You will get LlamaIndex RAG Expert: Ingestion Pipeline & Retrieval Quality Audit
Top Rated
Project details
Is your RAG system hallucinating, missing obvious answers, or retrieving irrelevant documents?
I Will Audit These 4 Critical Layers:
Data Ingestion & Parsing:
Are you parsing PDFs/HTML correctly, or feeding "garbage" characters to the LLM?
Review of SimpleDirectoryReader or custom loaders to ensure clean text extraction.
Chunking Strategy:
Is your chunk_size too small (missing context) or too big (confusing the LLM)?
Evaluation of your node parsers (SentenceSplitter, SemanticChunking, Hierarchical).
Check for proper chunk_overlap to prevent data loss at boundaries.
Embedding & Vector Search:
Are you using the right embedding model for your specific domain?
Audit of vector store health (Pinecone, Weaviate, Qdrant, Milvus).
Check for "Lost in the Middle" phenomenon issues.
Retrieval Optimization:
Analysis of Top-K precision.
Review of Hybrid Search (Keyword + Vector) implementation.
My Tech Stack:
Frameworks: LlamaIndex, LangChain, Haystack
Vector DBs: Pinecone, Weaviate, ChromaDB, Qdrant, Supabase (pgvector).
LLMs: GPT-4, Claude 3.5, Mistral, Llama 3.
Stop guessing why your chatbot is failing. Order an audit today and let's get your data grounded.
I Will Audit These 4 Critical Layers:
Data Ingestion & Parsing:
Are you parsing PDFs/HTML correctly, or feeding "garbage" characters to the LLM?
Review of SimpleDirectoryReader or custom loaders to ensure clean text extraction.
Chunking Strategy:
Is your chunk_size too small (missing context) or too big (confusing the LLM)?
Evaluation of your node parsers (SentenceSplitter, SemanticChunking, Hierarchical).
Check for proper chunk_overlap to prevent data loss at boundaries.
Embedding & Vector Search:
Are you using the right embedding model for your specific domain?
Audit of vector store health (Pinecone, Weaviate, Qdrant, Milvus).
Check for "Lost in the Middle" phenomenon issues.
Retrieval Optimization:
Analysis of Top-K precision.
Review of Hybrid Search (Keyword + Vector) implementation.
My Tech Stack:
Frameworks: LlamaIndex, LangChain, Haystack
Vector DBs: Pinecone, Weaviate, ChromaDB, Qdrant, Supabase (pgvector).
LLMs: GPT-4, Claude 3.5, Mistral, Llama 3.
Stop guessing why your chatbot is failing. Order an audit today and let's get your data grounded.
AI Algorithms
Large Language Model, Multimodal Large Language Model, Regression Analysis, Transformer Model, YOLOAI Applications
AI Chatbot, AI-Enhanced Classification, Natural Language Generation, Text RecognitionAI Development Language
PythonAI Tools
Hugging Face, PyTorch, TensorFlowAI Models
ChatGPT, LLaMA, OpenAI Codex, WhisperWhat's included
| Service Tiers |
Starter
$100
|
Standard
$250
|
Advanced
$600
|
|---|---|---|---|
| Delivery Time | 2 days | 4 days | 7 days |
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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Daniel Lim H.
Aug 4, 2026
Re-architect & Build a Lean LLM Conversation Worker
Thank you for your professional and outstanding help...at the time i needed an Expert for Ai Chatbots. Thank you soo much.
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Roman A.
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WANTED: React programmer for IAP setup in my app (wrapped with buildnatively and revenuecat)
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Curtis S.
Mar 8, 2026
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Shaban jumped in and got tasks done, good attitude and willing to do th work. Thanks!
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Muhammad Bilal J.
Jan 25, 2026
VPS Server Deployment and Git Branch Management for Development, Staging and Production
Brilliant guy. Worked and provided exactly what I wanted.
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Rod A.
Sep 7, 2025
Full-Stack Developer - AI Website
Absolutely outstanding experience! Shaban delivered beyond expectations on a highly technical full stack AI project that required expert skills in web scraping, LangChain integration, and Retrieval-Augmented Generation workflows. Their proficiency with Python, JavaScript (React/Next.js), APIs, and vector databases (like Pinecone and FAISS) was truly impressive and critical to the project’s success. Communication was clear, deadlines were consistently met, and every challenge was tackled with a professional, solutions-oriented attitude. If you’re seeking a reliable developer for complex, cutting-edge AI projects, I can’t recommend Shaban highly enough. Would hire again without hesitation—one of the best freelancers I’ve worked with!
About Shaban
Ai & python expert | deepseek harness consultant
100%
Job Success
Faisalabad, Pakistan - 8:56 am local time
Availabilty : 𝗘𝗦𝗧 𝗛𝗼𝘂𝗿𝘀
I solve complex business problems by shipping production-ready AI at Cursor-driven speed.
🛠️ What I Build & Fix
MCP Server Development & AI Integration: I connect internal APIs and databases directly to LLMs. Utilizing Google AI Studio, Vertex AI Agent, and Genkit, I build secure Model Context Protocol (MCP) servers and orchestrate intelligent workflows that execute real tasks flawlessly.
CRM & Sales Automation: Deep integrations with GoHighLevel (GHL), Zoho, Salesforce, and HubSpot. I design Claude Cowork systems that operate as autonomous sales and support assistants alongside Twilio telephony.
AI Video Generation & UGC: Building automated media workflows for marketing and UGC ads using HeyGen, ComfyUI, LTX, and Seed Dance to generate high-converting video content at scale.
Intelligent Web Scraping & Data Pipelines: I fix broken scraping scripts and build autonomous, anti-bot data extraction pipelines at scale using Crawl4AI, Playwright, and Selenium to feed clean data directly into your AI models.
Voice AI & Conversational Agents: Production-grade voice automation handling thousands of concurrent calls. Expert in OpenAI Whisper (Voice-to-Text), ElevenLabs (Text-to-Voice), VAPI.ai, and Retell.ai for seamless, multi-step voice reasoning.
Workflow Automation & Pipeline Refactoring: I step in to rescue failing AI apps and eliminate 80%+ of repetitive operations. I design end-to-end automations using n8n, Make, and custom Python/FastAPI backends.
Steps for completing your project
After purchasing the project, send requirements so Shaban can start the project.
Delivery time starts when Shaban receives requirements from you.
Shaban works on your project following the steps below.
Revisions may occur after the delivery date.
Access: You grant read access to your repo and Vector DB