Personalizing Health at Scale: How Al Borg Diagnostics Transformed Patient Care with HoopAI

AI Patient Assistant with Voice and Video Across 130+ Locations

At 7:42 AM on a Tuesday morning, a patient in Riyadh opens WhatsApp and types a simple question: "Do I need to fast before my cholesterol test?" Within seconds, she receives a detailed answer—not from a busy receptionist juggling phone lines, but from an AI assistant that already knows her appointment schedule, has read her previous lab results, and can explain medical requirements in clear, conversational Arabic.

This isn't a glimpse into the distant future. It's what happens every day at Al Borg Diagnostics, where artificial intelligence has become the invisible thread connecting 130+ locations, thousands of daily patient interactions, and a mission to make healthcare more accessible across Saudi Arabia.

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When scale becomes the problem

Al Borg Diagnostics operates one of Saudi Arabia's largest medical laboratory networks, serving both individual patients and corporate clients across the Kingdom. Their success created its own challenge: as they grew to over 130 locations, maintaining consistent, high-quality patient experiences became increasingly complex.

"We had teams at every branch answering the same questions hundreds of times a day," recalls Dr. Ranya Al-Faris, Head of Customer Experience at Al Borg Diagnostics. "Patients would wait for callbacks about test preparation. Information about packages lived in different systems. And our Google reviews were scattered across locations, so we couldn't see patterns or respond systematically."

The fragmentation showed up in subtle but meaningful ways. A patient might receive different advice about test preparation depending on which branch they called. Corporate clients managing employee health screenings had to coordinate with multiple locations separately. When someone uploaded lab results asking for interpretation, wait times could stretch to hours—or they'd get redirected to make an appointment just to understand their numbers.

For a healthcare organization where trust and timeliness matter deeply, these friction points weren't just operational inefficiencies. They were missed opportunities to support people during sensitive health moments.

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Reimagining healthcare conversations

The team at Al Borg knew they needed more than incremental improvements. They needed to fundamentally reimagine how they connected with patients across every touchpoint—while keeping clinicians central to the care experience.

"We weren't looking for a chatbot to deflect questions," Dr. Al-Faris explains. "We needed intelligent assistance that could handle complexity: understanding test requirements, reading uploaded lab reports, recommending appropriate packages, and knowing exactly when to bring in our medical staff."

Enter HoopAI—a platform designed specifically for this kind of sophisticated, multi-channel patient engagement.

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Building trust through understanding

The transformation started with something deceptively simple: giving every patient interaction context.

With HoopAI's unified profile system, the AI assistant immediately recognizes returning patients. It knows their appointment history, previous tests, and preferences. When someone asks about fasting requirements, the assistant doesn't just provide generic instructions—it references their specific scheduled test and can offer to reschedule if the timing doesn't work.

But the real breakthrough came with HoopAI's Content Agent and Knowledge Base capabilities. The system can actually read uploaded PDF lab results, interpret clinical ranges, and explain findings in patient-friendly language.

"Someone can literally send us their test results through WhatsApp, and the AI will help them understand what the numbers mean," says Dr. Al-Faris. "It follows our policies about what requires a consultation, what's routine, and what packages might be relevant for follow-up testing. And if anything looks concerning or ambiguous, it immediately routes to our medical team with full context."

This wasn't about replacing medical expertise—it was about extending it. The AI handled routine questions and explanations so clinical staff could focus on cases requiring professional judgment.

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Voice, video, and the human touch

Text-based chat was just the beginning. HoopAI's Service Agent handles voice calls with the same sophistication, understanding Arabic and English with natural language processing that feels genuinely conversational.

"Patients can literally call and speak to the AI like they're talking to a person," Dr. Al-Faris notes. "It understands their questions, can check appointment availability, explain test preparation, and even handle booking—all through natural voice conversation."

For more sensitive topics or complex explanations, the system supports video replies. A staff member can record a personalized video walking through lab results or explaining a health package, delivered through the same thread where the conversation started.

This multi-modal approach proved especially powerful for patient education. A customer wondering about their diabetes screening package receives not just text information, but access to brief educational videos, preparation checklists, and scheduling—all without leaving the conversation.

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Reputation at scale

One of the most unexpected transformations came from how Al Borg now manages their online reputation. With 130+ locations each generating Google reviews, feedback had become fragmented and difficult to action.

HoopAI's platform centralizes all reviews into a single dashboard with intelligent routing. Negative reviews automatically flag to the relevant location manager. Positive feedback highlights best practices to share across branches. Most importantly, the AI suggests response templates that maintain clinical accuracy and brand voice while allowing personalization.

"We went from scattered review management to having a complete picture across all our locations," says Dr. Al-Faris. "We can see patterns—maybe a specific location needs better signage, or certain tests consistently get questions about preparation. That insight drives real operational improvements."

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The machinery behind the magic

Making this level of sophistication feel effortless required careful orchestration across HoopAI's platform:

Marketing & Outreach: Using Campaigns and WhatsApp Marketing, teams share seasonal health packages, preventive care reminders, and educational content. Traffic flows naturally into conversations where the AI can answer questions and book appointments through Meeting Scheduler.

