You will get n8n and Make Automation
Project details
Someone copies data between systems every day and it fails quietly. I build n8n or Make workflows that never duplicate a record or undo a manual fix.
➜ THE PROBLEM
The copying is dull and slow. The real cost is that it breaks without telling anyone. A message arrives twice and you get two records. A retry overwrites a correction someone made by hand. At one client the nightly refresh destroyed a day of manual work every time it ran, and reported success.
➜ COMPLIANCE HANDLED
Every record gets a unique key, so running the job twice updates the right row instead of creating a duplicate or wiping a manual fix. Failed runs are routed to a person, not swallowed. Every run is logged with what changed, so your numbers reconcile and you can prove what happened on any given night.
➜ WHAT YOU GET
• The working workflow in your own account. You own it.
• Error handling, retries, and alerting that reaches a human.
• Connections to your CRM, sheets, Slack, email, payments or any API.
• Documentation so your team can extend it without me.
➜ THE PROBLEM
The copying is dull and slow. The real cost is that it breaks without telling anyone. A message arrives twice and you get two records. A retry overwrites a correction someone made by hand. At one client the nightly refresh destroyed a day of manual work every time it ran, and reported success.
➜ COMPLIANCE HANDLED
Every record gets a unique key, so running the job twice updates the right row instead of creating a duplicate or wiping a manual fix. Failed runs are routed to a person, not swallowed. Every run is logged with what changed, so your numbers reconcile and you can prove what happened on any given night.
➜ WHAT YOU GET
• The working workflow in your own account. You own it.
• Error handling, retries, and alerting that reaches a human.
• Connections to your CRM, sheets, Slack, email, payments or any API.
• Documentation so your team can extend it without me.
AI Algorithms
AdaBoost, Convolutional Neural Network, Generative Adversarial Network, Large Language Model, Long Short-Term Memory Network, Multimodal Large Language Model, Recurrent Neural Network, Self-Organizing Map, Transformer Model, YOLOAI Applications
AI Chatbot, AI Content Creation, AI Mobile App Development, AI Text-to-Image, AI Text-to-Speech, AI-Enhanced Medical Imaging, AI-Generated Music, Automatic Speech Recognition, Conversational AI, Natural Language Understanding, Object Detection, Speech SynthesisAI Development Language
PythonAI Tools
Azure OpenAI, GitHub Copilot, Gradio, Hugging Face, Microsoft 365 Copilot, NVIDIA AI Platform, PyTorch, Replit, Streamlit, TensorFlowAI Models
ChatGPT, DALL-E, GPT-3, GPT-4, GPT-Neo, LLaMA, Midjourney AI, OpenAI Codex, Stable Diffusion, WhisperWhat's included
| Service Tiers |
Starter
$150
|
Standard
$400
|
Advanced
$900
|
|---|---|---|---|
| Delivery Time | 3 days | 7 days | 14 days |
Number of Revisions | 2 | 2 | 3 |
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 |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$100 - $550
Additional Revision
+$60
Extra system connection
(+ 2 Days)
+$100
Custom middleware
(+ 4 Days)
+$300
30 days monitoring and fixes
+$200Frequently asked questions
About Abdullah
AI Architect | 5 years | Enterprise RAG Systems, Agents & AWS MLOps
Lahore, Pakistan - 11:23 pm local time
My career began in the trenches of classical statistical modeling and specialized NLP, working with models like BioBERT and LegalBERT. As the industry shifted, I transitioned into the Generative AI space during the era of raw text generation. However, the real turning point in my career came with the evolution of modern chat models and autonomous agents. Today, my core specialty is forcing non-deterministic AI to behave deterministically. By utilizing strict schema validation tools like Pydantic, I ensure AI outputs are perfectly structured with near-zero hallucinations, allowing me to deploy robust, production-ready, Human-in-the-Loop (HITL) agentic systems.
Historically, my deep domain expertise lies in FinTech, PropTech, and HealthTech, with additional touchpoints in EdTech. In every engagement, I don't just jump in as a standard developer; I act as a strategic technical partner. My ultimate goal is to architect automation that directly increases my client's revenue, slashes their manual operational overhead, and minimizes their business costs.
To give you an example of this business impact, during my time in the PropTech/FinTech space at Prypco, the company was facing a massive bottleneck in their mortgage processing pipeline. Customers came from various nationalities, and advisors were spending up to 3 days manually verifying documents and bundling them to meet the strict compliance requirements of different banks. I architected and deployed a Human-in-the-Loop agentic system that completely automated this verification and bundling process. We successfully reduced the processing time from 3 days down to just 15 minutes. This allowed advisors to handle exponentially more clients per day, providing lightning-fast responses that helped Prypco establish a virtual monopoly in their market.
Similarly, in the HealthTech space at SutureHealth, I built a HIPAA-compliant NLP orchestration platform that tackled the massive administrative burden on healthcare providers. I engineered a real-time transcription and parsing pipeline that listened to live doctor-patient conversations and autonomously synthesized them into structured, highly accurate clinical notes. By eliminating the manual charting process, care teams were able to reclaim hours of their day to focus strictly on patient care, drastically improving both clinic efficiency and patient outcomes.
My automation expertise also extends into complex Computer Vision for the architectural and compliance sectors. For a recent client, the manual process of planning and placing ADA-compliant signage on dense architectural blueprints was incredibly tedious and error-prone. To solve this, I architected an end-to-end, multi-tenant platform powered by custom fine-tuned YOLO object detection models. The system autonomously scanned complex PDFs, utilized spatial OCR to semantically map room types, and dynamically scaled inference resolution to detect minute structural thresholds (like doors). Instead of blindly burning images onto a PDF, I decoupled the architecture, saving lightweight coordinate vectors to the database and utilizing a Just-In-Time (JIT) rendering engine upon download. This not only automated the entire signage planning process but drastically reduced cloud compute costs and provided organizational owners with a lightning-fast UI to manage compliance effortlessly.
Moving forward, while I continue to deliver immense value in my core domains, I am actively looking forward to bringing this level of autonomous, ROI-driven architecture to emerging sectors like GovTech, GreenTech, and AgriTech. I believe the complex data challenges in those spaces are perfectly suited for the deterministic AI ecosystems I build.
If you are looking to automate your business, streamline your workflows, or completely eliminate repetitive daily bottlenecks, please feel free to contact me.
Steps for completing your project
After purchasing the project, send requirements so Abdullah can start the project.
Delivery time starts when Abdullah receives requirements from you.
Abdullah works on your project following the steps below.
Revisions may occur after the delivery date.
Kick-off and process walkthrough
You show me how the process works today, including the parts people still do by hand.
You give test access
Test logins or sandbox access for each system the workflow needs to touch.