You will get a Custom Retrieval-Augmented AI System for Your Documents
Project details
I build reliable and scalable AI systems using Natural Language Processing (NLP), Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG) to help businesses and researchers turn their data into intelligent solutions.
My services include AI chatbots, document-based question answering systems, knowledge-base search platforms, sentiment analysis tools, content moderation systems, and multilingual NLP solutions. Each project is carefully designed for accuracy, performance, and real-world usability.
With strong experience in AI research and applied engineering, I focus on delivering clean code, proper documentation, and production-ready systems. You will receive a secure, optimized, and easy-to-maintain solution that fits your technical and business needs.
I follow a transparent development process: requirement analysis, data preparation, model development, system integration, testing, and deployment. You stay informed and involved at every stage.
If you are looking for a dedicated AI engineer who values quality, communication, and long-term success, feel free to message me. Let’s build an intelligent system that truly works for you.
My services include AI chatbots, document-based question answering systems, knowledge-base search platforms, sentiment analysis tools, content moderation systems, and multilingual NLP solutions. Each project is carefully designed for accuracy, performance, and real-world usability.
With strong experience in AI research and applied engineering, I focus on delivering clean code, proper documentation, and production-ready systems. You will receive a secure, optimized, and easy-to-maintain solution that fits your technical and business needs.
I follow a transparent development process: requirement analysis, data preparation, model development, system integration, testing, and deployment. You stay informed and involved at every stage.
If you are looking for a dedicated AI engineer who values quality, communication, and long-term success, feel free to message me. Let’s build an intelligent system that truly works for you.
AI Development Type
Deep Learning, Knowledge Representation, Model TuningAI Tools
Azure Machine Learning, deeplearn.js, Keras, PyTorch, Sonnet, TensorFlowAI Development Language
PythonWhat's included
| Service Tiers |
Starter
$30
|
Standard
$70
|
Advanced
$120
|
|---|---|---|---|
| Delivery Time | 7 days | 10 days | 15 days |
Number of Revisions | 1 | 2 | 2 |
AI Model Integration | |||
Detailed Code Comments | - | ||
Knowledge Graph | - | - | |
Model Documentation | - | ||
Ontology | - | - | |
Source Code | |||
Taxonomy | - | - |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$15 - $50
Additional Revision
+$10
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KC
Ken C.
Feb 1, 2026
Technical Consultation: Large-Scale Text Retrieval System Architecture Review (1-2 Hours, Paid)
About Samir
AI/NLP Engineer| RAG & LLM| Data Preprocessing& Research Backed System
Kathmandu, Nepal - 4:55 pm local time
I am an AI and NLP Engineer and published research paper author, specializing in Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and applied NLP systems. My work focuses on accuracy, evaluation, and real-world deployment, particularly for domain-specific and low-resource language applications.
I work at the intersection of research and production engineering—designing AI systems grounded in peer-reviewed methods, validating them with rigorous evaluation, and delivering production-ready solutions rather than experimental demos.
I am the winner of the AIDEA National-Level AI Hackathon, where my project NepSAUL was recognized for technical depth and real-world impact. The project was subsequently selected for angel investment seed funding, validating its practical and commercial viability.
𝐑𝐄𝐒𝐄𝐀𝐑𝐂𝐇 & 𝐏𝐔𝐁𝐋𝐈𝐂𝐀𝐓𝐈𝐎𝐍𝐒 (𝐀𝐔𝐓𝐇𝐎𝐑)
• Profanity and Offensiveness Detection in Nepali Social Media Using Bi-directional LSTM Models
21st International Conference on Natural Language Processing (ICON 2024)
• Evaluating Sentence Embedding Models for Nepali Sentiment Analysis
National Conference on Computer Innovation 2025
• Retrieval-Augmented Generation Framework for the Nepali Legal Domain Question Answering (Under Review)
𝐂𝐎𝐑𝐄 𝐄𝐗𝐏𝐄𝐑𝐓𝐈𝐒𝐄
𝗥𝗔𝗚 & 𝗟𝗟𝗠 𝗦𝘆𝘀𝘁𝗲𝗺𝘀
• Designed and implemented NepSAUL using 10,000+ real court case documents
• Hybrid retrieval using BM25 + dense embeddings
• Achieved 91% Precision@1 in low-resource legal data
• Grounded generation with LLM-as-Judge and expert review
𝗡𝗮𝘁𝘂𝗿𝗮𝗹 𝗟𝗮𝗻𝗴𝘂𝗮𝗴𝗲 𝗣𝗿𝗼𝗰𝗲𝘀𝘀𝗶𝗻𝗴
• Sentiment analysis, text classification, profanity detection
• Created and annotated 11,000+ real-world Nepali samples
• Noisy, multilingual, domain-specific data handling
𝗠𝗟 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴 & 𝗗𝗲𝗽𝗹𝗼𝘆𝗺𝗲𝗻𝘁
• Python, FastAPI, production inference APIs
• Research to production model transition
• Maintainable and evaluation-driven architectures
𝐓𝐄𝐂𝐇𝐍𝐈𝐂𝐀𝐋 𝐒𝐊𝐈𝐋𝐒
• Python, C++, JavaScript
• LangChain, Hugging Face, Multilingual BERT, Bi-LSTM
• BM25, FAISS, Pinecone
• TensorFlow, Keras, Scikit-learn
• FastAPI, Flask
𝐖𝐇𝐘 𝐂𝐋𝐈𝐄𝐍𝐓𝐒 𝐂𝐇𝐎𝐎𝐒𝐄 𝐌𝐄
• Research-backed engineering decisions
• Clear and transparent communication
• Production-focused system design
• Honest feasibility assessment
𝐀𝐕𝐀𝐈𝐋𝐀𝐁𝐈𝐋𝐈𝐓𝐘
If you are building a high-accuracy RAG system, LLM-powered research tool, or NLP pipeline using real-world data, I am available to review requirements and propose a technically sound architecture.
Steps for completing your project
After purchasing the project, send requirements so Samir can start the project.
Delivery time starts when Samir receives requirements from you.
Samir works on your project following the steps below.
Revisions may occur after the delivery date.
Requirement Analysis
Review client goals, data, documents, and technical requirements to finalize the project scope.
Data Preparation & Setup
Clean, preprocess, and organize datasets or documents. Prepare environment and tools.