You will get a GenAI proof-of-concept with LLM integration in 3-5 days
Project details
I build rapid GenAI proof-of-concepts that demonstrate real business value using LLMs — fast. With 6+ years in AI/GenAI and hands-on experience with OpenAI, Azure OpenAI, Anthropic, LangChain, and LlamaIndex, I've shipped PoCs across chatbots, RAG pipelines, document intelligence, and agentic workflows.
What you get: a working prototype with LLM integration, clean source code, a demo, and a handoff guide — all within 3–5 days. No bloated scoping cycles. Just fast, focused delivery.
I've built GenAI systems for healthcare, fintech, HR, and enterprise clients. Whether you need a quick demo for stakeholders or a validated foundation for production, I'll get it done efficiently and professionally.
Starter: basic LLM PoC with prompt engineering and demo.
Standard: full PoC with API layer, UI, and deployment guide.
Advanced: end-to-end PoC with testing, docs, and production handoff.
What you get: a working prototype with LLM integration, clean source code, a demo, and a handoff guide — all within 3–5 days. No bloated scoping cycles. Just fast, focused delivery.
I've built GenAI systems for healthcare, fintech, HR, and enterprise clients. Whether you need a quick demo for stakeholders or a validated foundation for production, I'll get it done efficiently and professionally.
Starter: basic LLM PoC with prompt engineering and demo.
Standard: full PoC with API layer, UI, and deployment guide.
Advanced: end-to-end PoC with testing, docs, and production handoff.
AI Algorithms
Large Language Model, Multimodal Large Language Model, Transformer ModelAI Applications
AI Chatbot, AI-Generated Code, Conversational AI, Natural Language Generation, Natural Language UnderstandingAI Tools
Azure OpenAI, Hugging FaceAI Models
GPT-4, LLaMAWhat's included
| Service Tiers |
Starter
$400
|
Standard
$900
|
Advanced
$2,000
|
|---|---|---|---|
| Delivery Time | 5 days | 10 days | 15 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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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
Senior GenAI Engineer | LangChain | LangGraph | RAG | Agentic AI
Chandigarh, India - 11:04 am local time
6 years building production-grade AI for Fortune 500 clients including Nike, Ernst & Young, and 7-Eleven. I architect and deploy complete AI systems — from first conversation to enterprise-scale production.
🔧 WHAT I BUILD
✔ Multi-agent systems (LangChain, LangGraph, AutoGen, LlamaIndex) — autonomous workflows that reason, plan, and act
✔ RAG pipelines with Pinecone, Weaviate, ChromaDB — grounded, accurate AI over your private data
✔ LLM integration and fine-tuning — GPT-4o, Claude, Gemini adapted to your domain
✔ Cloud-native deployments on Azure AKS and AWS Bedrock — Docker, Kubernetes, FastAPI, CI/CD
✔ NLP solutions — document processing, SQL generation from natural language, automated data extraction
🚀 PROJECT RESULTS
◆ ThreatSense AI (Nike) — Real-time cybersecurity multi-agent platform on AWS Bedrock. 40% faster incident response.
◆ Vision Flow (EY) — AI image-to-data pipeline on Azure AKS. 95%+ accuracy on complex document types.
◆ AI Ledger Analyzer (7-Eleven) — Natural language to SQL via Azure OpenAI. Eliminated manual financial query writing.
◆ QueryLens (Casey's) — Plain English to BigQuery on GCP. Enabled non-technical teams to query live data independently.
⚙️ TECH STACK
LangChain · LangGraph · LlamaIndex · AutoGen · Python · FastAPI · Azure OpenAI · AWS Bedrock · GPT-4o · Claude · Gemini · Pinecone · Weaviate · CosmosDB · PostgreSQL · Docker · Kubernetes · Databricks · Apache Spark · Kafka · MLflow
🌟 WHY CHOOSE ME
✔ Enterprise delivery — production systems used by global brands, not just demos
✔ Full-stack AI ownership — architecture, development, deployment, and monitoring
✔ Clear communication — you always know what's being built, why, and when
📩 Building an AI agent, RAG system, or LLM-powered application? Send me your project details. I respond within 4 hours.
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.
Discovery & PoC Architecture Design
Understand requirements, select LLM stack, design PoC architecture, and align on deliverables before development starts.