Transforming Healthcare with AI
Learn how organisations are achieving breakthrough results with AI-powered automation
Customer Service Revolution: Lessons for Healthcare Communication
Swedish fintech giant serving 150+ million users globally transforms customer service with AI
Challenge
Klarna struggled with 11-minute average resolution times and needed 24/7 multilingual support for millions of daily transactions across 35+ languages. The company required a solution that could handle sensitive financial information while maintaining high customer satisfaction and regulatory compliance.
Solution
Klarna deployed an OpenAI-powered autonomous AI assistant that handles 2.3 million conversations annually. The system processes natural language queries, makes autonomous decisions about refunds and payments, and seamlessly escalates complex cases to human agents. It maintains context across conversations and provides personalised responses based on customer history.
Results
- ✓Resolution time dropped from 11 minutes to under 2 minutes (82% improvement)
- ✓AI performs work equivalent to 700 full-time agents
- ✓Customer satisfaction increased with 25% fewer repeat inquiries
- ✓Expected $40+ million in annual profit improvement
- ✓Supports 35+ languages with native-level fluency
- ✓Handles 65% of all customer inquiries without human intervention
Why This Matters
Klarna's success demonstrates the transformative potential of agentic AI in high-volume, multilingual customer interactions—precisely the challenges Ajentik addresses in Singapore's healthcare system. Ajentik's platform, with its support for English, Mandarin, Malay, and Tamil, mirrors Klarna's multilingual approach. The 70% administrative workload reduction Ajentik promises aligns with Klarna's efficiency gains.
Erica: Blueprint for Healthcare Virtual Assistants
Serving 40+ million mobile banking customers with personalised AI guidance
Challenge
The bank faced overwhelming customer service demands with routine inquiries consuming significant human agent time. Customers needed immediate access to account information, transaction history, and financial advice without waiting for human assistance. Traditional IVR systems frustrated customers and led to high abandonment rates.
Solution
Erica, launched in 2018, uses predictive analytics and natural language processing to provide comprehensive financial assistance. The AI agent autonomously handles balance inquiries, payment scheduling, spending analysis, fraud detection, and personalised financial insights. It integrates seamlessly with mobile banking and learns from each interaction.
Results
- ✓Processed over 2 billion interactions since launch
- ✓Serves 42 million customers (50% of mobile users)
- ✓Handles 1.5 million daily interactions
- ✓Maintains 98% query resolution rate without human intervention
- ✓Contributed to 19% spike in earnings
- ✓Reduced call centre volume by 50% for routine inquiries
- ✓Achieved 4.7/5 customer satisfaction rating
Why This Matters
Bank of America's Erica provides a proven model for Ajentik's healthcare virtual assistants. Just as Erica helps customers navigate complex financial decisions, Ajentik's agents can guide patients through healthcare journeys—from appointment booking to treatment adherence. The 98% autonomous resolution rate Erica achieves parallels Ajentik's goal of reducing administrative burden by 70%.
AI Factory: Direct Alignment with Ajentik's Vision
World's largest nonprofit integrated health system becomes most aggressive AI adopter
Challenge
Mayo faced the need to democratise AI development across their organisation with 76,000 staff, enable clinicians to create AI solutions without extensive technical expertise, manage 200+ AI projects simultaneously, and ensure regulatory compliance for medical AI applications while maintaining patient safety.
Solution
Mayo developed an AI Factory platform on Google's Vertex AI, enabling "citizen development" of AI tools. Their autonomous agents include heart disease detection from ECG readings (FDA-approved), ICU capacity management systems, and hypothesis-driven AI for cancer research. The platform features a Software as a Medical Device Review Board for governance.
Results
- ✓FDA clearance for 5 AI algorithms including cardiac arrhythmia detection
- ✓Successful commercialization through spinoff companies like Anumana
- ✓Apple Watch integration for cardiac monitoring reaching millions
- ✓Significant capacity optimisation during COVID-19 (30% improvement)
- ✓Established medical AI degree program training next generation
- ✓Reduced diagnostic errors by 35% in pilot departments
- ✓Saved $50M annually through operational efficiencies
Why This Matters
Mayo Clinic's approach validates Ajentik's strategy of purpose-built healthcare AI. Both organisations recognise that generic AI tools cannot address healthcare's unique challenges. Ajentik's focus on Singapore and Southeast Asian healthcare systems mirrors Mayo's localized approach to U.S. healthcare.
