You will get AI Chatbot Development RAG, LLM integrations, Langchain/Langgraph
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Project details
I build production-ready AI chatbots using RAG (Pinecone/ChromaDB) + LangChain/LangGraph with FastAPI backends and modern LLMs.
I can makePDFs, docs, websites, or internal knowledge base into a secure, accurate Q&A assistant with citations. I have 3 years of experience in AI niche .
Includes end-to-end pipeline: data ingestion → chunking → embeddings → retrieval → response orchestration + guardrails.
Features: multi-turn memory, tools/function-calling, role-based access, feedback loop, and analytics/logging.
Deployable via Docker/Cloud with REST APIs, auth, rate limits, and scalable architecture.
I can makePDFs, docs, websites, or internal knowledge base into a secure, accurate Q&A assistant with citations. I have 3 years of experience in AI niche .
Includes end-to-end pipeline: data ingestion → chunking → embeddings → retrieval → response orchestration + guardrails.
Features: multi-turn memory, tools/function-calling, role-based access, feedback loop, and analytics/logging.
Deployable via Docker/Cloud with REST APIs, auth, rate limits, and scalable architecture.
Machine Learning Tools
Azure Machine Learning, BERT, ChatGPT, Keras, MLflow, NLTK, NumPy, NVIDIA AI Platform, OpenCV, pandas, Python, Python Scikit-Learn, PyTorch, scikit-learn, SQL, TensorFlow, Tesseract OCR, Vertex AI, Word2vec, XGBoostWhat's included
| Service Tiers |
Starter
$75
|
Standard
$150
|
Advanced
$250
|
|---|---|---|---|
| Delivery Time | 2 days | 4 days | 7 days |
Number of Revisions | 0 | 1 | 2 |
Number of Model Variations | 1 | 2 | 2 |
Model Validation/Testing | - | - | - |
Model Documentation | - | - | - |
Data Source Connectivity | - | - | - |
Source Code | - | - | - |
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RG
Risky G.
May 19, 2025
Linear Regression Project
Sannan delivered the project on time, the project met all the requirements. 10/10 would recommend
RG
Risky G.
Apr 19, 2025
Programmer
Competent, delivered on time and made revisions when requested without additional charge.
FA
Fatima A.
Apr 9, 2025
Road defect project.
The project was completed efficiently and with professionalism. The work was delivered on time, and communication was always clear and prompt. I'm very happy with the results.
SA
Shahenaz A.
Mar 29, 2025
Yolo
About Sannan
AI Engineer | RAG | Agentic AI | OpenClaw | CV | Generative AI
100%
Job Success
Islamabad, Pakistan - 10:19 pm local time
AI / Machine Learning & Computer Vision specialist with hands-on experience building, training, and deploying deep learning models for real-world applications. I specialize in YOLO-based object detection/segmentation and image processing, with a strong background in PyTorch, TensorFlow, and OpenCV, Plus modern RAG and agentic AI LLM systems using LangChain and LangGraph.
Key Expertise
YOLO Object Detection & Segmentation: Custom training/tuning (YOLO v8–v12), dataset prep, evaluation, and edge AI deployment on Jetson Nano.
RAG & Agentic AI: Retrieval-augmented generation with LangChain/LangGraph, vector stores (Pinecone, ChromaDB), tool use, memory, and guardrails. Recommendation AI Engine Systems.
Model Deployment & Optimization: Packaging for production (REST), quantization/acceleration where applicable; VM-based deployments.
Full Pipeline Development: Data collection → labeling → training → testing → Flask/FastAPI REST APIs → monitoring.
MLOps & CI/CD: Experiment tracking, versioning, reproducible workflows, and automated delivery with GitHub/GitLab.
API Integration & Apps: Secure API integration with third-party services; Flutter front-ends that consume ML APIs.
Cloud & Storage: AWS S3 for datasets/artifacts; deployable on cloud VMs or on-prem.
Frameworks & Tools
PyTorch, TensorFlow/TFLite, OpenCV, scikit-learn, Pandas, NumPy
LangChain, LangGraph, RAG, LLM, Pinecone, ChromaDB
Flask, FastAPI (REST API deployment)
Databases SQL, MySQL, PostgreSQL, Supabase
GitHub, GitLab (MLOps/CI-CD)
Google Colab / Jupyter Notebook
AWS S3, VM-based deployments
React & Flutter (client apps & dashboards)
Steps for completing your project
After purchasing the project, send requirements so Sannan can start the project.
Delivery time starts when Sannan receives requirements from you.
Sannan works on your project following the steps below.
Revisions may occur after the delivery date.
RAG Chatbot Build (LangChain/LangGraph)
I implement the RAG pipeline with prompts, citations, memory, and guardrails (fallbacks, constraints) to reduce hallucinations.