Selected work
Engineering · MENA · 2026
What we shipped,and what changed.
Every engagement below carries the numbers it moved — before, after, and how long it took. No composite clients, no metrics we can’t stand behind.
Time compressed
25 min → 45 sec · 6 h → 4 s · 3.5 days → 10 h
Quality raised
Precision 0.61 → 0.88 · Failures 14% → <1%
Systems consolidated
11 tools → 1 workspace · Duplicated infra → shared core
Bilingual Knowledge-Graph Platform for 200 Years of Gulf Archival History
Thirty-three PDF volumes of 1622–1810 Gulf history — 1.94M words over 5,657 pages — existed only as unsearchable prose, alongside a parallel Arabic edition whose text layer was unrecoverable. No structure, no entities, no map, no way to cite a passage.
- 0 → 1.94M words
- Source text captured from 33 volumes
- 524 → 3,985
- Arabic edition records
Production-Grade Multi-Product AI Backend on a Shared Core
Two AI products (one retrieval-heavy, one vision-heavy) were being built as separate backends. Duplicated auth, duplicated RBAC, duplicated observability, and diverging fast.
- 0 → 7
- Shared infra components
- Weeks → Days
- Time to add new product surface
RAG Assistant for MENA Regulatory Compliance
Advisory staff were answering the same 40-50 recurring UAE corporate-tax questions by hand, each pulling 2-3 regulatory PDFs. Turnaround averaged 6 hours and junior staff frequently missed cross-references between VAT and CT documents.
- 6h → under 4s
- Average time to first accurate answer, end-to-end
- Precision@5: 0.61 → 0.88
- Composite embeddings outperformed pure-text by ~27 points
Visual Product-Discovery Assistant for Home-Furnishing Retail
Customers shared Pinterest-style inspiration photos over WhatsApp and expected matching SKUs in return. Manual matching cost 20-30 minutes per enquiry; most customers dropped off before the retailer could respond.
- 25 minutes → 45 seconds
- Enquiry-to-shortlist time
- 0% → 58%
- Enquiries resolved without staff
Editorial Workflow Platform for Multi-Volume Document Production
Editorial ops was running 11 separate tools to move a document from intake to edit to merge to format to export. Turnaround was unpredictable and any one tool outage stalled the whole pipeline.
- 11 → 1
- Tools in editorial pipeline
- 3.5 days → 10 hours
- Median doc turnaround
Research-Grade Linguistic Analysis Platform
A corpus of 676 Arabic doubled-verb conjugations needed to be explorable by researchers and students alike. Existing academic tools required CSV wrangling and produced static PNGs that nobody could interact with.
- Days → Minutes
- Time to explore corpus
- Automated
- Feature discovery method
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