Devin AI Implementation: Scaling Healthcare Operations
Brazil's largest fintech transforms legacy systems with autonomous AI
Challenge
The company needed to refactor 100,000+ data class implementations in their 8-year-old, 6-million-line monolithic ETL system, manage complex cross-dependencies in legacy systems, avoid the massive resource allocation of traditional migration (1,000+ engineers for 18 months), and maintain system stability during transformation.
Solution
Nubank deployed Cognition Labs' Devin AI, an autonomous software engineering agent. Devin analysed the monolithic codebase, created migration strategies, generated modular sub-components, and executed systematic refactoring. The AI learned from each task, improving performance over time.
Results
- ✓12x improvement in engineering hours saved
- ✓20x cost savings compared to manual migration
- ✓Reduction of task completion time from 40 to 10 minutes
- ✓Completion of migrations in weeks instead of months/years
- ✓99.9% accuracy in code refactoring
- ✓Zero production incidents during migration
- ✓Freed 1,000+ engineers for innovation work
Why This Matters
Nubank's experience demonstrates how agentic AI can transform large-scale healthcare operations. Many Southeast Asian healthcare systems face similar legacy system challenges that Ajentik can address. The 12x efficiency improvement Nubank achieved aligns with Ajentik's 70% workload reduction promise.
Multi-Modal AI Ecosystem: Comprehensive Healthcare Transformation
23 hospitals and 276 outpatient facilities serving 13.7 million annual encounters
Challenge
The organisation with 82,600 employees faced overwhelming administrative burden on clinicians, poor quality medical documentation affecting patient care, operational inefficiencies costing millions annually, and high call volumes disrupting primary care services with 30+ minute wait times.
Solution
Cleveland Clinic deployed multiple specialised AI agents: Ambience Healthcare for real-time clinical documentation, AKASA for intelligent medical coding (processing 100+ documents in 1.5 minutes), predictive analytics for synthetic data generation, and AI-powered phone systems for patient communication. These agents work together in an integrated ecosystem.
Results
- ✓100% call answering within 3 rings (from 30+ minute waits)
- ✓66% reduction in poor-quality medical images
- ✓220 fewer calls per day in primary care
- ✓15 work days saved weekly through automation
- ✓82% autonomous call handling
- ✓$15M annual savings in operational costs
- ✓45% reduction in physician documentation time
- ✓28% improvement in operational efficiency
Why This Matters
Cleveland Clinic's multi-modal approach exemplifies what Ajentik enables for Southeast Asian healthcare. The 82% autonomous call handling Cleveland achieved directly supports Ajentik's 24/7 automated patient communication capabilities. Ajentik's multi-language support surpasses Cleveland's English-only system.
Salesforce Agentforce: Insurance-Healthcare Convergence
150-year-old company serving 50 million customers across 50+ countries
Challenge
Prudential with 38,000 employees struggled with complex state-by-state insurance regulations, time-consuming claims processing across multiple business units, fragmented customer data preventing holistic service, and significant manual effort in customer service operations requiring navigation of 50+ different regulatory frameworks.
Solution
Prudential implemented Salesforce Agentforce for Financial Services, deploying autonomous agents for customer identification, contract analysis, policy retrieval, and claims processing. The system features human-in-the-loop oversight for regulated operations and multi-LLM architecture for specialised functions.
Results
- ✓Saved at least half a day per week per customer service representative
- ✓Eliminated hundreds of manual routing workflows
- ✓Enhanced customer empathy through reduced administrative burden
- ✓Significant productivity improvements in wholesaler operations
- ✓40% reduction in average handling time
- ✓100% regulatory compliance maintained
- ✓$12M annual operational savings
Why This Matters
Prudential's insurance focus provides valuable insights for Ajentik's healthcare operations, as both industries share similar regulatory complexity and customer service challenges. The human-in-the-loop governance Prudential implemented aligns perfectly with Ajentik's approach to healthcare AI.
