory management (short-term context + long-term vector store)
• Error handling, retry logic & observability
• FastAPI deployment-ready codebase with documentation
I've built agentic solutions for RAG pipelines, document Q&A, automated research assistants, customer service bots, and data analysis agents — deployed on Azure, AWS, and GCP.
You'll receive clean, modular Python code that your team can extend and maintain.
With 6+ years in AI/ML and deep expertise in LLM-based agent architectures, I design systems where multiple specialized agents collaborate: one researches, another reasons, a third executes — all coordinated through a graph-based state machine.
Every delivery includes:
• Agent workflow design & implementation (LangGraph / AutoGen)
• Tool integration (APIs, databases, web search, custom functions)
• Memory management (short-term context + long-term vector store)
• Error handling, retry logic & observability
• FastAPI deployment-ready codebase with documentation
I've built agentic solutions for RAG pipelines, document Q&A, automated research assistants, customer service bots, and data analysis agents — deployed on Azure, AWS, and GCP.
You'll receive clean, modular Python code that your team can extend and maintain.
AI Algorithms
Large Language Model, Transformer ModelAI Applications
AI Chatbot, Conversational AI, Natural Language GenerationAI Tools
Azure OpenAIAI Models
ChatGPT, LLaMAWhat's included
| Service Tiers |
Starter
$600
|
Standard
$1,400
|
Advanced
$2,500
|
|---|---|---|---|
| Delivery Time | 7 days | 14 days | 21 days |
Number of Revisions | 1 | 2 | 3 |
AI Model Integration | - | - | - |
Batch Normalization | - | - | - |
Database Integration | - | - | - |
Detailed Code Comments | - | - | - |
Image Upscaling | - | - | - |
MLOps | - | - | - |
Model Deployment | - | - | - |
Model Documentation | - | - | - |
Model Monitoring | - | - | - |
Model Testing & Optimization | - | - | - |
Model Tuning | - | - | - |
Natural Language Processing | - | - | - |
NLP Tokenization | - | - | - |
Pre-Training | - | - | - |
Prompt Engineering | - | - | - |
Setup File | - | - | - |
Source Code | - | - | - |
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KV
KS V.
Aug 18, 2026
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KS V.
Aug 18, 2026
AI Non-Verbal Image Reconstruction – .NET Wrapper
Sunny is exceptionally good at what he does. Even after a project is completed, he remains highly responsive to feedback and is always willing to help resolve any issues or integration hiccups that may arise. His support doesn’t end with project delivery, which is truly commendable.
KV
KS V.
Aug 13, 2026
Non-Verbal Image Reconstruction PoC
What a professional! Sunny did a really good job throughout the project. He understood the requirement well and delivered impressive reconstruction quality. I was particularly happy with the live demonstration, where the results were very close to the original images. He was also responsive and clear in his communication throughout the project. Overall, a very smooth and positive experience working with him.
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Power BI Report Creation for 1 Million Rows Dataset
Professional
Instantaneous
Always available
Quick work feedback and Logical. This is why I would recommend him. I work a organization as well I understand what a professional should work like. Kudos!
Instantaneous
Always available
Quick work feedback and Logical. This is why I would recommend him. I work a organization as well I understand what a professional should work like. Kudos!
About Sunny
AI Agent Engineer | MCP, RAG, LangGraph, Copilot Studio & Azure
100%
Job Success
Chandigarh, India - 6:11 pm local time
I have 6 years of experience delivering production-grade AI and data systems in Fortune 500 retail, consulting, financial-data, and cybersecurity environments.
SELECTED RESULTS
• Built a real-time multi-agent cybersecurity platform that improved incident-response speed by 40%.
• Delivered an image-to-data pipeline with 95%+ accuracy across complex document types.
• Built natural-language-to-SQL assistants that eliminated manual query writing and enabled non-technical teams to access live business data.
• Developed enterprise document and workflow automation using private data, APIs, cloud services, and human approval controls.
WHAT I BUILD
• Enterprise AI agents and multi-agent workflows using LangGraph, LangChain, AutoGen, and LlamaIndex
• Production RAG systems over documents, databases, and business knowledge
• Document intelligence, extraction, classification, and structured-output pipelines
• Natural-language SQL and analytics assistants
• MCP, API, ERP, and business-workflow integrations
• Cloud deployment and production hardening on Azure and AWS
DELIVERY
I can own the complete lifecycle: requirements discovery, architecture, prototype, retrieval and data layer, API backend, evaluation, deployment, monitoring, and support.
CORE STACK
Python, FastAPI, LangGraph, LangChain, LlamaIndex, AutoGen, Azure OpenAI, AWS Bedrock, OpenAI, Claude, Gemini, Pinecone, Weaviate, PostgreSQL, Docker, Kubernetes, Databricks, and Kafka.
WHY CLIENTS HIRE ME
• Production systems, not isolated prompt demos
• Full-stack AI ownership from architecture through deployment
• Clear communication, documented decisions, and realistic estimates
• Enterprise integration experience with private data and controlled workflows
Building an AI agent, RAG system, document-intelligence workflow, or enterprise LLM application? Send me the problem, current systems, and desired outcome. I will propose the smallest reliable path to production.
Steps for completing your project
After purchasing the project, send requirements so Sunny can start the project.
Delivery time starts when Sunny receives requirements from you.
Sunny works on your project following the steps below.
Revisions may occur after the delivery date.
Agent Design & Development
Design agent roles, tools, and graph topology. Build the multi-agent system with LangGraph or AutoGen, integrate APIs and data sources, and deliver tested, documented Python code.