---
title: Retail Analytics Automation with XenonStack’s AWS Vision Platform
description: Discover retail analytics automation with xenonStack’s AWS vision platform for enhanced efficiency and data-driven decision-making.
image: https://www.xenonstack.com/hubfs/retail-analytics-automation.png
---

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[AWS](https://www.xenonstack.com/use-cases/tag/aws)

# Retail Analytics Automation with XenonStack’s AWS Vision Platform

[Navdeep Singh Gill](https://www.xenonstack.com/use-cases/author/navdeep-singh-gill) | 04 December 2025

Retail Analytics Automation with XenonStack’s AWS Vision Platform

7:46

![Retail Analytics Automation with XenonStack’s AWS Vision Platform](https://www.xenonstack.com/hs-fs/hubfs/retail-analytics-automation.png?width=1280&height=720&name=retail-analytics-automation.png)

XenonStack collaborated with a global premium spirits manufacturer to revolutionise retail outlet analytics through a cloud-native, AI-driven platform built on AWS. Manual inefficiencies, inconsistent data, and delayed insights plagued the legacy system. [Vision AI solution](https://www.nexastack.ai/solutions/vision-ai/)automated image capture and analysis using advanced computer vision models, integrated real-time dashboards, and deployed a fully managed architecture compliant with global data regulations.

 

The result was a scalable, secure, and intelligent platform that significantly reduced the need for on-site visits, improved data consistency, and delivered real-time actionable insights. By leveraging Amazon EKS, YOLOv8, and a range of [AWS services](https://www.xenonstack.com/amazon-web-services/), the platform elevated retail execution strategy, reduced labor overhead, and enhanced cross-market performance visibility. This case study reflects XenonStack’s leadership in delivering end-to-end AWS Managed Services, showcasing deep technical acumen and a commitment to measurable business impact.

![retail-analytics](https://www.xenonstack.com/hs-fs/hubfs/retail-analytics.png?width=784&height=671&name=retail-analytics.png)**Figure 1: Retail Analytics Automation** 

## Customer Challenge

The client, a globally recognised premium beverage producer, faced serious inefficiencies in retail outlet execution analysis. Traditional approaches involved periodic manual audits, often requiring physical site visits across dispersed geographies. These costly, inconsistent methods often resulted in delayed performance reporting, impacting market responsiveness.

 

Operational bottlenecks stemmed from a lack of a unified digital system for collecting and interpreting retail shelf data. The manual process was labour-intensive and error-prone, leading to governance issues, unreliable KPIS, and fragmented insights. The client needed a comprehensive platform to automate data collection, ensure high data fidelity, and empower stakeholders to make timely, informed decisions across global retail markets.

## Customer Information

- **Industry**: Beverage / Spirits Manufacturing
- **Geography**: Global operations with retail presence in North America, Europe, and Asia-Pacific
- **Company Size**: Large Enterprise
- **Key Objectives**: Automate outlet analysis, reduce operational costs, improve reporting accuracy, and enhance strategic retail execution

## Business Challenges

The client’s legacy operations relied on decentralised, spreadsheet-based tools and manual inputs to track in-store performance and brand compliance. This approach led to:

- High labor costs due to frequent on-site visits for shelf audits
- Inconsistent data due to varied regional practices and manual reporting errors
- Delayed insights, making real-time market responsiveness unattainable
- Stock-out incidents that impacted brand presence and sales opportunities
- Siloed data structures that hampered holistic, cross-functional analysis
- Lack of a feedback mechanism for field teams, causing misalignment in brand execution

The business needed an intelligent, cloud-native analytics platform capable of automating visual data capture and analysis to transform its retail operations into a more proactive, insight-driven process.

