You will get Custom RAG Pipelines with Vector DBs | Pinecone, Weaviate, FAISS | Gen AI
Project details
⚡ Custom RAG Pipelines with Vector Databases (Pinecone • Weaviate • FAISS)
Looking to supercharge your LLM apps with accurate, context-aware responses? I build Retrieval-Augmented Generation (RAG) pipelines that combine Generative AI + Vector DBs for powerful knowledge-driven AI solutions.
🔹 What I Deliver:
RAG Pipeline Development – tailored to your data (PDFs, docs, databases, APIs).
Vector DB Integration – Pinecone, Weaviate, FAISS, Milvus, or ChromaDB.
Framework Expertise – LangChain, LlamaIndex, Haystack.
Data Preprocessing – chunking, embeddings (OpenAI, HuggingFace, Cohere).
Optimized Retrieval – hybrid search, semantic search, metadata filtering.
Deployment Ready – scalable APIs, containers, or cloud setup.
🔹 Use Cases:
✔️ Enterprise Knowledge Bases
✔️ Chatbots & AI Assistants
✔️ Research/Legal/Medical Knowledge Systems
✔️ SaaS AI Integrations
✔️ Context-aware AI Q&A
🔹 Why Work With Me?
5+ years in AI & Data Engineering
Built multi-LLM + vector DB production apps
Experience across Generative AI, NLP, and SaaS platforms
Clear documentation & collaborative approach
👉 Let’s build your next-gen RAG pipeline and make your AI smarter.
Looking to supercharge your LLM apps with accurate, context-aware responses? I build Retrieval-Augmented Generation (RAG) pipelines that combine Generative AI + Vector DBs for powerful knowledge-driven AI solutions.
🔹 What I Deliver:
RAG Pipeline Development – tailored to your data (PDFs, docs, databases, APIs).
Vector DB Integration – Pinecone, Weaviate, FAISS, Milvus, or ChromaDB.
Framework Expertise – LangChain, LlamaIndex, Haystack.
Data Preprocessing – chunking, embeddings (OpenAI, HuggingFace, Cohere).
Optimized Retrieval – hybrid search, semantic search, metadata filtering.
Deployment Ready – scalable APIs, containers, or cloud setup.
🔹 Use Cases:
✔️ Enterprise Knowledge Bases
✔️ Chatbots & AI Assistants
✔️ Research/Legal/Medical Knowledge Systems
✔️ SaaS AI Integrations
✔️ Context-aware AI Q&A
🔹 Why Work With Me?
5+ years in AI & Data Engineering
Built multi-LLM + vector DB production apps
Experience across Generative AI, NLP, and SaaS platforms
Clear documentation & collaborative approach
👉 Let’s build your next-gen RAG pipeline and make your AI smarter.
Programming Languages
C, C++, C#, Dart, Java, Python, VB, Lua, JavaScript, Delphi, KotlinOperating System
WindowsDesktop App Expertise
App Design, Application Setup & Installation, Development, Software Debugging, Performance Optimization, Security, W3C Markup Validation Service, Localization, Application Review & OptimizationWhat's included
| Service Tiers |
Starter
$95
|
Standard
$745
|
Advanced
$1,495
|
|---|---|---|---|
| Delivery Time | 1 day | 3 days | 5 days |
Number of Revisions | Unlimited | Unlimited | Unlimited |
Bug Investigation | - | - | |
Source Code | |||
Database Integration | - | ||
Detailed Code Comments | - | ||
Fix Documentation | - | - |
Frequently asked questions
4 reviews
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MM
Mick M.
Jan 20, 2024
Programmatic Subplots Pandas
Perfect result!
GM
George M.
Feb 19, 2023
Need help with data science
He communicates very well and delivers great work. I'd like to work with Muhammad again.
AK
Abhishek K.
Jul 13, 2021
I want to learn python from scratch with problem solving
Noman is amazing with python. He gave me pretty good exposure to python concepts and provided a roadmap to become a python web developer with flask.
JB
John B.
May 16, 2021
Join our team on GitHub !!
Thanks !! 🚀🚀
About Muhammad Noman
Python Data Scientist, ML & Big Data Engineer, Generative AI -LLM, API
Karachi, Pakistan - 12:39 pm local time
I help enterprises transform raw data into scalable AI/ML solutions that cut costs, boost efficiency, and drive measurable ROI.