Sales & Conversion: The Customer Agent compares package options, surfaces preparation requirements, and guides decisions based on patient history and eligibility. When someone's ready to book, scheduling happens in the same thread—no app switching, no forms to fill out separately.

Commerce Integration: Staff use Payment Links and Invoices to collect deposits or settle balances directly in the conversation thread. Commerce Tools handle reconciliation automatically, removing administrative friction.

Service Excellence: The Service Agent maintains 24/7 availability across voice and chat, recognizes returning patients, and escalates appropriately based on conversation context and clinical protocols.

Operational Intelligence: Analytics in Hoop reveals patterns in question types, response times, conversion rates, and review sentiment across locations. User Management and Centralized Audit Log ensure compliance and security. Workflows automate routing for escalations and follow-ups.

"The AI handles calls, chats, and reviews so our teams can focus on care," Dr. Al-Faris summarizes. "Patients get answers immediately, and branch managers see the full picture."

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Partnership, not just platform

What set HoopAI apart wasn't just technical capability—it was the collaborative approach to implementation.

The onboarding process started with alignment on what success actually meant: faster response times, consistent patient guidance, and measurable improvements in satisfaction and efficiency. HoopAI's team helped map patient journeys for different scenarios—booking tests, following up on results, managing corporate screenings—and identified where AI could add value versus where human expertise remained essential.

Agent design went deep into Al Borg's specific needs. The Service and Customer Agents were trained on medical policies, consent requirements, package eligibility rules, and escalation paths. Safety guardrails ensured the AI never overstepped clinical boundaries. Arabic and English support was tuned for natural, regionally appropriate conversation.

But technical setup was only part of the equation. HoopAI provided playbooks, office hours, and role-based training to help Al Borg's teams adopt chat-first and voice-first workflows across 130+ locations. Change management mattered as much as technology.

"Weekly review sessions let us continuously improve," notes Dr. Al-Faris. "We tune prompts based on real conversations, add new package information, refine review response templates. It's an ongoing partnership, not a set-it-and-forget-it deployment."

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Transformation by the numbers—and beyond

Six months into implementation, the metrics tell a compelling story:

• 130+ locations now operate from one unified view with consistent policies and routing
• 24/7 voice AI coverage handles calls in Arabic and English with natural conversation
• Response time improvements across all channels as AI handles routine questions instantly
• Centralized review management surfaces patterns and enables systematic responses across branches
• File-aware intelligence reduces back-and-forth on lab result interpretation

But the real transformation shows up in moments that don't fit neatly into dashboard metrics:

A patient uploads concerning test results at 11 PM. The AI recognizes values outside normal ranges, flags the case as urgent, and ensures a clinician reviews it first thing in the morning—with full context already assembled.

A corporate client managing employee health screenings for 500 people coordinates the entire program through a single WhatsApp thread, with the AI handling scheduling logistics across multiple locations while staff focus on results review and follow-up care.

A first-time visitor overwhelmed by package options receives personalized recommendations based on age, gender, and stated health goals—then books an appointment, receives a preparation checklist, and gets reminder messages, all without a single phone call.

"Patients receive precise, timely guidance," Dr. Al-Faris reflects. "Our staff focus on complex cases instead of repeating basic information. And managers finally see conversation trends and review patterns across all locations—insight that directly improves operations."

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The patient journey, reimagined

Here's how a typical interaction now flows:

Step 1: A visitor opens chat on the website or calls the support line. The AI immediately identifies whether they're a returning patient and understands their intent.

Step 2: The assistant answers questions, explains options, or suggests the next best action—whether that's booking an appointment, uploading previous results, or connecting with a specialist.

Step 3: Meeting Scheduler handles appointment booking with real-time availability across nearby locations.

Step 4: If deposits or payments are needed, Payment Links arrive in the same thread—no redirects, no separate checkout process.

Step 5: Post-visit, automated surveys and review requests keep feedback flowing, while the AI monitors sentiment and routes concerns appropriately.

Step 6: Analytics in Hoop reveals patterns in common questions, conversion rates, and satisfaction scores—informing package design, content updates, and staffing across regions.

From the patient's perspective, it feels seamless: one conversation thread that understands context, moves things forward, and knows when to bring in human expertise.

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Looking ahead

Al Borg Diagnostics isn't finished. They're already exploring proactive health check-ins—AI-initiated conversations that remind patients about recommended screenings based on their history and age. New specialty packages are being integrated into the knowledge base. And deeper analytics on review themes will guide training programs and operational improvements across regions.

"We've built a foundation for truly personalized healthcare at scale," says Dr. Al-Faris. "The AI learns from every interaction, our content stays current across all touchpoints, and our teams work from one source of truth. That's what lets us grow without losing the personal touch that matters in healthcare."

The vision is ambitious but grounded: a healthcare experience where getting answers, booking tests, understanding results, and receiving care coordination feels effortless—because intelligent systems handle complexity in the background while keeping human expertise at the center when it matters most.

For Al Borg Diagnostics, artificial intelligence isn't replacing the human element of healthcare. It's making it possible to deliver that human element more consistently, more personally, and at a scale that would be impossible through manual effort alone.