AI Engineering · LLMs & Vector Systems
Custom AI Application & Intelligent Chatbot Engineering
Custom AI application development, OpenAI/Claude API integrations, vector search systems, and conversational AI chatbots.
✦ Direct Answer & Architecture Scope:
Custom AI application development by Jyotirmay Ray delivers domain-specific LLM integrations, conversational AI chatbots, and intelligent enterprise assistants. Built with Python FastAPI, OpenAI/Claude APIs, and Pinecone vector databases to eliminate hallucinations and automate business operations.
Target Capabilities & Coverage:
Production Deliverables & Milestones
Domain-Anchored RAG (Retrieval-Augmented Generation) Architecture
Custom Conversational Chatbot Widget with Streaming Typewriter Responses
Secure API Gateway with Rate Limiting & Cost Optimization
Multi-Modal Document Parsing (PDF, CSV, Docx analysis)
Automated CRM & WhatsApp Lead Sync Integration
Technical Architecture & Verified Code Pattern
SYSTEM TOPOLOGY BLUEPRINT
User Query
├── Semantic Embedding Model (text-embedding-3)
├── Pinecone / Supabase pgvector Similarity Match
├── Grounded LLM Prompt Pipeline (Claude / GPT-4o)
└── Streaming Real-time SSE Response to Frontend
PRODUCTION CODE IMPLEMENTATION
# Python FastAPI Streaming RAG Endpoint
from fastapi import FastAPI
from fastapi.responses import StreamingResponse
from openai import AsyncOpenAI
app = FastAPI()
client = AsyncOpenAI()
async def stream_generator(query: str, context: str):
response = await client.chat.completions.create(
model="gpt-4o",
messages=[
{"role": "system", "content": f"Ground your answer in context: {context}"},
{"role": "user", "content": query}
],
stream=True
)
async for chunk in response:
if chunk.choices[0].delta.content:
yield chunk.choices[0].delta.contentArchitecture Comparison: Custom Engineering vs. Generic Agency
| Feature | Generic Agency / Page Builder | Jyotirmay's Custom Architecture |
|---|---|---|
| Accuracy | Generic ChatGPT wrapper prone to hallucinations | Strict vector RAG grounding with source verification |
| API Cost | Wastes tokens with unoptimized, oversized prompts | Semantic caching and token compression reducing costs by 60% |
Frequently Asked Questions & Technical Scope
How do you prevent the AI from making things up (hallucinating)?
We ground the AI using Retrieval-Augmented Generation (RAG) and semantic vector search, ensuring it only answers from your verified business documentation.
Ready to build your Custom AI Application & Intelligent Chatbot Engineering?
Direct technical consultation with founder-engineer Jyotirmay Ray. Zero middlemen, 100% intellectual property ownership, and rapid milestone delivery.