You will get any Natural Language Processing (NLP) model using advanced techniques
Top Rated
Project details
You will get a production-ready AI-powered NLP (Natural Language Processing) model tailored to your exact business need whether it's text classification, sentiment analysis, named entity recognition, or summarization. With 10+ years of backend engineering experience and 170+ delivered projects, I don't just build machine learning models that work in a notebook; I build ones that survive real-world, messy data and integrate cleanly into your existing systems.
Most NLP and machine learning projects fail at the handoff stage great accuracy in testing, but broken or slow in production. My focus is on the full pipeline: clean architecture, edge-case handling, and cost-effective deployment using Python, spaCy, Hugging Face, and modern LLMs (OpenAI, Claude). You get a scalable AI solution built for real-world production, not just a demo.
Most NLP and machine learning projects fail at the handoff stage great accuracy in testing, but broken or slow in production. My focus is on the full pipeline: clean architecture, edge-case handling, and cost-effective deployment using Python, spaCy, Hugging Face, and modern LLMs (OpenAI, Claude). You get a scalable AI solution built for real-world production, not just a demo.
AI Development Type
Deep Learning, Knowledge Representation, Model TuningAI Tools
Amazon SageMaker, Keras, MLflow, Open Neural Network Exchange, PyTorch, TensorFlowAI Development Language
PythonWhat's included
| Service Tiers |
Starter
$149
|
Standard
$429
|
Advanced
$1,199
|
|---|---|---|---|
| Delivery Time | 3 days | 6 days | 10 days |
Number of Revisions | 1 | 2 | 3 |
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
+$49 - $399
Additional Revision
+$49
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DS
Darrell S.
Dec 17, 2025
AI and LLM developer
Excellent developer with a lot of skills.
DS
Darrell S.
Nov 9, 2025
Senior Backend Developer with AI expertise
Great service and very pleased with the end product! Will work with again.
MA
Mohamed A.
Nov 9, 2025
Fulltime Senior Tech Lead - Django + AI For Enterprise Platform
DS
Darrell S.
Oct 30, 2025
AI Agent Platform Developer
He delivered excellent work on time and with great attention to detail.
DS
Darrell S.
Oct 20, 2025
AI engineer with n8n, python, AWS experiance
An outstanding experience from start to finish. AI automation skills turned complex tasks into smooth efficient workflows and consistently went beyond expectations. Communication was clear fast and professional throughout the project making the whole process seamless. I highly recommend for anyone looking for reliable AI automation expertise.
About Abbas
AI/ML Developer | AI Automation | Multi-Agent | Python & Django | NLP
100%
Job Success
Lahore Cantt, Pakistan - 6:02 pm local time
Build production-ready AI systems that solve real business problems; not AI demos that break after deployment. Most AI projects fail because they never move past the prototype stage or break when they hit real-world data. I specialize in building robust Multi-Agent Systems and RAG (Retrieval Augmented Generation) architectures designed for enterprise scale and reliability.
𝗛𝗼𝘄 𝗜'𝗹𝗹 𝗦𝘁𝗮𝗿𝘁:
𝐅𝐫𝐞𝐞 𝟏𝟓-𝐦𝐢𝐧𝐮𝐭𝐞 𝐜𝐨𝐧𝐬𝐮𝐥𝐭𝐚𝐭𝐢𝐨𝐧 where I'll review your idea, explain what can realistically be automated with AI, outline the architecture, and tell you honestly if it's worth building.
𝟏. What can actually be built or automated with AI
𝟐. A simple, step-by-step roadmap to get there
𝟑. An honest opinion on whether it's even worth doing
I'll give you an honest technical assessment before you spend money.
Leveraging 𝟏𝟎+ 𝐲𝐞𝐚𝐫𝐬 of backend seniority and 𝟏𝟕𝟎+ 𝐩𝐫𝐨𝐣𝐞𝐜𝐭𝐬, I provide the infrastructure that makes AI work.I start by identifying specific bottlenecks whether that is lead processing, complex document retrieval, or automated data operations and build custom solutions using Python, LangGraph, and n8n.
My focus is on the architecture, not just the prompts. I ensure your LLM implementation is cost-effective, handles edge cases, and integrates seamlessly with your existing tech stack.
