You will get custm llm solution using langchain & nlp
Rising Talent
Project details
🚀 Welcome to my Upwork project catalog! I specialize in fine-tuning and deploying Large Language Models (LLMs) for high-performance NLP tasks, offering expert solutions tailored to your unique needs.
🌐 What I Provide: I fine-tune foundational and advanced LLMs, optimizing them for your specific domains and tasks. My expertise includes developing and deploying ChatGPT-powered chatbots using state-of-the-art language models for engaging, natural conversations. I leverage advanced techniques like Reinforcement Learning, Multi-Task Learning, LoRA, QLoRA, and FlashAttention to maximize model efficiency and performance.
💡 Custom prompt engineering is incorporated to ensure controlled, context-aware outputs. I expertly deploy your models on cloud platforms like AWS, Azure, or Runpod and offer bespoke NLP solutions using machine learning and deep learning frameworks.
🔧 My Tech Stack Includes:
Python, JavaScript, SQL, PyTorch, Transformers, LangChain, Pinecone, OpenAI, Llama-Index, Vector Databases, FastAPI, Streamlit, AWS RDS, and more.
📩 Ready to elevate your project? Let’s connect for exceptional results!
🌐 What I Provide: I fine-tune foundational and advanced LLMs, optimizing them for your specific domains and tasks. My expertise includes developing and deploying ChatGPT-powered chatbots using state-of-the-art language models for engaging, natural conversations. I leverage advanced techniques like Reinforcement Learning, Multi-Task Learning, LoRA, QLoRA, and FlashAttention to maximize model efficiency and performance.
💡 Custom prompt engineering is incorporated to ensure controlled, context-aware outputs. I expertly deploy your models on cloud platforms like AWS, Azure, or Runpod and offer bespoke NLP solutions using machine learning and deep learning frameworks.
🔧 My Tech Stack Includes:
Python, JavaScript, SQL, PyTorch, Transformers, LangChain, Pinecone, OpenAI, Llama-Index, Vector Databases, FastAPI, Streamlit, AWS RDS, and more.
📩 Ready to elevate your project? Let’s connect for exceptional results!
AI Algorithms
Autoencoder, Transformer ModelAI Applications
AI Chatbot, AI Content Creation, AI Mobile App Development, AI Text-to-Speech, AIOps, Conversational AI, Machine Translation, Natural Language Generation, Natural Language Understanding, Neural Machine Translation, Synthetic Data Generation, Text RecognitionAI Development Language
PythonAI Tools
Azure OpenAI, Hugging Face, Microsoft 365 Copilot, PyTorch, Streamlit, TensorFlow, Word2vecAI Models
BERT, BLOOM, ChatGPT, DALL-E, GPT-3, GPT-4, GPT-J, GPT-Neo, LaMDA, LLaMA, Naive Bayes Classifier, WhisperWhat's included
| Service Tiers |
Starter
$100
|
Standard
$300
|
Advanced
$1,000
|
|---|---|---|---|
| Delivery Time | 5 days | 10 days | 20 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 | - | - | - |
Frequently asked questions
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M M.
Jun 28, 2025
AI Agent Developer (LangChain + GPT-4o) for Structured Farm Data Parsing
Sajjad delivered exceptional work on our first PDF extractor agent by completing the entire build in just 10 days. He fully understood the scope, the technical nature of the project, and the larger vision of what FarmdOut is building. He is professional, kind, and thoughtful, and he communicates clearly and consistently.
After the initial agent was complete, we realized we needed something more autonomous. Though it represented a shift in direction, Sajjad took it on graciously and turned around an enhanced, autonomous version within just a few days. We compensated him for the added scope, but his responsiveness and ability to adapt so quickly were key.
I would absolutely hire Sajjad again and recommend him for any project involving autonomous agents, LangGraph, GPT-4o, agentic workflows, or scalable AI pipelines. His ability to work with evolving specifications while delivering clean, production-ready code makes him a standout contributor on any team.
After the initial agent was complete, we realized we needed something more autonomous. Though it represented a shift in direction, Sajjad took it on graciously and turned around an enhanced, autonomous version within just a few days. We compensated him for the added scope, but his responsiveness and ability to adapt so quickly were key.
I would absolutely hire Sajjad again and recommend him for any project involving autonomous agents, LangGraph, GPT-4o, agentic workflows, or scalable AI pipelines. His ability to work with evolving specifications while delivering clean, production-ready code makes him a standout contributor on any team.