## Technical Challenges

The technical solution needed to address several complex requirements:

- **High-Volume Image Processing**: Thousands of shelf images require daily analysis using computer vision models to detect brand presence, pricing, and compliance indicators.
- **Accuracy and Model Performance**: Achieving high accuracy (\>95%) in KPI extraction demanded extensive model training and continuous optimisation of YOLOv8-based algorithms.
- **Geospatial Validation**: Field data required real-time location validation to confirm the authenticity of the images submitted from retail outlets.
- **Security & Compliance**: Global operations mandated GDPR compliance, data encryption at rest and in transit, IAM-based access controls, and auditability.
- **Scalability & Availability**: The solution needed to maintain high performance during peak loads, using Kubernetes-based orchestration across multiple availability zones.
- **Real-Time Visualisation**: Building dual dashboards for executive and admin users to track live KPIS, alerts, and outlet compliance trends.

## Partner Solution

### Solution Overview

XenonStack delivered a cloud-native computer vision-powered retail analytics platform hosted on AWS, engineered to automate outlet audits and enhance data-driven decisions. Key capabilities included:

- **Containerised Vision Workloads**: YOLOv8 models encapsulated in Docker containers to classify, detect, and extract brand-level KPIS with over 95% accuracy.
- **Kubernetes Orchestration via Amazon EKS**: EKS managed clusters with autoscaling node groups ensured optimal performance and uptime.
- **Custom Task Management Backend**: A secure backend enabled task assignments, verification, and data lineage tracking.
- **Real-Time Dashboards**: Amazon CloudWatch dashboards gave tailored insights to different user personas—field executives, data analysts, and operations leads.
- **Secure, Compliant Architecture**: Multi-layered security using IAM, KMS, and CloudTrail to meet GDPR and internal governance standards.

### Architectural Diagram

![architecture](https://www.xenonstack.com/hs-fs/hubfs/architecture-2.png?width=1920&height=1080&name=architecture-2.png)

**Figure 2: Architectural Diagram**

## AWS Services Used

- **Amazon VPC & Subnets**: Isolated network segments for public and private workloads
- **Amazon Route 53**: Low-latency DNS resolution
- **Amazon EKS**: Orchestration of Docker-based AI models
- **Amazon ECR**: Container image repository integrated with CI/CD
- **Amazon S3**: Image and artefact storage with lifecycle policies
- **Amazon RDS**: Relational metadata store for task management
- **AWS CloudWatch**: Logging, monitoring, and dashboarding
- **AWS CloudTrail**: API-level audit trails
- **AWS KMS**: Encryption of data at rest
- **AWS IAM**: Role-based access and policy enforcement
- **AWS Secrets Manager**: Secure management of API tokens and DB credentials
- **Elastic Load Balancer**: Traffic management across multi-AZ services

## Results and Benefits

### Business Outcomes

- **50%+ Reduction in Field Visit Costs**: Automation replaced manual audits, cutting overhead significantly
- **Improved Data Accuracy**: Standardized image analysis led to over 95% accuracy in KPI reporting
- **Accelerated Time-to-Insight**: Market response time improved from days to hours through real-time dashboards
- **Decrease in Stock-Outs**: Enhanced shelf visibility reduced out-of-stock incidents, boosting revenue potential
- **Cross-Market Transparency**: Unified dashboards enabled global consistency and compliance benchmarking
- **Enhanced Employee Productivity**: Sales teams focused on strategic engagement rather than data collection

### Technical Benefits

- **High Scalability**: EKS autoscaling supports dynamic workload demands
- **Robust Compliance Posture**: KMS, IAM, and CloudTrail ensured adherence to GDPR and internal data governance policies
- **Real-Time Operations**: Dashboards powered by CloudWatch significantly reduced report generation and lag
- **Optimised Resource Use**: [GitLab CI pipelines](https://docs.gitlab.com/ci/pipelines/) and S3 lifecycle policies minimise infrastructure and storage costs

## Lessons Learned

### Challenges Overcome

- **Model Accuracy Optimisation**: YOLOv8 models required multiple training iterations and fine-tuning with diverse datasets (100–150 images per brand) to reach the target accuracy
- **Compliance and Policy Automation**: Security configurations were codified into infrastructure scripts to enforce IAM, KMS, and audit logging at scale
- **Dashboard Performance**: Initial slow query response was improved by implementing caching and optimising database indices in RDS
- **Middleware Compatibility**: Standardised data exchange formats and containerised middleware helped integrate computer vision components and backend APIS seamlessly.

