AI-Powered Housekeeping Quality Check for Hotels
Executive Summary
Our customer, a leading AI solutions provider, partnered with QloudX to develop and deploy an AI-powered Housekeeping Quality Check solution for one of their hospitality clients. The goal was to revolutionize hotel room quality inspections through the use of Artificial Intelligence, Computer Vision, and scalable AWS cloud technologies.
Leveraging QloudX’s expertise in AWS architecture, cloud automation, and enterprise-scale deployment, the project successfully delivered a cost-effective, scalable, and intelligent solution that enhances operational efficiency and ensures consistent room quality across all hotel properties.
The Challenge
Housekeeping supervisors traditionally perform manual room inspections post-cleaning, using checklists to evaluate cleanliness and readiness. As room volume increased, this model became increasingly unsustainable due to:
About Our Customer
Our customer is an AI solutions company focused on helping enterprises harness the power of large language models and automation to improve operational efficiency. With expertise across Generative AI, Machine Learning, and Cloud technologies, they enable businesses to modernize processes and deliver intelligent, data-driven outcomes. Their partnership with QloudX reflects a shared commitment to driving innovation through practical AI applications that deliver measurable value.
- Limited scalability — supervisors could only inspect a fraction of cleaned rooms.
- Subjective evaluations — room readiness assessments varied across properties and inspectors.
- Inconsistent documentation — lack of photographic records for verification or training.
- Delayed room availability — waiting for manual approvals caused operational bottlenecks.
- Inability to track trends — no central dashboard to identify recurring issues or performance by staff.
The customer needed a modern, scalable solution that could automate visual inspections while ensuring brand-aligned quality.
AWS lays the foundation
To support real-time processing, scalability across multiple hotel properties, and secure image handling, QloudX deployed the solution on AWS using a fully managed, cloud-native architecture.
The AWS infrastructure allowed seamless ingestion, processing, and analysis of high-resolution images, while ensuring low latency and strong governance. The solution was designed with multi-tenancy in mind, supporting multiple properties and user roles (staff, supervisors, quality leads).
AWS Services
The platform used a combination of AWS AI/ML and serverless services to enable rapid rollout, real-time feedback, and scalability
- Amazon S3 – Acts as the central image repository where cleaning staff upload post-cleaning photos of key areas like beds, bathrooms, and desks.
- Amazon S3 Event Notifications – Automatically triggers processing when a new image is uploaded.
- AWS Lambda – Serverless function that gets triggered upon image upload, orchestrates the flow, and interacts with AI models for analysis.
- Amazon Bedrock – Used to run foundation models that assess cleanliness by analyzing the image context and determine whether the area is “Clean” or “Messy.”
- Amazon RDS (MySQL) – Stores metadata of each image, cleanliness status, room number, timestamps, and staff details for audit and reporting.
- Amazon EKS (Elastic Kubernetes Service) – Hosts the supervisor dashboard, which allows authorized users to review room-wise images and their cleanliness status.
- Application Load Balancer (ALB) – Balances traffic to the EKS-hosted frontend application, ensuring high availability and fault tolerance.
- Amazon Route 53 – Provides DNS routing to the web dashboard under the hotel’s internal or branded domain.
- AWS IAM – Manages secure access between services and role-based access to the dashboard for cleaning staff and supervisors.
The QloudX Partnership
QloudX partnered with the customer to build an AI-powered Housekeeping Quality Check Platform leveraging computer vision and large language models (LLMs). The objective was to introduce automation while preserving the existing housekeeping workflow.
- Worked closely with the client’s operations and housekeeping management teams to understand their existing quality control processes, performance metrics, and operational challenges.
- Through collaborative discovery sessions, QloudX identified key areas where automation and AI could enhance efficiency.
- Created a framework that ensures scalability, operational ease, and alignment with the hospitality group’s brand and service standards.
Together, QloudX and the customer delivered a production-ready AI-powered platform that met enterprise standards for scalability, security, and performance.
Our Solution
QloudX developed an AI-powered housekeeping quality inspection platform built on a modular, serverless AWS architecture to automate and standardize room cleanliness evaluations across multiple hotel properties:
- Housekeeping staff capture images post-cleaning using a mobile app, which are automatically uploaded to Amazon S3.
- Each upload triggers AWS Lambda to invoke AWS Bedrock and vision models that assess room conditions and tag images as “Clean” or “Messy.”
- The results, along with quality scores and audit data, are stored in Amazon RDS, while Amazon QuickSight dashboards provide supervisors with instant visibility into room quality and operational performance.
- Supervisors access the insights through a secure web portal hosted on Amazon EKS, where they can review quality trends, identify recurring issues, and take corrective actions.
This scalable, AI-driven architecture enables real-time quality checks, automated reporting, and measurable performance improvements
Impact and Results
Within the first 3 months of pilot rollout, the hotel chain observed the following results:
- 60% reduction in time spent on manual room inspections.
- 100% coverage of cleaned rooms, ensuring no room is missed.
- Consistent cleanliness scoring, independent of human bias.
- Faster room turnover, improving occupancy and guest satisfaction.