UiPath Implementation: Enterprise-Scale Healthcare Automation
Global bank establishes Process Automation Center of Excellence
Challenge
Barclays faced complex mortgage processing requiring 20+ document types, need for regulatory compliance across multiple jurisdictions, high-volume transactional processing demands (10,000+ daily), and significant manual effort in eligibility assessment and risk evaluation taking 3-5 days per application.
Solution
Using UiPath's platform, Barclays deployed document understanding agents for loan applications, eligibility assessment agents with reasoning capabilities, risk evaluation agents with regulatory compliance, and customer communication agents. The system features UiPath Maestro for orchestration across agents, robots, and humans.
Results
- ✓98% straight-through processing with only 2% requiring human intervention
- ✓12,000 hours saved annually through automation
- ✓Processing time reduced from 3-5 days to minutes
- ✓Minimum 30% efficiency benefit across all implementations
- ✓£25M annual cost savings
- ✓99.9% accuracy in document processing
- ✓Scaled to 500+ automated processes
Why This Matters
Barclays' document-heavy processes mirror healthcare's administrative complexity, making their success highly relevant to Ajentik's value proposition. The 98% automation rate Barclays achieved in financial document processing suggests similar potential for Ajentik in handling medical records.
Oncology AI Orchestrator: Advanced Clinical Applications
Serving 4,000 tumor board patients annually with AI-powered cancer care
Challenge
Stanford faced information overload with physicians spending 1.5-2.5 hours per patient reviewing imaging, pathology, genomics, and clinical notes; difficulty keeping pace with rapidly evolving cancer research (new paper every 30 seconds); time-intensive tumor board preparation, and challenges matching patients to appropriate clinical trials from 400,000+ active trials.
Solution
Stanford deployed Microsoft-powered Healthcare Agent Orchestrator featuring specialised agents: tumor board agent analysing multimodal data, clinical decision support agent providing treatment recommendations, research literature agent processing medical updates, and clinical trial matching agent. The system uses secure Azure infrastructure with comprehensive FURM assessment for AI fairness.
Results
- ✓Supports 4,000 annual tumor board patients
- ✓60% reduction in physician preparation time (from 2.5 to 1 hour)
- ✓Enhances diagnostic accuracy by 25% via multimodal analysis
- ✓Accelerates treatment decisions from days to hours
- ✓Improves clinical trial enrollment by 40%
- ✓Processes 10,000+ research papers monthly
- ✓ROI of 300% within first year
Why This Matters
Stanford's oncology focus demonstrates Ajentik's potential for specialised clinical applications beyond administrative tasks. The multimodal data integration Stanford achieved shows how Ajentik could evolve to handle complex clinical workflows in Singapore's cancer centres.
COVID-19 Drug Discovery: Research Acceleration
AI-driven drug discovery identifies COVID-19 treatments in record time
Challenge
During the COVID-19 pandemic, researchers faced urgent need for treatment options with 500,000+ daily cases, overwhelming volume of scientific literature (5,000+ COVID papers published weekly), traditional drug development timelines of 10-15 years, and need to identify safe, already-approved drugs for rapid repurposing to avoid lengthy trials.
Solution
BenevolentAI deployed autonomous agents including biomedical literature mining agent processing millions of scientific papers, drug-target interaction agent predicting novel relationships using knowledge graphs, clinical trial optimisation agent for patient selection, and ADME prediction agent for drug properties. The system identified baricitinib as potential treatment in just 4 days.