## Next Steps with AWS Vision Platform

Talk to our experts about implementing compound AI system, How Industries and different departments use Agentic Workflows and Decision Intelligence to Become Decision Centric. Utilizes AI to automate and optimize IT support and operations, improving efficiency and responsiveness.

[Contact Us](https://www.xenonstack.com/contact-us/) [Talk To Specialist](https://www.xenonstack.com/talk-to-specialist/)

### More Ways to Explore Us

### [AWS Panorama for Edge-based Computer Vision](https://www.xenonstack.com/blog/aws-panaroma-computer-vision-applications)

### [Building Scalable Computer Vision Solutions with Amazon](https://www.xenonstack.com/blog/computer-vision-solutions-amazon-rekognition)

### [AWS Computer Vision Services and Solutions Company](https://www.xenonstack.com/amazon-web-services/aws-computer-vision/)

 

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## Explore Related Topics

[Platform Engineering](https://www.xenonstack.com/use-cases/tag/platform-engineering)

[XAI](https://www.xenonstack.com/use-cases/tag/xai)

[DataOps](https://www.xenonstack.com/use-cases/tag/dataops)

[Multi Cloud](https://www.xenonstack.com/use-cases/tag/multi-cloud)

[Enterprise AI](https://www.xenonstack.com/use-cases/tag/enterprise-ai)

[Application Modernization](https://www.xenonstack.com/use-cases/tag/application-modernization)

![navdeep-singh-gill](https://www.xenonstack.com/hubfs/navdeep-gill-ceo-xenonstack.svg)

## Navdeep Singh Gill

Global CEO and Founder of XenonStack

Navdeep Singh Gill is serving as Chief Executive Officer and Product Architect at XenonStack. He holds expertise in building SaaS Platform for Decentralised Big Data management and Governance, AI Marketplace for Operationalising and Scaling. His incredible experience in AI Technologies and Big Data Engineering thrills him to write about different use cases and its approach to solutions.

[Explore More by Navdeep Singh Gill ![cta-blue-arrow](https://www.xenonstack.com/hubfs/cta-arrow-blue.svg)](https://www.xenonstack.com/use-cases/author/navdeep-singh-gill)

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XenonStack Agentic Foundry powers enterprise agentic systems with unified infra, analytics, workflows, and security to drive automation and compliance.

[![Youtube](https://www.xenonstack.com/hubfs/xs-footer-social-icons/youtube-icon.svg)](https://www.youtube.com/c/XenonStackOfficial) [![LinkedIn](https://www.xenonstack.com/hubfs/xs-footer-social-icons/linkedin-icon.svg)](https://www.linkedin.com/company/xenonstack/) [![Github](https://www.xenonstack.com/hubfs/xs-footer-social-icons/github-icon.svg)](https://github.com/xenonstack) [![Twitter](https://www.xenonstack.com/hubfs/xs-footer-social-icons/twitter-icon.svg)](https://twitter.com/xenonstack) [![Medium](https://www.xenonstack.com/hubfs/xs-footer-social-icons/medium-icon.svg)](https://medium.com/@xenonstack) [![Instagram](https://www.xenonstack.com/hubfs/xs-footer-social-icons/instagram-icon.svg)](https://www.instagram.com/teamxenonstack/)

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## AI Engineering

[Composite AI](https://www.xenonstack.com/artificial-intelligence/composite-ai/) [Decision AI](https://www.xenonstack.com/artificial-intelligence/decision-ai/) [AI Quality](https://www.xenonstack.com/artificial-intelligence/ai-quality/) [Generative AI](https://www.xenonstack.com/artificial-intelligence/generative-ai/) [Multimodal AI](https://www.xenonstack.com/artificial-intelligence/multimodal-ai/) [AI Assurance](https://www.xenonstack.com/artificial-intelligence/explainable-ai/) [MLOps](https://www.xenonstack.com/artificial-intelligence/mlops/) [Physical AI](https://www.xenonstack.com/artificial-intelligence/physical-ai/) [Augmented Engineering](https://www.xenonstack.com/artificial-intelligence/ai-augmented-software-development/) [Generative BI](https://www.xenonstack.com/artificial-intelligence/generative-bi/)

