Allah Nawaz | AI Builder | AI Deploy Network

About Allah

AI/ML & Automation Engineer with 4+ years of hands-on experience building practical machine learning solutions, Generative AI applications, intelligent automation workflows, RAG systems, and AI agents. Experienced in Python, LLM integrations, LangChain, LangGraph, n8n, API development and integration, vector databases, data processing, and workflow automation.

Skilled at connecting AI models with business processes to build automated systems for content generation, document processing, classification, prediction, research, customer workflows, and operational automation. Comfortable working with both cloud-based and local AI models and deploying applications using Docker and modern development tools.

CORE SKILLS

Artificial Intelligence & Generative AI

Generative AI Application Development

Large Language Models (LLMs)

Prompt Engineering

AI Agents & Multi-Agent Systems

Agentic AI Workflows

AI Chatbots & Intelligent Assistants

Text Generation & Content Automation

AI-powered Classification

AI Research & Automation

Local AI / Open-Source AI Models

Gemini / Google Generative AI

Ollama

Hugging Face

Machine Learning & Deep Learning

Supervised & Unsupervised Learning

Classification & Prediction Models

Deep Learning

Model Training & Fine-Tuning

Feature Engineering

Data Preprocessing & Cleaning

Model Evaluation

Model Optimization

TensorFlow

Scikit-learn

Python ML Pipelines

RAG & Knowledge-Based AI

Retrieval-Augmented Generation (RAG)

Embeddings

Semantic Search

Vector Search

Document Processing

Knowledge Bases

Pinecone

ChromaDB

Text Embeddings

AI Document Q&A

PDF / Document Data Extraction

AI Agents & Frameworks

LangChain

LangGraph

Agent Workflows

Tool Calling

Function Calling

Multi-Agent Architectures

AI Decision-Making Workflows

Memory & Context Management

API-connected AI Agents

Automation & Workflow Engineering

n8n

Make.com

Pabbly

AI Workflow Automation

Business Process Automation

API Automation

Webhook Automation

CRM / Email Automation

Content Automation

Data Processing Automation

Scheduled & Event-Driven Workflows

Third-Party API Integrations

Professional profile

Location: Lahore, Pakistan
Time zone: Asia/Karachi
Work mode: Remote
Availability: Available Now
AI experience: 4+ years
Languages: English, Arabic
Working hours: monday to saturday
Typical response: Within a few hours
Available in: United States, Australia, Austria, United Kingdom

Proven on the network

Implementation records and publicly available work, where published.

1 AI Deployment delivered, including 1 publicly identified implementation available to inspect.

Reported business outcomes

Hours Automated20 hours
period not specified
Automated 20 hours (period not specified)
Cost SavingsUSD 200
period not specified
Reduced operating costs by USD 200 (period not specified)
Revenue ImpactUSD 499
period not specified
Generated USD 499 additional revenue (period not specified)

Builder-reported outcomes, recorded on deployment and case study records that AI Deploy Network reviewed before publication. AI Deploy Network does not currently capture a measurement basis or calculation methodology for reported outcomes, so none is shown.

What Allah builds

Implementation domains listed on this profile. Evidence-supported items are identified separately below.

Specialisations

Agentic Workflow Automation

AI Agents

Anomaly Detection

Intelligent Automation

RAG & Knowledge Retrieval

Builder-listed deployment types

AI Agent
Task Automation
Workflow Automation

AI Deployments

Real AI implementations demonstrated through evidence.

01 / AI DeploymentPublished record

Agriculture AI Agent

**Agriculture AI Agent** Developed an AI-powered agriculture assistant using n8n, Google Gemini, and Pinecone vector database. It uses Retrieval-Augmented Generation (RAG), embeddings, and automated workflows to answer agriculture-related questions

20 hours automated / per month · USD 200 cost savings / per month · USD 499 reported revenue impact / per month

Agriculture · AI Agent · Task Automation · Workflow Automation

View Deployment

Implementation capabilities

Evidence-supported means linked to a published Deployment or Case Study; other capabilities are Builder declared.

Evidence-supported

AI Agent1 record
Task Automation1 record
Workflow Automation1 record

Builder declared

Agentic Workflow Automation
AI Agents
Anomaly Detection
Intelligent Automation
RAG & Knowledge Retrieval

Industry experience

Published Deployments support the listed counts. Other industries are Builder declared.

Agriculture

1 published Deployment

Banking

Builder declared

Cloud & Infrastructure Providers

Builder declared

E-Commerce

Builder declared

IT Services & Systems Integration

Builder declared

Trust & verification

A closer look at how this profile and its evidence are reviewed.

Community Member

Published evidence is reviewed against the AI Deploy Network Evidence Standard.

How verification works

Community

Verified Builder

Independently reviewed by AI Deploy Labs against the platform Evidence Standard.

How this is verifiedWhat the platform has established, and what remains builder-declared.

Identity and organisation: Identity checks confirm that the person presenting this profile controls the account and the professional identifiers attached to it, such as a LinkedIn profile. Organisation membership is confirmed by the organisation, not self-declared by the builder.
AI Deployments: An approved AI Deployment is an implementation record the builder submitted and the platform reviewed against the Evidence Standard before publication. Approval confirms the record is complete, coherent and consistent with the supporting material provided — it is not an audit of the client's systems.
Business outcomes: Outcome figures are recorded by the builder on the deployment or case study that produced them, and are reviewed at publication. Aggregates shown on this profile are calculated from those approved records only.
Evidence: Supporting evidence comes from the records the builder published on this platform: approved AI Deployments, published AI Case Studies, verification outcomes and organisation participation.
Currency: Older evidence continues to count and is never removed. Recency is presented separately through Professional Currency so that current expertise can be assessed alongside historical work.
Traceability: Every figure on this profile can be followed to the record that produced it. Open the linked AI Deployment or AI Case Study to read the outcome exactly as it was reported.

The platform does not independently audit client systems or financial records. How this is verified

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