- Centralized quality data, enabling performance benchmarking and training.
The AI-powered housekeeping checker has now become a key enabler in the brand’s digital transformation of hotel operations, with future plans to integrate voice assistance and multilingual feedback features for frontline teams.
MSP LifeCycle
QloudX delivered Managed Services using its Plan–Build–Run–Optimize model:
Plan
Baseline assessment of workloads, IAM practices, tagging, and monitoring.
Defined governance models for cost, security, and compliance.
Build
— Established cost and security monitoring by deploying necessary AWS services.
— Integrated Azure AD with AWS SSO, ensuring streamlined access management.
— Designed tagging strategy and being followed for tagging compliance.
— Introduced compliance dashboards for proactive oversight.
Run
— Enabled daily/weekly compliance reporting to detect and remediate non-compliant resources.
— Conducted IAM user cleanup, enforced MFA, and strengthened security groups.
— Monitored S3 policies, lifecycle management, and CloudWatch log retention.
— Continuous cost monitoring with Savings Plans, Reserved Instances, and rightsizing actions.
Optimize
— Increased AWS Security Hub score from 55% baseline to 85–90%+ across their multiple AWS accounts (9+), sustaining posture.
— Implemented cost optimization strategies, reducing cloud spend while improving performance.
— Enhanced governance through proactive reporting and regular stakeholder reviews.
— Pushing for SPP.
This lifecycle ensured Customer AWS environment remained secure, efficient, and continuously optimized.
Key Deliverables & Capabilities
Proactive Operations: Monitoring & Automation
— Deployed AWS Security Hub, Config and GuardDuty via Audit account to centralize security monitoring and reduce operational overhead.
— Established SNS alerting for GuardDuty findings.
— Established Cost monitoring with Budgets, Billing Alarms and Cost Anomaly Detection.
Governance & Compliance: Security Posture Hardening
— Enabled daily/weekly compliance reporting.
— IAM user cleanup, MFA enforcement, and strong password policies.
— Security group hardening for network defence.
— Continuous improvement of AWS Security Hub score.
Identity & Access Management
— Seamless Azure AD–AWS SSO integration, centralizing identity control.
— Precise permission and access protocols to reinforce security.
Value Realization: Cost Optimization & FinOps
— Structured cost governance model with tagging enforcement.
— Adopted Savings Plans and Reserved Instances to optimize predictable workloads.
— Rightsized EC2 instances and optimized S3 lifecycle policies.
— Achieved 15% to 20% cost reductions while improving performance.
Collaboration & Transparency: Reporting
— Delivered monthly Cloud Usage, Cost Optimization, and Security Reports.
— Provided clear visibility into utilization trends, compliance gaps, and cost-saving opportunities.
AWS Lays the Foundation:
QloudX leveraged AWS-native services to deliver proactive governance, security, and cost management.
AWS services
Operational Efficiency & Automation
— AWS Systems Manager for task automation and consistency
— CloudWatch & Systems Manager for monitoring and automation
Security & Compliance
— AWS Security Hub & AWS Config for security visibility and compliance enforcement
— IAM, MFA, and Security Groups for a strong security baseline
Identity & Access Management
— IAM integrated with Azure AD SSO for centralized and scalable identity management
Monitoring & Logging
— CloudWatch for infrastructure monitoring and log management
Storage Optimization
— S3 Policies and Lifecycle Management for data governance and cost efficiency
Cost Management & FinOps
— AWS Budgets, Cost Explorer, Savings Plans, and Reserved Instances for structured cost optimization
Outcomes
Operational Resilience & Efficiency
— Automated daily /weekly compliance reporting
— IAM cleanup, MFA enforcement, and security group hardening
— Reduced manual effort, enabling teams to focus on strategic initiatives
Enhanced Security Posture
— Improved AWS Security Hub scores from 55% to 85–90%+ across accounts
— Continuous monitoring and remediation for sustained compliance
— Strengthened security baseline with IAM, MFA, and Security Groups
Modernized Identity & Access Management
— Centralized access via Azure AD–AWS SSO integration
— Eliminated manual IAM overhead
— Ensured alignment with enterprise security standards
Resource & Storage Optimization
— EC2 rightsizing and S3 lifecycle policies for efficient resource utilization
— Reduced waste and improved performance
Cost Optimization & FinOps Maturity
— Structured FinOps practices: Budgets, Billing Alarms, Cost Explorer, Anomaly Detection
— Achieved 15–20% AWS cost reduction through Savings Plans, Reserved Instances, and EC2 rightsizing
— Improved forecasting and early anomaly detection
Governance & Executive Visibility
— Monthly consolidated reports for clear visibility into usage, cost, and security
— Enabled data-driven decision-making and proactive planning
— Established tagging compliance and long-term governance guardrails
Conclusion
Through this Managed Services partnership, QloudX enabled CUSTOMER to transform AWS operations into a secure, cost-optimized, and continuously improving environment. By combining proactive monitoring, security hardening, FinOps governance, and transparent reporting, CUSTOMER gained measurable business benefits — lowering costs, strengthening compliance, and achieving operational maturity across its AWS footprint.
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