You will get custom NLP automation pipeline to streamline your workflows
Project details
Every support ticket handled manually, every lead sorted by hand, every email triaged by a person — that's time and money your team shouldn't be spending.
I build NLP automation pipelines that classify, route, and respond to incoming text automatically — reducing manual workload by 30–40% based on real client results in fintech.
What you get:
• Intent detection & text classification tailored to your use case
• Automated routing logic (to teams, queues, CRMs, or APIs)
• Built with GPT-4 or fine-tuned transformer models, depending on volume
• Integrates with your existing tools — no rip-and-replace
• Delivered as clean Python + Docker — your team can maintain it
Tech stack: Python · spaCy · Transformers · GPT-4o · FastAPI · Docker
Not sure if your process can be automated? Message me — I'll give you an honest answer within a few hours.
I build NLP automation pipelines that classify, route, and respond to incoming text automatically — reducing manual workload by 30–40% based on real client results in fintech.
What you get:
• Intent detection & text classification tailored to your use case
• Automated routing logic (to teams, queues, CRMs, or APIs)
• Built with GPT-4 or fine-tuned transformer models, depending on volume
• Integrates with your existing tools — no rip-and-replace
• Delivered as clean Python + Docker — your team can maintain it
Tech stack: Python · spaCy · Transformers · GPT-4o · FastAPI · Docker
Not sure if your process can be automated? Message me — I'll give you an honest answer within a few hours.
Machine Learning Tools
ChatGPT, fastText, GitHub Copilot, GPT-3, Keras, Kubeflow, MLflow, NLTK, NumPy, OpenCV, pandas, Python, Python Scikit-Learn, PyTorch, scikit-learn, SciPy, Scrapy, SQL, Stanford CoreNLP, TensorFlow, Tesseract OCR, TextBlob, XGBoostWhat's included
| Service Tiers |
Starter
$120
|
Standard
$280
|
Advanced
$600
|
|---|---|---|---|
| Delivery Time | 5 days | 10 days | 16 days |
Number of Revisions | 1 | 2 | 3 |
Number of Model Variations | 1 | 2 | 3 |
Number of Scenarios | 1 | 3 | 5 |
Number of Graphs/Charts | 1 | 3 | 5 |
Model Validation/Testing | - | ||
Model Documentation | - | ||
Data Source Connectivity | - | - | |
Source Code |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$25 - $70
Additional Revision
+$20
Additional Model Variation
(+ 1 Day)
+$30
Additional Scenario
(+ 1 Day)
+$20
Model Validation/Testing
(+ 2 Days)
+$40
Model Documentation
(+ 1 Day)
+$30
Data Source Connectivity
(+ 2 Days)
+$50Frequently asked questions
About Sarim
AI Developer | LLM Pipelines, NLP Automation & Intelligent Systems
Islamabad, Pakistan - 4:44 pm local time
What I bring to your project:
- LLM Integration & Chatbot Systems: I build custom AI agents and automation workflows using GPT-4o, Claude, and LangChain — integrated into CRMs, support platforms, and business tools. At GO-Globe, my NLP-driven customer service automation cut manual support workload by ~35% for fintech clients including Al Dar Exchange (Qatar).
- RAG & Document Intelligence: I architect privacy-first Retrieval-Augmented Generation (RAG) systems with hybrid semantic + keyword retrieval (75%+ accuracy), OCR pipelines, and local LLM inference — processing 50-page docs in under 45 seconds.
- Data Engineering & Cloud Pipelines: I've built medallion data lakes on AWS handling 400–500 GB of raw data, automated ingestion across 100+ datasets, and replaced fully manual analyst workflows with parameter-driven export systems.
- Computer Vision & NLP Analytics: I've shipped real-time YOLOv8 object detection dashboards with heatmaps and tracking, and NLP pipelines processing 70,000+ news sources for sentiment analysis and media bias detection.
Tech I use daily: Python, PyTorch, LangChain, FAISS, OpenAI/Anthropic APIs, Docker, AWS, FastAPI, Streamlit, spaCy, Transformers.
I'm a final-year BS AI student at FAST-NUCES, recipient of the Best Internee Award at AI GenMat, and I deliver clean, well-documented, production-ready code. If you need intelligent automation that actually works at scale — let's talk.
Steps for completing your project
After purchasing the project, send requirements so Sarim can start the project.
Delivery time starts when Sarim receives requirements from you.
Sarim works on your project following the steps below.
Revisions may occur after the delivery date.
Process audit & scoping
I review your current workflow, identify automation opportunities, and confirm the pipeline design.
Data preprocessing & model selection
input data is cleaned, labeled if needed, and the right NLP approach is selected (rule-based, transformer, LLM).