## Data Foundry

[Streaming Data Platform](https://www.xenonstack.com/dataops/streaming-data-platform/) [Data Lakehouse](https://www.xenonstack.com/dataops/delta-lake/) [Data Catalog](https://www.xenonstack.com/dataops/data-catalog/) [Data Observability](https://www.xenonstack.com/dataops/data-observability/) [Cloud Data Warehouse](https://www.xenonstack.com/dataops/cloud-data-warehouse/) [Data Engineering](https://www.xenonstack.com/dataops/data-engineering/) [MetaData Management](https://www.xenonstack.com/dataops/metadata-management/) [Data Quality](https://www.xenonstack.com/dataops/augmented-data-quality/) [Real Time Analytics](https://www.xenonstack.com/dataops/real-time-analytics/) [Data Modernization](https://www.xenonstack.com/dataops/data-modernization/)

## Platform Engineering

[Cloud Native](https://www.xenonstack.com/cloud-native/platform-engineering/) [Automation As Code](https://www.xenonstack.com/cloud-native/automation-as-code/) [Observability](https://www.xenonstack.com/cloud-native/observability/) [FinOps](https://www.xenonstack.com/cloud-native/finops/) [Application Modernization](https://www.xenonstack.com/cloud-native/application-modernization/) [DevSecOps](https://www.xenonstack.com/cloud-native/devsecops/) [Site Reliability Engineering](https://www.xenonstack.com/cloud-native/site-reliability-engineering/) [Progressive Delivery](https://www.xenonstack.com/cloud-native/progressive-delivery/) [GitOps](https://www.xenonstack.com/cloud-native/gitops/) [Compliance as code](https://www.xenonstack.com/cloud-native/compliance-as-code/) [Value Stream Management](https://www.xenonstack.com/cloud-native/value-stream-management/) [Policy as Code](https://www.xenonstack.com/cloud-native/policy-as-code/) [Telemetry Pipeline](https://www.xenonstack.com/cloud-native/telemetry-pipeline/)

## Agentic AI

[Agentic Analytics](https://www.xenonstack.com/agentic-ai/enterprise-systems/) [Agentic AI Systems](https://www.xenonstack.com/agentic-ai/agentic-ai-system/) [Process Intelligence](https://www.xenonstack.com/agentic-ai/business-process-operations/) [Developer Experience](https://www.xenonstack.com/agentic-ai/developer-experience-platform/) [Autonomous Operations](https://www.xenonstack.com/agentic-ai/autonomous-operations/) [AI Vision at EDGE](https://www.xenonstack.com/agentic-ai/edge-and-vision-ai/) [Compound AI System](https://www.xenonstack.com/agentic-ai/compound-ai-system/) [GUI Agents](https://www.xenonstack.com/agetic-ai/gui-agents/) [CMDB Management](https://www.xenonstack.com/agentic-ai/cmdb-management/) [ITSM](https://www.xenonstack.com/agentic-ai/itsm/) [Network Automation](https://www.xenonstack.com/agentic-ai/network-automation/)

## AI Agents

[DataBricks AI Agents](https://www.xenonstack.com/ai-agents/databricks-ai-agents/) [SnowFlake AI Agents](https://www.xenonstack.com/ai-agents/snowflake-ai-agents/) [ServiceNow AI Agents](https://www.xenonstack.com/ai-agents/servicenow-ai-agents/) [AWS AI Agents](https://www.xenonstack.com/ai-agents/aws-ai-agents/) [Microsoft Azure AI Agents](https://www.xenonstack.com/ai-agents/microsoft-azure-ai-agents-actions/) [SalesForce AI Agents](https://www.xenonstack.com/ai-agents/salesforce-agents-actions/) [MySQL AI Agents](https://www.xenonstack.com/ai-agents/mysql-agents-actions/) [PostgreSQL AI Agents](https://www.xenonstack.com/ai-agents/postgresql-agents-actions/) [Datadog AI Agents](https://www.xenonstack.com/ai-agents/datadog-agents-actions/) [DynaTrace AI Agents](https://www.xenonstack.com/ai-agents/dynatrace-agents-actions/) [Splunk AI Agents](https://www.xenonstack.com/ai-agents/splunk-agents-actions/) [BigQuery AI Agents](https://www.xenonstack.com/ai-agents/bigquery-agents-actions/) [SAP AI Agents](https://www.xenonstack.com/ai-agents/sap-agents-actions/) [Infor AI Agents](https://www.xenonstack.com/ai-agents/infor-agents-actions/) [Oracle AI Agents](https://www.xenonstack.com/ai-agents/oracle-agents-actions/) [WorkDay AI Agents](https://www.xenonstack.com/ai-agents/workday-agents-actions/) [Jira AI Agents](https://www.xenonstack.com/ai-agents/jira-agents-actions/)

