Case Studies: Enterprise AI Automation & Web Engineering Results

Six engagements across Riyadh and London, spanning AI automation, bilingual support, and enterprise web builds, each with the challenge, the approach, and the measurable result. Real technical depth, not a highlight reel.

Logistics warehouse with automation systems
AI AutomationRiyadh, KSA

Automating a Riyadh logistics giant

Deployed custom LLM workflows for a Tier-1 GCC logistics provider, eliminating manual cross-border documentation across 6 countries.

42%

Less manual work

3.2×

Faster operations

Custom LLMAI PipelinesPythonAzure
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Business team in modern office analyzing data
Lead GenerationLondon, UK

310% more leads for a London fintech

Built an autonomous multi-agent lead pipeline for a City of London firm with AI qualification across 14 data sources running 24/7.

310%

More qualified leads

£2.1M

Pipeline generated

Multi-Agent AILead ScrapingNode.jsHubSpot
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Customer support team with headset working
Multilingual AIRiyadh & London

Arabic & English AI support engine

Fine-tuned bilingual agents handling 12,000+ monthly tickets across Arabic and English with full cultural and compliance awareness.

89%

Auto-resolved

4.9★

Satisfaction score

Fine-Tuned LLMsArabic NLPCortex AIAWS
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Luxury e-commerce shopping interface
Web EngineeringLondon, UK

100/100 Lighthouse for a luxury retailer

Redesigned a luxury retail group's e-commerce with Next.js headless. Lighthouse 34→100, load time 4s→0.4s.

100

Lighthouse score

0.4s

Load time

Next.js 15Headless CMSEdge CDNOmniCommerce
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Modern residential and commercial buildings in a city skyline
Operations AutomationRiyadh, KSA

Automating leasing operations for a Riyadh property group

Deployed an AI-driven leasing and maintenance-request pipeline for a major KSA real estate portfolio, cutting response time from days to minutes across 40+ properties.

76%

Faster response time

1,200+

Units under management

Custom LLMWorkflow AutomationPythonTwilio
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Modern corporate office building exterior
Web EngineeringLondon, UK

Enterprise React rebuild for a London professional services firm

Migrated a legacy client portal to Next.js for a City of London firm, cutting load times and passing strict compliance and security review.

2.1s

Load time (from 6.8s)

99.9%

Uptime SLA

Next.js 15TypeScriptSSO/SAMLAWS
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