You will get Self-Healing RAG Systems with Advanced Hallucination Control
Project details
I build advanced AI Agent and RAG (Retrieval-Augmented Generation) systems focused on accuracy, automation, and scalability. My solutions go beyond basic chatbots by implementing self-healing workflows, hallucination control, intelligent retrieval pipelines, and MCP-based integrations.
This project is ideal for AI assistants, knowledge base chatbots, document search systems, autonomous AI agents, and workflow automation using OpenAI, Claude, Gemini, or open-source LLMs.
What sets my work apart is the focus on production-ready architecture and reliable AI responses. I implement advanced retrieval, reranking, context validation, memory systems, and automated correction workflows to reduce hallucinations and improve response quality.
Services include:
• AI Agents & Multi-Agent Systems
• Self-Healing RAG Pipelines
• Hallucination Detection & Control
• MCP & Tool Integrations
• Vector Database Setup
• API & Cloud Deployment
• Custom AI Automation Workflows
I focus on scalable architecture, clean implementation, and delivering AI systems that solve real business problems.
This project is ideal for AI assistants, knowledge base chatbots, document search systems, autonomous AI agents, and workflow automation using OpenAI, Claude, Gemini, or open-source LLMs.
What sets my work apart is the focus on production-ready architecture and reliable AI responses. I implement advanced retrieval, reranking, context validation, memory systems, and automated correction workflows to reduce hallucinations and improve response quality.
Services include:
• AI Agents & Multi-Agent Systems
• Self-Healing RAG Pipelines
• Hallucination Detection & Control
• MCP & Tool Integrations
• Vector Database Setup
• API & Cloud Deployment
• Custom AI Automation Workflows
I focus on scalable architecture, clean implementation, and delivering AI systems that solve real business problems.
AI Algorithms
Autoencoder, Feedforward Neural Network, Large Language Model, Multimodal Large Language Model, Regression AnalysisAI Applications
AI Chatbot, Anomaly Detection, Machine TranslationAI Development Language
PythonAI Tools
Hugging Face, PyTorch, TensorFlowAI Models
BERT, ChatGPT, LLaMAWhat's included
| Service Tiers |
Starter
$99
|
Standard
$299
|
Advanced
$799
|
|---|---|---|---|
| Delivery Time | 3 days | 7 days | 14 days |
Number of Revisions | 3 | 3 | 0 |
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 |
About Yashas
Software developer | AI Agents | RAG | Vector Embedding | MCP
Mysuru, India - 5:07 am local time
What I Work On
AI Agents using OpenAI, Claude, Gemini, and open-source LLMs
RAG pipelines with vector databases and semantic search
MCP (Model Context Protocol) integrations and tool orchestration
Multi-agent systems and autonomous workflows
LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel
Custom chatbots and AI assistants
API integrations and AI automation
Knowledge base AI systems
Workflow automation using Python and cloud services
Tech Stack
Python, FastAPI, Node.js
OpenAI API, Anthropic Claude, Gemini
LangChain, LlamaIndex, LangGraph
Pinecone, Weaviate, ChromaDB, FAISS
Docker, AWS, GCP
MCP servers and tool integrations
PostgreSQL, Redis
What You Can Expect
Clean, scalable architecture
Production-ready AI systems
Fast communication and reliable delivery
Strong focus on performance and usability
End-to-end support from idea to deployment
Steps for completing your project
After purchasing the project, send requirements so Yashas can start the project.
Delivery time starts when Yashas receives requirements from you.
Yashas works on your project following the steps below.
Revisions may occur after the delivery date.
Requirement Analysis & AI Architecture Planning
Understand business goals, analyze data sources, define AI workflow, and design the best RAG/AI agent architecture for the project.
Knowledge Base & Vector DB Setup
Prepare documents/data, create embeddings, and configure vector databases for efficient semantic retrieval.