𝗧𝗘𝗖𝗛 𝗦𝗧𝗔𝗖𝗞
𝗔𝗜 & 𝗟𝗟𝗠𝘀: OpenAI, Claude, Llama, Mistral, Gemini, Hugging Face, Ollama, vLLM, LangChain, LangGraph, LlamaIndex, Multi-Agent Systems, RAG (Retrieval-Augmented Generation), Prompt Engineering, NLP, Machine Learning, LangSmith
𝗕𝗮𝗰𝗸𝗲𝗻𝗱: Python, FastAPI, Django, Elixir, Phoenix, PostgreSQL, Supabase, Redis, Celery, REST APIs, Microservices
𝗙𝗿𝗼𝗻𝘁𝗲𝗻𝗱: React, TypeScript, Next.js, Tailwind CSS
𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻: n8n, Workflow Automation, API Integrations, ETL Pipelines, Selenium
𝗖𝗹𝗼𝘂𝗱 & 𝗩𝗲𝗰𝘁𝗼𝗿: AWS (EC2, EventBridge), Docker, Kubernetes, Pinecone, Qdrant, pgvector
𝗗𝗲𝘃𝗢𝗽𝘀: CI/CD, GitHub Actions, Docker, Linux, Unit Testing, Terraform
𝐀𝐈 𝗧𝗼𝗼𝗹𝘀: Claude Code, Cursor, Lovable, Windsurf, GitHub Copilot, Bolt, v0
𝗥𝗘𝗖𝗘𝗡𝗧 𝗣𝗥𝗢𝗗𝗨𝗖𝗧𝗜𝗢𝗡 𝗦𝗢𝗟𝗨𝗧𝗜𝗢𝗡𝗦
1. InvoCom
Built an AI/NLP-powered chatbot platform that processes, interprets, and responds to customer communications automatically, streamlining business-to-customer engagement.
Stack: ReactJS, NodeJS, AI, NLP, Machine Learning
Industry: AI Chatbot / Business Communication
2. AppWork
Automated tenant-application processing for a real estate platform with an NLP-powered web portal and mobile app.
Stack: TypeScript, React.js, Elixir, Phoenix, PostgreSQL, React Native, Google NLP
Industry: Real Estate / Service-on-Demand
𝗦𝗘𝗥𝗩𝗜𝗖𝗘𝗦
✔ Agentic Workflows: Moving beyond chatbots into autonomous task execution.
✔ Multi-Agent Systems: Orchestrating complex reasoning using LangGraph and CrewAI.
✔ AI Chatbots & Voice Agents: Building conversational and real-time voice-based AI assistants for support and automation.
✔ Advanced RAG Pipelines: Enterprise-grade retrieval systems for high-accuracy knowledge search over massive private datasets.
✔ MCP Server Integration: Connecting AI agents to external tools, APIs, and data sources via Model Context Protocol.
✔ AI-Powered SaaS & MVP Development: Building and launching production-ready SaaS platforms and MVPs with integrated AI features.
✔ Workflow Automation: End-to-end business process automation via n8n and Python.
✔ Backend Architecture: Production-grade FastAPI, Django, and AWS deployment.
𝗜𝗡𝗗𝗨𝗦𝗧𝗥𝗜𝗘𝗦 𝗦𝗘𝗥𝗩𝗘𝗗:
Healthcare, Fintech, Real Estate, eCommerce, and Blockchain delivering production-grade backend and AI systems across regulated, high-stakes, and high-scale environments.
𝗪𝗛𝗬 𝗖𝗟𝗜𝗘𝗡𝗧𝗦 𝗛𝗜𝗥𝗘 𝗠𝗘
• 100% Job Success Score with a focus on business ROI.
• Proven Seniority: I bridge the gap between AI experimentation and robust software engineering.
• Reliability: I deliver clean, maintainable code designed for long-term production use.
If you are looking for a technical partner to ensure your AI investment delivers a measurable return, let’s discuss your project.
𝐋𝐞𝐭'𝐬 𝐝𝐢𝐬𝐜𝐮𝐬𝐬 𝐲𝐨𝐮𝐫 𝐩𝐫𝐨𝐣𝐞𝐜𝐭 𝐬𝐞𝐧𝐝 𝐦𝐞 𝐚 𝐦𝐞𝐬𝐬𝐚𝐠𝐞 𝐚𝐧𝐝 𝐈'𝐥𝐥 𝐡𝐞𝐥𝐩 𝐲𝐨𝐮 𝐟𝐢𝐠𝐮𝐫𝐞 𝐨𝐮𝐭 𝐭𝐡𝐞 𝐛𝐞𝐬𝐭 𝐭𝐞𝐜𝐡𝐧𝐢𝐜𝐚𝐥 𝐚𝐩𝐩𝐫𝐨𝐚𝐜𝐡.
AI Engineer | AI Developer | API Developer | Python Developer | Python Django | NLP Machine Learning Python | Python Full Stack Developer | MLM Software Developer | LLM Developer | Python Fastapi | Full Stack Developer AI | Natural Language Processing | AI NLP | GPT-3 NLP | NLP Chatbot | NLP Engineer | ML Developer | Machine Learning Model | Cloud solution Architect | Github Copilot | AWS CI/CD | Large Language Model ( LLMs) | LLM Integration | AI Chatbot Developer | OpenAI chatbot | Python Rest Api Developer | OpenAI Api | AI consultant | AI ML | AI Deep Learning | PyTorch | pinecone
Steps for completing your project
After purchasing the project, send requirements so Abbas can start the project.
Delivery time starts when Abbas receives requirements from you.
Abbas works on your project following the steps below.
Revisions may occur after the delivery date.
Data & requirements review
I review your sample text data, understand the specific NLP task (classification, NER, summarization, etc.), and confirm the expected output format with you
Model design & development
I select the best approach (pretrained model, fine-tuning, or custom architecture) and build the NLP pipeline using Python, spaCy, Hugging Face, or LLMs as needed