💼 Work:
✅ AI Agents & Chatbots: Built IBM Watson + LLM (LangChain, RAG, XAI) chatbot handling 5,000+ monthly queries, cutting response time by 40% and boosting CSAT by 18%
✅ Fraud Detection Models: Developed an ML pipeline improving transaction monitoring by 20% accuracy and reducing false positives by 15%
✅ OCR & Automation: Engineered OCR workflow with Python/OpenCV, integrated into Temenos T24, reducing manual data entry by 60%
✅ Data Pipelines: Automated ETL (DB2 → Hive → SQL Server → Power BI Server) via PySpark/Scala + Cron, reducing runtimes by 30% and ensuring reliability with log monitoring
✅ Big Data Engineering: Managed 12-node Cloudera clusters (100+ TB) with 99.9% uptime, optimizing Spark + Hive workloads for faster queries
✅ BI Dashboards: Designed 30+ dashboards in Power BI, Tableau, Qlik & IBM Cognos, deployed for 1,000+ enterprise users across Risk, Compliance & Finance
✅ Streaming Pipelines: Built Kafka + Spark streaming systems for real-time analytics, processing 2M+ daily transactions
✅ Regulatory Reporting: Automated SBP compliance reports (Python + SQL chaining), cutting manual effort by 70%
✅ RPA Bots: Built a Selenium-based compliance bot, saving 50+ hours/month in analyst workload
✅ Data Warehousing: Migrated 50+ TB structured/unstructured data on Cloudera stack (Hive, HDFS, Impala), cutting storage costs by 20%
💻 Skills:
☑ Languages: Python, R, Scala, SQL, Bash
☑ Generative AI: LLMs (GPT, LLaMA, Claude), LLM fine-tuning (LoRA, PEFT), RAG pipelines, LangChain, LlamaIndex, AI Agents, Vector Databases (Pinecone, Weaviate, FAISS, Milvus, ChromaDB), Prompt Engineering, Chatbots, Multi-Modal AI, Knowledge Graphs, Guardrails, XAI (SHAP, LIME)
☑ Big Data & Cloud: Cloudera, Hadoop (HDFS, MapReduce, YARN), Spark (PySpark/Scala, MLlib, Streaming), Kafka, Flink, Hive, Pig, Impala, Storm, Sqoop, Oozie, NiFi, Zookeeper, Databricks, Snowflake, Delta Lake, Data Warehouse Architecture, Presto, AWS (SageMaker, EMR, S3, Lambda, Redshift), GCP (BigQuery, Vertex AI), Azure (Synapse, ML, OpenAI)
☑ ETL & Data Engineering: Airflow, dbt, Cron, Pandas, NumPy, Spark SQL, Data Wrangling, APIs, Automation, ETL pipelines, OpenCV, BeautifulSoup, Scrapy
☑ Databases: SQL Server, MySQL, PostgreSQL, IBM DB2, MongoDB, Hive, Cassandra, Redis, Elasticsearch
☑ Machine Learning & Data Science: Predictive analytics (Deposit Prediction, Fraud Detection), NLP, Computer Vision, OCR, Supervised/Unsupervised Learning, Reinforcement Learning, Deep Learning (CNNs, RNNs, Transformers), scikit-learn, TensorFlow, Keras, PyTorch, XGBoost, LightGBM, CatBoost, Hugging Face, AutoML, MLOps (MLflow, Kubeflow, DVC, Airflow
☑ Business Intelligence & Visualization: Power BI, Tableau, Looker, Qlik, IBM Cognos Analytics, Excel, Matplotlib, Seaborn, Plotly, PBI Report Server Configuration
☑ Development (Backend & Full-Stack): Python (APIs, automation, ETL, backend), Django, Flask, FastAPI, Streamlit, Node.js, React, WordPress (Elementor), Odoo ERP, AI SaaS apps
☑ Automation: RPA bots (Selenium), Web Scraping, ETL Workflow Automation
☑ DevOps & Tools: Git, Gitlab, Docker, Kubernetes, CI/CD pipelines, Jupyter, PyCharm, Anaconda Distribution
🌎 Trusted by clients in banking, fintech, e-commerce, and enterprise systems for writing clean, scalable, and production-ready code.
📩 Not sure where to start? Share your challenge with me, and I’ll map out a step-by-step AI/data strategy - no fluff, just actionable insights that you can apply right away.
Steps for completing your project
After purchasing the project, send requirements so Muhammad Noman can start the project.
Delivery time starts when Muhammad Noman receives requirements from you.
Muhammad Noman works on your project following the steps below.
Revisions may occur after the delivery date.
What type of data do you want to use (PDFs, databases, APIs)?
Which vector DB do you prefer (Pinecone, Weaviate, FAISS, Milvus, etc.)?