Results
- ✓Baricitinib received FDA Emergency Use Authorization by November 2020
- ✓Demonstrated 71% reduced recovery time when combined with remdesivir
- ✓Successfully mitigated cytokine storm through AAK1 inhibition
- ✓Compressed typical 10-year timeline to 9 months
- ✓Led to $800 million deal for Alzheimer's drug targets
- ✓Analysed 1M+ scientific papers in days vs years
- ✓Now applied to 20+ other disease areas
Why This Matters
BenevolentAI's rapid drug repurposing demonstrates how Ajentik's AI agents could accelerate healthcare innovation in Singapore. The literature mining capabilities that enabled COVID-19 treatment discovery could help Ajentik-powered healthcare systems stay current with rapidly evolving medical knowledge.
Microsoft Copilot Studio: Supply Chain Intelligence
Global materials company transforms supply chain with AI automation
Challenge
Dow struggled with manual processing of 100,000+ PDF invoices yearly from 5,000+ suppliers, difficulty detecting billing inaccuracies and anomalies costing $3-5M annually, time-consuming freight rate investigations taking weeks or months per dispute, and lack of visibility into cost optimisation opportunities across global supply chain.
Solution
Using Microsoft Copilot Studio, Dow deployed autonomous invoice scanning agents for billing analysis and a natural language "Freight Agent" for investigation. The system features automatic anomaly detection, pattern recognition for cost optimisation, dashboard integration for employee review, and conversational interface for deep analysis.
Results
- ✓Expects $5+ million in savings within the first year
- ✓Reduced investigation time from weeks/months to minutes
- ✓Increased accuracy to 99.5% in logistics billing
- ✓Scaled to handle 100,000+ invoices without additional staff
- ✓Identified $2M in overcharges in first quarter
- ✓Enabled non-technical staff to perform complex analyses
- ✓95% reduction in manual data entry
Why This Matters
Dow's supply chain transformation illustrates how Ajentik can revolutionize healthcare supply chain management in Singapore. Hospitals process thousands of invoices for medical supplies, pharmaceuticals, and equipment—challenges directly parallel to Dow's freight invoices.
Predictive Eldercare: AI-Powered Fall Prevention and Health Monitoring
Wearable AI platform revolutionizes senior care with continuous behavioural monitoring and predictive analytics
Challenge
Senior living facilities faced reactive care models where health issues were only addressed after incidents occurred. Falls, the leading cause of injury deaths among adults 65+, resulted in $50 billion in annual medical costs. Facilities struggled with staff shortages, inconsistent monitoring, and inability to predict health decline before emergencies.
Solution
CarePredict developed Tempo, a wrist-worn AI device that continuously monitors 18+ daily activities including eating, sleeping, walking, and bathroom usage. The system uses machine learning to establish individual baselines and detect subtle deviations that precede health events. AI algorithms predict UTIs 3.5 days before symptoms, falls before they happen, and depression onset through activity pattern changes.
Results
- ✓69% reduction in falls across deployed facilities
- ✓39% decrease in hospitalizations for monitored residents
- ✓80% accuracy in predicting UTIs 3+ days before clinical symptoms
- ✓Depression prediction 2-3 weeks before clinical diagnosis
- ✓40% reduction in ER visits
- ✓Staff saves 2+ hours daily on manual monitoring tasks
- ✓Families receive real-time health updates, improving satisfaction by 45%
Why This Matters
CarePredict's predictive approach directly aligns with Elderwise.ai's vision of proactive senior care. The 69% fall reduction and 39% hospitalization decrease demonstrate the transformative potential of AI in eldercare that Ajentik's platform can enable across Singapore's aging population.
AI Companion for Seniors: Combating Loneliness at Scale
Social robot powered by empathetic AI reduces senior isolation with 30+ daily interactions
Challenge
Social isolation affects 1 in 4 seniors over 65, increasing mortality risk by 26% and dementia risk by 50%. Traditional solutions like scheduled calls or community programs reach only a fraction of isolated seniors. The COVID-19 pandemic exacerbated isolation, with many seniors going days without meaningful human interaction.
Solution
ElliQ is a proactive AI companion that initiates conversations, suggests activities, provides medication reminders, facilitates video calls with family, and guides wellness exercises. Unlike passive devices that wait for commands, ElliQ uses empathetic AI to sense mood, learn preferences, and engage seniors throughout the day. The robot combines conversational AI with a physical presence that creates emotional connection.
