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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Rod A.
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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!
DA
Daniela A.
Aug 31, 2025
RAG Pipeline Engineer - Qdrant Database
Shaban did an excellent job building a RAG pipeline with Qdrant Database. He delivered a scalable, efficient solution and showed great expertise in embeddings, vector search, and retrieval optimization. Communication was smooth, deadlines were met, and the final result exceeded expectations. Highly recommended!
About Shaban
LLM & python expert | whatsapp chatbots | hermes agent | aws bedrock
100%
Job Success
Faisalabad, Pakistan - 3:33 am local time
🎁 A 100% refund if I set the wrong expectations
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.
💻 Core Technology Stack
→ AI & Frameworks: CrewAI, Genkit, Google Vertex AI, Google AI Studio, OpenAI, Anthropic, AWS Bedrock, Claude Cowork.
→ Voice AI & Telephony: ElevenLabs, OpenAI Whisper, VAPI.ai, Retell.ai, Twilio.
→ Video Gen & AI Media: HeyGen, ComfyUI, LTX, Seed Dance, UGC Ads automation.
→ CRMs: GoHighLevel (GHL), Zoho, Salesforce, HubSpot.
→ Web Scraping: Crawl4AI, Playwright, Selenium.
→ Vector Stores & Analytics: Pinecone, Qdrant, Chroma.
→ Backend & Queuing: Python (FastAPI), Node.js, BullMQ (for highly scalable background processing), Cassandra, Kafka, Redis.
→ Security & Compliance: OWASP, GDPR, SSL/TLS, Data Encryption, Vulnerability Testing.
→ Full-Stack AI Backends: Python (FastAPI, Flask, Django) and Node.js (NestJS, Express) backends built for performance, security, and scale.
→ Automations & Protocols: MCP, n8n, Make.
→ Databases: PostgreSQL, MongoDB, MySQL, Firebase, DynamoDB, CosmosDB, ClickHouse.
Click INVITE and let's stabilize and scale your AI infrastructure.
𝗠𝗖𝗣 𝗦𝗲𝗿𝘃𝗲𝗿𝘀 & 𝗔𝗴𝗲𝗻𝘁𝘀: 𝗚𝗲𝗻𝗸𝗶𝘁 / 𝗩𝗲𝗿𝘁𝗲𝘅 𝗔𝗜 / 𝗖𝗿𝗲𝘄𝗔𝗜 / 𝗟𝗮𝗻𝗴𝗚𝗿𝗮𝗽𝗵 / 𝗔𝘂𝘁𝗼𝗚𝗲𝗻
𝗩𝗼𝗶𝗰𝗲 𝗔𝗜 & 𝗧𝗲𝗹𝗲𝗽𝗵𝗼𝗻𝘆: 𝗘𝗹𝗲𝘃𝗲𝗻𝗟𝗮𝗯𝘀 / 𝗪𝗵𝗶𝘀𝗽𝗲𝗿 / 𝗩𝗔𝗣𝗜 / 𝗥𝗲𝘁𝗲𝗹𝗹 / 𝗧𝘄𝗶𝗹𝗶𝗼
𝗩𝗶𝗱𝗲𝗼 𝗚𝗲𝗻 & 𝗨𝗚𝗖: 𝗛𝗲𝘆𝗚𝗲𝗻 / 𝗖𝗼𝗺𝗳𝘆𝗨𝗜 / 𝗟𝗧𝗫 / 𝗦𝗲𝗲𝗱 𝗗𝗮𝗻𝗰𝗲
𝗖𝗥𝗠 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻: 𝗚𝗼𝗛𝗶𝗴𝗵𝗟𝗲𝘃𝗲𝗹 (𝗚𝗛𝗟) / 𝗭𝗼𝗵𝗼 / 𝗦𝗮𝗹𝗲𝘀𝗳𝗼𝗿𝗰𝗲 / 𝗛𝘂𝗯𝗦𝗽𝗼𝘁
𝗟𝗟𝗠𝘀 & 𝗜𝗻𝗳𝗿𝗮: 𝗔𝗪𝗦 𝗕𝗲𝗱𝗿𝗼𝗰𝗸 / 𝗖𝗹𝗮𝘂𝗱𝗲 (𝗖𝗼𝘄𝗼𝗿𝗸) / 𝗢𝗽𝗲𝗻𝗔𝗜 / 𝗛𝘂𝗴𝗴𝗶𝗻𝗴𝗙𝗮𝗰𝗲 / 𝘃𝗟𝗟𝗠
𝗙𝗶𝗻𝗲-𝗧𝘂𝗻𝗶𝗻𝗴: 𝗣𝗘𝗙𝗧 / 𝗟𝗼𝗥𝗔 / 𝗤𝗟𝗼𝗥𝗔 / 𝗥𝗟𝗛𝗙 / 𝗗𝗣𝗢
𝗥𝗔𝗚 & 𝗩𝗲𝗰𝘁𝗼𝗿𝘀: 𝗟𝗹𝗮𝗺𝗮𝗜𝗻𝗱𝗲𝘅 / 𝗟𝗮𝗻𝗴𝗖𝗵𝗮𝗶𝗻 / 𝗣𝗶𝗻𝗲𝗰𝗼𝗻𝗲 / 𝗤𝗱𝗿𝗮𝗻𝘁 / 𝗖𝗵𝗿𝗼𝗺𝗮 / 𝗙𝗔𝗜𝗦𝗦
𝗦𝗰𝗿𝗮𝗽𝗶𝗻𝗴 & 𝗗𝗮𝘁𝗮: 𝗖𝗿𝗮𝘄𝗹𝟰𝗔𝗜 / 𝗣𝗹𝗮𝘆𝘄𝗿𝗶𝗴𝗵𝘁 / 𝗦𝗲𝗹𝗲𝗻𝗶𝘂𝗺
𝗚𝗼𝘃𝗲𝗿𝗻𝗮𝗻𝗰𝗲 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆: 𝗠𝗮𝗰𝗵𝗶𝗻𝗲-𝗘𝗻𝗳𝗼𝗿𝗰𝗲𝗱 𝗚𝗼𝘃𝗲𝗿𝗻𝗮𝗻𝗰𝗲 (𝗠𝗘𝗚) / 𝗢𝗽𝗲𝗻𝗖𝗹𝗮𝘄
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