Umair Ahmed | AI Builder | AI Deploy Network

About Umair

Full-stack AI engineer. I build web apps and the AI inside them, end to end: Next.js and Node.js on the web side, Python/FastAPI and LangChain for the model work, PostgreSQL underneath. Currently on Adroom (adroom.pixis.ai), a generative-AI ad platform, where I built the quality gate that scores generated video and regenerates low scorers. Before that: eDaftar, a document AI system (OCR, LLM drafting, role-based access) used daily by 100+ government staff, and a RAG legal assistant with a LoRA-fine-tuned LLaMA model. One IEEE paper accepted on speech recognition for a low-resource language.

Professional profile

Location: Islamabad, Pakistan
Time zone: Asia/Karachi
Availability: Available Now
AI experience: 1+ years
Industry experience: 2+ years
Languages: English
Working hours: 09:00–18:00 PKT, Mon–Fri
Typical response: Within 24 hours

Proven on the network

Implementation records and publicly available work, where published.

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

What Umair builds

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

Specialisations

AI Agents

Document Intelligence

Fine-Tuning & Model Customisation

RAG & Knowledge Retrieval

Builder-listed deployment types

Document Processing
OCR & Document Understanding
Task Automation

AI Deployments

Real AI implementations demonstrated through evidence.

01 / AI DeploymentPublished record

eDaftar – AI document drafting for Sindh government offices

OCR plus LLM drafting system for Sindh government offices: extracts data from uploaded documents, drafts official correspondence for staff approval, with audit logs and role-based access. Used daily by 100+ civil servants.

Government · Document Processing · OCR & Document Understanding · Task Automation

View Deployment

Implementation capabilities

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

Evidence-supported

Document Processing1 record
OCR & Document Understanding1 record
Task Automation1 record

Builder declared

AI Agents
Document Intelligence
Fine-Tuning & Model Customisation
RAG & Knowledge Retrieval

Technology

Technologies listed by the Builder, distinguished by published evidence.

Evidence-supported

Next.js1 record
Node.js1 record
OpenAI Agents SDK1 record

Builder declared

AWS
FAISS
FastAPI
Gemini Omni 1.1 Flash
Hugging Face Inference
LangChain
PostgreSQL
PyTorch
Python

Industry experience

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

Government

1 published Deployment

E-Commerce

Builder declared

Legal

Builder declared

Marketing & Advertising

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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