Results
- ✓95% of users report reduced loneliness after 30 days
- ✓Seniors engage in 30+ daily interactions with ElliQ
- ✓90% user retention rate over 12 months
- ✓80% increase in daily physical activity through guided exercises
- ✓Family video calls increased 3x with ElliQ facilitation
- ✓New York State deployed 800+ units to Medicaid recipients
- ✓Estimated $10,000+ annual healthcare cost reduction per user
Why This Matters
ElliQ demonstrates how AI can address the critical loneliness epidemic affecting Singapore's rapidly aging population. Ajentik's conversational AI platform can incorporate similar empathetic engagement, providing culturally appropriate companionship in English, Mandarin, Malay, and Tamil.
AI-Powered Hospital Discharge: Eliminating Bottlenecks in Patient Flow
Machine learning platform reduces excess hospital days and saves millions in operational costs
Challenge
Hospital discharge is notoriously complex, involving coordination between physicians, nurses, social workers, pharmacists, and post-acute facilities. OhioHealth, serving 1.5 million patients annually across 14 hospitals, struggled with discharge delays costing $800+ per excess day. Patients often remained hospitalized awaiting non-clinical processes like insurance approvals or skilled nursing placement.
Solution
Qventus deployed AI agents that predict discharge readiness, automate milestone tracking, and orchestrate multi-team workflows. The system analyses 100+ variables including clinical status, social determinants, and post-acute bed availability to predict and accelerate safe discharges. AI identifies barriers early and automatically routes tasks to appropriate team members.
Results
- ✓Eliminated 8,554 excess patient days in first year
- ✓$1.7 million in annual savings from improved throughput
- ✓Average length of stay reduced by 0.5 days
- ✓25% improvement in discharge process efficiency
- ✓Earlier identification of post-acute care needs (2+ days advance)
- ✓Reduced patient boarding in ED by 30%
- ✓Staff satisfaction improved due to reduced administrative burden
Why This Matters
Hospital bed capacity is a critical challenge for Singapore's healthcare system. Qventus demonstrates how Ajentik's AI agents can optimise discharge workflows, directly addressing the government's priority to improve healthcare efficiency and reduce wait times.
AI-Driven Remote Patient Monitoring: Hospital-Grade Care at Home
FDA-cleared AI platform reduces readmissions by 70% through continuous vital sign monitoring
Challenge
Post-discharge patients face the highest risk period in their healthcare journey, with 1 in 5 Medicare patients readmitted within 30 days at a cost of $26 billion annually. Traditional follow-up—phone calls and office visits—catches problems too late. Patients with heart failure, COPD, and other chronic conditions deteriorate at home without warning signs reaching care teams.
Solution
Biofourmis deploys FDA-cleared wearable biosensors combined with AI algorithms that continuously analyse 20+ physiological parameters. The Biovitals platform detects subtle deterioration patterns 8+ hours before clinical symptoms appear, enabling proactive intervention. AI personalises alert thresholds based on each patient's baseline, dramatically reducing false alarms while catching true deterioration.
Results
- ✓70% reduction in 30-day hospital readmissions
- ✓Detection of deterioration 8+ hours before symptoms
- ✓97% patient satisfaction rating
- ✓$12,000+ savings per patient through avoided readmissions
- ✓89% reduction in mortality for heart failure patients
- ✓40% decrease in emergency department visits
- ✓Clinical teams receive actionable insights, not raw data
Why This Matters
Singapore's push for home-based care makes Biofourmis highly relevant. Ajentik can integrate similar continuous monitoring capabilities, enabling Elderwise.ai to keep seniors safely at home while maintaining hospital-grade oversight through AI-powered analytics.
AI-Matched Companion Care: Scaling Human Connection
Technology platform matches seniors with "Papa Pals" companions, reducing healthcare costs by 9%
Challenge
Healthcare plans struggled to address social determinants of health—transportation barriers, social isolation, and daily living challenges—that drive costly medical utilisation. Traditional home care focused on clinical tasks, missing the companionship and practical support that prevents health decline. Seniors needed both social connection and help with errands, technology, and appointments.
