Laiba Ghalib | AI Builder | AI Deploy Network

About Laiba

I’m an AI Engineer based in Lahore, Pakistan, specialising in agentic workflows and Retrieval-Augmented Generation (RAG). I build AI agents, chatbots, and knowledge retrieval systems that give accurate, traceable answers. My open-source RAG platform processes unstructured PDFs and responds in natural language with page-level citations, which reduces hallucinations. I work across software, IT services, data, and e-commerce, and I’m available for consulting, project work, and full-time roles. I work remotely or hybrid and speak English, Urdu, and Punjabi.

Professional profile

Location: Lahore, Pakistan
Time zone: Asia/Karachi
Availability: Available Now
Languages: English, Urdu, Punjabi
Typical response: Within a few hours

Proven on the network

Implementation records and publicly available work, where published.

0 AI Deployments delivered. No publicly identified implementations are available to inspect.

What Laiba builds

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

Specialisations

Agentic Workflow Automation

AI Agents

Chatbots

Prompt & Context Engineering

RAG & Knowledge Retrieval

AI Deployments

Real AI implementations demonstrated through evidence.

No publicly identified Deployments are available to inspect.

Implementation capabilities

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

Evidence-supported

No published evidence linked yet.

Builder declared

Agentic Workflow Automation
AI Agents
Chatbots
Prompt & Context Engineering
RAG & Knowledge Retrieval

Industry experience

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

Cross-Industry / Horizontal

Builder declared

Data & Analytics

Builder declared

E-Commerce

Builder declared

IT Services & Systems Integration

Builder declared

Software & SaaS

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

Professional record and further evidence

Client Portfolio

Portfolio started

Open-Source Software Development
RAG • Software & SaaS
Pakistan2026
• Developed and deployed an open-source Retrieval-Augmented Generation (RAG) platform that processes unstructured PDFs and generates natural language responses equipped with precise page-level citations to eliminate text hallucinations.

Professional Certifications

Well credentialed

Data Science Essentials with Python
Cisco Networking Academy
Issued Oct 2026
Machine Learning Explainability
Kaggle
Issued Oct 2026
The Art of Prompt Engineering
Cognitive Class
Issued Oct 2026

Ready to discuss your AI implementation?

Tell Laiba Ghalib what you are trying to automate and the outcome you need. Your message goes directly to the builder, with a copy kept in your Organisation Workspace.