AI stack live in 14 days. 4,200 tasks automated monthly. $180K estimated annual savings.
Al Yousif Group is a Saudi Arabia-based multi-vertical conglomerate operating across automotive, real estate, and retail. Leadership needed an AI implementation partner who could move fast, deploy across departments, and show ROI — not deliver a roadmap presentation.
Manual processes across 6 departments — and no internal expertise to change them
Al Yousif Group's operations ran on a patchwork of email queues, manual spreadsheets, and ad-hoc document workflows. Finance reporting took 5 days per cycle. Procurement requests sat in email queues for 3–4 days. HR was manually screening CVs across three divisions. Sales proposals were written from scratch each time.
Leadership had explored AI tools independently but had no internal capability to evaluate, select, configure, or integrate them securely. They were aligned on Vision 2030 and committed to AI adoption — but needed an external implementation partner to own the deployment from tool selection through to adoption. The mandate: all tools live within 2 weeks, measurable results within 30 days.
Process audit first. Tool selection second. Deployment third. No skipping steps.
Days 1–3: Audit
- Workflow mapping across all 6 departments
- 40+ existing processes documented
- 12 AI-automation candidates identified
- Tool stack selected based on tech compatibility and security requirements
Days 4–11: Build
- Claude Team + ChatGPT Enterprise configured with company-specific instructions
- Notion AI workspace built mirroring 6-division org chart
- 7 custom automation workflows built in Zapier + Make.com
- All workflows tested against live data before training
Days 12–14: Train & Launch
- Half-day session per department — their tools, their workflows
- No generic AI overview: Finance saw the reporting pipeline, HR saw the CV screener
- Full stack live on Day 14
- 30-day post-deployment support included
4,200 tasks automated per month. Finance reporting cut by 70%. Stack paid back in under 90 days.
Operations — Before AI Stack
- Finance reports: 5-day cycle, manual data assembly
- Procurement RFQ: 2–3 days in email queues
- CV screening: 3+ hours per 100 applicants
- Sales proposals: 4–6 hours each, written from scratch
- CS responses: manually written, inconsistent tone
- No central knowledge base — information siloed by division
Operations — After AI Stack (Day 28)
- Finance reports: 1.5-day cycle — 70% faster
- Procurement RFQ: AI-generated in 15 min
- CV screening: Claude shortlists 100 CVs in 55 min
- Sales proposals: AI-drafted in 35 min with CRM data
- CS responses: template + AI personalisation, consistent brand voice
- Notion AI knowledge base live across all 6 departments
Process Audit & Tool Selection
Full workflow audit across all 6 departments. 40+ processes documented. 12 automation candidates ranked by impact and complexity. Tool stack selected: Claude Team, ChatGPT Enterprise, Perplexity Pro, Notion AI, Zapier, Make.com — chosen based on compatibility with existing systems, security requirements, and Vision 2030 compliance considerations.
Tool Configuration & System Prompt Engineering
Claude Team and ChatGPT Enterprise configured with Al Yousif Group-specific system prompts — brand voice, document standards, escalation rules, and data handling parameters. Notion AI workspace built to mirror the company's 6-division org structure. First 3 Zapier automation workflows built and tested.
Custom Automation Build — All 7 Workflows
Remaining 4 workflows built: finance report assembly (Make.com + Claude), CV screening pipeline (Make.com + Claude API), sales proposal drafter (Zapier + ChatGPT + CRM integration), onboarding document generator (Make.com + Claude). All tested against live production data before training day.
Department-by-Department Training
Half-day sessions with each department head and their teams. Finance saw the reporting pipeline live. HR ran the CV screener against a real job opening. Sales drafted a live proposal using their CRM data. Procurement generated an RFQ in 15 minutes. No generic demo — every team used their own tools on their own data.
Full Stack Live
All 6 tools and 7 automation workflows operational across all 6 departments. Densight Labs provided 30 days of post-deployment support: weekly check-in calls, a dedicated Slack channel, and one revision round on any automation that needed tuning based on real-world usage in the first two weeks.
"Al Yousif Group didn't want a consultant's PowerPoint. They wanted an implementation partner who would stay until the tools were live and the team was using them. That's what AI Stack Setup is built for — not a handoff, a handover."
— Numan Ahmad, Founder & CEO, Densight LabsReady to deploy AI across your organisation?
This is what AI implementation looks like when it's done properly — process-first, tool-second, live in 14 days. Book a discovery call and we'll scope what's possible for your departments.