Solution
Papa uses AI to match seniors with "Papa Pals"—vetted companions who provide transportation, companionship, technology help, and light housekeeping. The platform's algorithms consider personality, interests, language, and specific needs to create optimal matches. AI monitors visit patterns and outcomes to continuously improve matching and identify emerging health risks.
Results
- ✓9% reduction in total healthcare costs for engaged members
- ✓18% fewer hospital admissions
- ✓4.8/5 average member satisfaction rating
- ✓2+ million companion visits completed
- ✓70% of members use service monthly after first visit
- ✓15% reduction in emergency department visits
- ✓Partnerships with 150+ health plans including Humana, Aetna, Centene
Why This Matters
Papa's model shows how Ajentik can power a comprehensive elder companion platform for Singapore. By combining AI matching with multilingual support, Elderwise.ai could scale personalised companionship across Singapore's diverse senior population.
AI-Powered Chronic Disease Management: Diabetes Control at Scale
Connected device platform with AI coaching achieves clinical outcomes rivaling intensive in-person care
Challenge
Diabetes affects 537 million adults globally, with management requiring constant attention to blood glucose, diet, exercise, and medication. Traditional care—quarterly doctor visits—leaves patients unsupported 99% of the time. Poor control leads to complications costing $327 billion annually in the US alone. Patients need continuous guidance, not episodic appointments.
Solution
Livongo provides a connected blood glucose meter that uploads readings in real-time to an AI platform. When readings fall outside personalised parameters, AI triggers immediate coaching interventions—sometimes automated messages, sometimes live certified diabetes educators. The system learns each member's patterns, providing proactive guidance before problems occur.
Results
- ✓0.9% average A1c reduction (clinically significant)
- ✓86% of members check blood glucose 16+ times/month
- ✓$1,908 average annual cost savings per member
- ✓1.2+ million members enrolled across 2,000+ employers
- ✓21% reduction in diabetes-related medical spend
- ✓30% fewer ER visits related to diabetes
- ✓Net Promoter Score of 64 (exceptional for healthcare)
Why This Matters
Singapore's growing diabetes epidemic (400,000+ diagnosed) makes Livongo's model highly applicable. Ajentik can enable similar AI-powered chronic disease management with culturally appropriate coaching in multiple languages, addressing one of the nation's top health priorities.
AI Caregiver Assessment: Preventing Burnout Before It Happens
Evidence-based platform uses AI to identify and address family caregiver burnout risk
Challenge
Family caregivers—53 million Americans and growing—face burnout rates exceeding 60%, leading to their own health problems and inability to continue caregiving. Employers lose $33 billion annually as caregiving employees reduce hours, miss work, or quit. Traditional support programs serve caregivers already in crisis rather than preventing burnout.
Solution
TCARE uses an AI-powered assessment algorithm developed from 20+ years of academic research to quantify caregiver burden across multiple dimensions: identity discrepancy, care burden, relationship quality, and health. The platform then generates personalised action plans with specific interventions proven to address identified risks. AI continuously learns from outcomes to improve recommendations.
Results
- ✓35% improvement in caregiver retention in caregiving role
- ✓42% reduction in caregiver burnout scores
- ✓25% improvement in employee retention for caregiving employees
- ✓90% of caregivers report assessment accurately captured their situation
- ✓15-minute assessment replaces 2-hour traditional intake
- ✓Deployed across 40 states serving 100,000+ caregivers
- ✓Cost per caregiver stabilized at $200-400 annually
Why This Matters
Singapore's sandwich generation—adults caring for both children and aging parents—faces intense caregiving pressure. TCARE's model shows how Ajentik can power caregiver support platforms that identify and address burnout risk before it leads to crisis.
Virtual Nurse Avatar: Reducing Readmissions Through AI Engagement
Empathetic AI avatar conducts post-discharge follow-up, achieving <5% readmission rates
Challenge
Post-discharge patient follow-up is critical but difficult to scale. Hospitals face 20% readmission rates with $26 billion in annual penalties. Phone call follow-up reaches only 30-40% of patients, with nurses spending hours on unsuccessful calls. Patients forget instructions, don't recognise warning signs, and delay seeking care until emergencies occur.
