Available for projects Remote worldwide
Ibadat Ali AI automation & workflow engineering
I build AI-powered workflows that replace manual processes — n8n, agent systems, LLM pipelines, predictive models, and client-ready software.
Meet Ibadat 01:14
A personal introduction to my work, the services I offer, and how I approach client delivery.
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Technologies and tools used across this portfolio: Demand forecasting, AI automation, Client-ready APIs, Predictive maintenance, RAG pipelines, Full-stack delivery.
01 / Selected projects
One curated catalog, ordered from priority client systems and product builds to focused analysis. Netflix Data Analysis is the only compact lab included. Open any project for its scope, approach, result, technologies, and available evidence.
WhatsApp intake · OCR · duplicate detection · Stripe verification
Result — Delivered payment-verification workflow with queueing, OCR fallback, Stripe reconciliation, duplicate handling, and handoff documentation.
Education · Client platform
Result — Production client platform with documented handoff and a live website.
Demand forecasting · 4-model ensemble
Result — Four-model comparison with live inference and downloadable planning reports.
Predictive maintenance · anomaly detection + scheduling
Result — NASA CMAPSS RUL study with anomaly detection, SHAP attribution, and scheduling.
Multimodal clinical workflow · Gemma 4 Hackathon
Result — Gemma hackathon submission with multimodal inputs, audit logging, and offline fallback.
Capture · enrich · outreach · report
Result — Client workflow proof spanning capture, enrichment, outreach, and reporting.
Agent tool-calling · MCP & RAG
Result — Open-source MCP tooling for structured repository context before agent actions.
WhatsApp trigger · memory · tool use
Result — Client workflow proof connecting WhatsApp intake, memory, FAQ, order capture, and inventory tools.
Live resume product workflow
Result — Live product workflow for structured resume creation, authenticated state, and PDF export.
AI-assisted learning workspace
Result — Full-stack learning workspace with goals, resources, reminders, analytics, and AI-assisted study.
Automated ETL · global analytics
Result — Database-backed analytics platform connecting automated ETL, APIs, and an interactive dashboard.
Topology-aware KD research
Result — Research prototype exploring topology-aware knowledge distillation for compact CT classification.
Multimodal assisted-review prototype
Result — Assisted-review prototype combining image, audio, and vital-sign inputs in one bounded workflow.
Deployable price-prediction workflow
Result — Deployable inference workflow translating e-commerce transaction data into price estimates.
Procurement analytics workflow
Result — Procurement analysis workflow connecting sales, purchases, pricing, invoices, and vendor performance.
Exploratory data analysis
02 / Capabilities and delivery
From a messy business process to a working, documented system. Each service is connected to a project that puts the capability into practice.
01 / Data analysis
From raw operational data to decision-ready analysis: query, clean, explore, visualise, and communicate the signal.
Tools and methods
02 / Data science
Structured predictive work with interpretable features, robust baselines, time-series forecasting, and clear model evaluation.
Tools and methods
03 / ML engineering
Deep-learning, anomaly-detection, and agent retrieval systems built around repeatable experimentation, explainability, and operational use cases.
Tools and methods
04 / AI automation and delivery
Production LLM workflows, agent tool-calling, APIs, and client-delivered platforms built with deterministic validation and operational telemetry.
Tools and methods
How I work
Project scopes are agreed before implementation; delivery is planned around the work, constraints, and handoff needs.
03 / Evidence
I make project scope and evidence easy to distinguish, so a demo, research build, or client delivery is not presented as something it isn’t.
Each catalog entry opens a case study with its problem, approach, result, technology stack, and links where available.
Client work, live builds, research, prototypes, and labs are labeled separately for context.
Private client work is shown without source links or confidential implementation details.
04 / About
From dataI’m Ibadat, an AI automation and workflow engineer based in Pakistan. I build systems across analysis, model development, automation, and application delivery.
From the first scope to evaluation and handoff, I make the assumptions and operating context clear for the people who use the system.
Read the résumé05 / Experience
Industry roles, independent delivery, and practical collaboration across data science, machine learning, and AI automation.
2025 — Present (paused Dec 2025 – Mar 2026 for full-time role)
Fiverr · Remote
Delivering predictive modeling, forecasting, NLP, RAG, computer vision, and AI automation systems for international clients, with stakeholder-ready reports and structured handoff documentation.
Dec 2025 — Mar 2026
Soft Shack · Full-time, on-site
Designed production ML and LLM-integrated automation pipelines with FastAPI and Docker, adding RAG retrieval, confidence gates, audit logging, and client-ready technical handoffs.
May 2025 — Aug 2025
Arch Technologies · Internship
Built and evaluated forecasting and predictive analytics models with Python, Scikit-learn, XGBoost, and Pandas; engineered SQL/CSV ETL workflows and delivered SHAP-based reports.
Education and development
Self-directed learning in machine learning, AI systems, and software engineering — strengthened through client delivery, applied research, and focused technical certifications.
Credentials
Open certificate
Open certificate
06 / Contact
Share the context, constraints, and what a useful outcome would look like. I’ll reply within one business day.
Most projects begin with a focused 30-minute conversation about the problem, constraints, and fit.
Signature / 01
— Ibadat Ali