Results · Recent work

Systems quietly earning their keep.

Client projects, internal tools, and hackathon builds, all designed to solve one problem properly.

Weekly
Shortlist, not a pile of resumes
0
Manual data entry
0.95+
ROC-AUC, cart model
100k+
Orders analyzed
● Architecture Client project Hiring automation

QALAM Architects stopped drowning in resumes and got a clean weekly shortlist instead.

Shortlist
Only qualified candidates surface
~2 weeks
From kickoff to live
Hands-off
Runs without their attention

The problem

Every week, QALAM's partners spent hours personally reading applications, scheduling interviews with people who turned out to be unqualified, and playing admin instead of doing architecture.

What we built

A pre-screening pipeline that parses every applicant's resume and portfolio against weighted criteria: experience, software, location, visa. Only shortlisted candidates surface in the partners' inbox. Everyone else gets a professional auto-response.

The result

They now interview fewer candidates but hire better, and got their Saturdays back. The system runs without their attention; they just get a weekly shortlist.

“They rebuilt our hiring mess in a couple of weeks and gave us our Saturdays back. Now it just quietly works.”
Ar. Syukri Noor · Managing Director, QALAM Architects
● Document ops Internal tool OCR + AI

From stacks of PDFs to a clean spreadsheet: seconds per document, zero keystrokes.

0
Manual data entry
Seconds
From drop to filed row
Auto
Archive & filing

The problem

Most businesses get a weekly flood of invoices, receipts, forms, purchase orders. Someone has to open each, copy data into a sheet, rename the file, archive it. It's slow and error-prone.

What we built

A watcher on an input folder. Documents are parsed (OCR + LLM), the fields that matter are extracted, a row is appended to Google Sheets with correct typing, and the source file is renamed and moved to an archive folder, searchable forever.

The result

What was half a day's work every week is now invisible. Drop a file in; look at the sheet. Anomalies get flagged for a 3-second human check.

● E-commerce / AI Hackathon build XGBoost · recsys

A live analytics dashboard that predicts cart abandonment before the customer leaves.

0.95+
ROC-AUC on held-out test set
100k+
Real orders analyzed
3-in-1
Tools unified

The problem

Stores lose revenue to cart abandonment every day, and usually they find out after the sale's already gone. By then it's too late to win it back.

What we built

A dashboard trained on 100,000+ real orders that flags carts likely to abandon in real time, recommends products tuned to the individual, and gives operators a revenue view with purchase heatmaps and regional breakdowns.

The result

A single tool an operator can use to do something about abandonment in-session, not just report it after the fact. Built in a weekend.

Your industry is probably on our list

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