JH
James H.
Jun 14, 2025
Upgrade data connection
Pretty good work and really good communication.
JH
James H.
Jun 9, 2025
Upgrade data connection
JH
James H.
Jun 2, 2025
Ai food data
About Sajjad
AI Engineer / AI Agents, RAG & AI Integration, AI Apps / python
100%
Job Success
Islamabad, Pakistan - 3:44 am local time
The agent works until it doesn't and nobody can tell which step failed. The chatbot answers confidently and the answers are subtly wrong. The AI needs data locked inside a system built in 2011 that nobody wants to touch. Someone asks a question in English and the SQL that comes back is wrong in a way that looks right.
These are almost never model problems. They're architecture, integration, and evaluation problems wearing a model problem's coat.
𝗛𝗼𝘄 𝘁𝗵𝗮𝘁 𝗹𝗼𝗼𝗸𝘀 𝗶𝗻 𝗽𝗿𝗮𝗰𝘁𝗶𝗰𝗲:
→ A UK clinic needed prescriptions written by voice against a live encrypted patient database. I matched their existing PHP encryption, decrypted in flight, added allergy conflict checks, calculated dosage from frequency and duration, and touched nothing in their schema.
→ A second service for the same clinic listens to consultations across in-person, phone, Zoom, and Meet, then writes the clinical note. It never writes into their database, it returns results through a signed callback.
→ Copiloto, a multi-agent system for a Chilean client that researches companies from web and B2B sources, then answers analytics questions in plain language against a 62k-course database, running semantic search and direct SQL in parallel before merging and re-ranking the results.
→ A UK property group runs almost the entire business through WhatsApp on twelve specialized agents, self-hosted on OpenClaw. Only the Dispatcher can send a message. The other eleven draft, and swapping Claude for Gemini is a one-line config change.
→ A New Zealand government client needed redaction they could actually certify. Seven detection layers including OCR for scanned files, every model running on their own hardware, and verification strict enough that a failing file is deleted rather than returned.
→ An Australian firm needed R&D tax submissions drafted from raw client documents, scored against all five official ATO criteria with a risk level and a questionnaire naming exactly what evidence is missing.
→ Navi, a document intelligence platform where hybrid pgvector and BM25 retrieval is fused with rank fusion, and every claim in the answer cites the image of the source page it came from. Answers can be restricted to a specific year range, and there's an admin dashboard behind it.
→ A voice receptionist SaaS that reads any business website and has a live phone agent answering calls about ninety seconds later.
→ A media system that makes raw video searchable in plain English, returning the exact timestamp where a topic was discussed, with speaker and emotion identified per scene.
I build full AI SaaS and AI websites as well, billing and admin included, when that's what's needed.
𝗧𝗵𝗲 𝘀𝘁𝗮𝗰𝗸: Python, FastAPI, LangChain, LangGraph, OpenClaw, Claude, GPT, Next.js, Supabase, Postgres, pgvector, Redis, Docker, AWS, RunPod, OCR, Langfuse.
→ 𝗗𝗲𝘀𝗰𝗿𝗶𝗯𝗲 𝘄𝗵𝗮𝘁'𝘀 𝗴𝗼𝗶𝗻𝗴 𝘄𝗿𝗼𝗻𝗴. 𝗜𝗳 𝗶𝘁'𝘀 𝗳𝗶𝘅𝗮𝗯𝗹𝗲 𝗶𝗻 𝗮𝗻 𝗵𝗼𝘂𝗿 𝗜'𝗹𝗹 𝘀𝗮𝘆 𝘀𝗼 𝗿𝗮𝘁𝗵𝗲𝗿 𝘁𝗵𝗮𝗻 𝘁𝘂𝗿𝗻𝗶𝗻𝗴 𝗶𝘁 𝗶𝗻𝘁𝗼 𝗮 𝗽𝗿𝗼𝗷𝗲𝗰𝘁.
Steps for completing your project
After purchasing the project, send requirements so Sajjad can start the project.
Delivery time starts when Sajjad receives requirements from you.
Sajjad works on your project following the steps below.
Revisions may occur after the delivery date.
Requirement Gathering:
The client purchases the project and provides comprehensive details on objectives, datasets, and desired outcomes.
Analysis & Solution Design
I assess your requirements and design a custom LLM solution, including a strategy for data curation and pre-processing.