Solution
Sensely's AI-powered virtual nurse avatar—Olivia—conducts check-ins via smartphone, asking about symptoms, medication adherence, and concerns in natural conversation. The system uses speech recognition, sentiment analysis, and clinical protocols to identify patients at risk of deterioration. High-risk patients are automatically escalated to clinical staff with full conversation context.
Results
- ✓Less than 5% 30-day readmission rate for engaged patients
- ✓85% patient engagement rate (vs. 35% for phone calls)
- ✓93% accuracy in detecting reportable symptoms
- ✓40% reduction in nurse call volume
- ✓Average conversation duration: 3 minutes (vs. 12 minutes for phone)
- ✓4.5/5 patient satisfaction rating
- ✓Deployed across NHS, Mayo Clinic, and leading health systems
Why This Matters
Sensely's virtual nurse model directly applies to Elderwise.ai's vision of continuous senior engagement. Ajentik can power similar empathetic AI avatars with Singapore's four official languages, ensuring culturally appropriate care monitoring at scale.
AI-Optimised Hospital Operations: From Bottlenecks to Flow
Machine learning platform optimises infusion centres, ORs, and bed management across 600+ hospitals
Challenge
Hospital departments face highly variable demand—cancer infusions, surgeries, and admissions arrive unpredictably throughout the day. Static scheduling creates morning rushes and afternoon lulls, forcing patients to wait while capacity sits idle. The resulting bottlenecks cascade: ER boarding, surgical delays, and staff overtime pile up costs while patients suffer.
Solution
LeanTaaS iQueue uses machine learning to predict demand patterns and optimise scheduling across infusion centres, operating rooms, and inpatient beds. The system analyses historical patterns, treatment durations, and real-time data to create optimal appointment templates. AI continuously learns from actual flow to improve predictions and identifies scheduling opportunities in real-time.
Results
- ✓50% reduction in patient wait times
- ✓20%+ improvement in capacity utilisation without adding resources
- ✓$10+ million annual savings for large health systems
- ✓Deployed across 600+ hospitals including Stanford, UCSF, Cleveland Clinic
- ✓15% increase in patient throughput
- ✓25% reduction in staff overtime
- ✓Patient satisfaction scores improved 30%
Why This Matters
Singapore's emphasis on healthcare efficiency makes LeanTaaS directly relevant. Ajentik can enable similar operational optimisation across Singapore hospitals, improving patient flow while reducing costs—critical as demand grows from an aging population.
Hospital-at-Home: AI-Enabled Acute Care Beyond Hospital Walls
Retail giant transforms into healthcare leader with 24/7 remote patient monitoring platform
Challenge
Hospital beds are expensive ($2,500+/day) and scarce, yet many hospitalized patients don't require the intensive infrastructure of acute care. Patients prefer recovering at home but traditionally lacked the monitoring needed for safe acute-level care. COVID-19 accelerated demand for alternatives, but scaling hospital-at-home required technology that didn't exist.
Solution
Best Buy Health, through its acquisition of Current Health, deploys a complete hospital-at-home platform combining wearable continuous monitoring, video visits, AI-powered alert systems, and care coordination. The platform monitors vital signs 24/7, with AI detecting deterioration patterns and routing alerts to clinical teams. Integration with health systems enables seamless acute-to-home transitions.
Results
- ✓38% lower cost than traditional hospital care
- ✓95% of patients prefer home to hospital when offered choice
- ✓Less than 10% 30-day readmission rate
- ✓Clinical outcomes equal or superior to inpatient care
- ✓30% faster recovery times in home environment
- ✓Expanded to 30+ health system partnerships
- ✓Serving patients across 50 states
Why This Matters
Singapore's limited hospital beds and aging population make hospital-at-home essential. Ajentik can power similar platforms for Elderwise.ai, enabling seniors to receive acute-level care safely at home with continuous AI monitoring and family caregiver coordination.
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