## Industry

[Aerospace and Aviation](https://www.xenonstack.com/industries/aerospace/) [Financial Services](https://www.xenonstack.com/industries/banking/) [Automotive And Industrial](https://www.xenonstack.com/industries/automotive/) [Consumer Tech](https://www.xenonstack.com/industries/consumer-technology/) [Technology, Media and Telco](https://www.xenonstack.com/industries/enterprise-technology/) [Digital Supply Chain](https://www.xenonstack.com/industries/digital-supply-chain/) [Hospitality and Tourism](https://www.xenonstack.com/industries/travel-hospitality/) [Discrete Manufacturing](https://www.xenonstack.com/industries/automotive/) [Education](https://www.xenonstack.com/industries/education/) [Media and Entertainment](https://www.xenonstack.com/industries/media-entertainment/) [Oil and Gas](https://www.xenonstack.com/industries/oil-and-gas/) [Energy and Utilities](https://www.xenonstack.com/industries/energy-and-utilities/)

## Enterprise Support

[AI Managed Services](https://www.xenonstack.com/managed-services/ai-managed-services/) [Kubernetes Managed Services](https://www.xenonstack.com/managed-services/kubernetes/) [SRE as a Service](https://www.xenonstack.com/managed-services/site-reliability-engineering/) [Data Managed Services](https://www.xenonstack.com/managed-services/big-data/) [Analytics Managed Services](https://www.xenonstack.com/managed-services/analytics-managed-services/) [Data Protection](https://www.xenonstack.com/readiness-assessment/data-protection/) [On-Premise AI](https://www.xenonstack.com/managed-services/on-premise-ai-cluster/)

## Solutions

[Private Cloud](https://www.xenonstack.com/solutions/private-cloud/) [Internal Developer Platform](https://www.xenonstack.com/solutions/internal-developer-platform/) [AI Inference](https://www.xenonstack.com/solutions/ai-inference/) [Open-Source Data Platform](https://www.xenonstack.com/solutions/open-source-data-platform/) [AI Trust Score](https://www.xenonstack.com/solutions/ai-trust-score/) [Autonomous SoC](https://www.xenonstack.com/solutions/autonomous-soc/) [Digital Twin](https://www.xenonstack.com/solutions/digital-twin/) [Readiness Assessment](https://www.xenonstack.com/readiness-assessment/) [Talk To Specialist](https://www.xenonstack.com/talk-to-specialist/)

## Company

[About Us](https://www.xenonstack.com/about-us/) [Leadership Team](https://www.xenonstack.com/about-us/leadership-team/) [TAO of XenonStack](https://www.xenonstack.com/about-us/tao-of-xenonstack/) [How We Grow](https://www.xenonstack.com/about-us/how-we-grow/) [How We Work](https://www.xenonstack.com/about-us/how-we-work/) [Careers](https://www.xenonstack.com/careers/) [XA - QSIR](https://www.xenonstack.com/xenonstack-academy/) [Contact Us](https://www.xenonstack.com/contact-us/) [Book Demo](https://demo.xenonstack.com/)

## Resources

[Blog](https://www.xenonstack.com/blog) [Insights](https://www.xenonstack.com/insights/) [Use Cases](https://www.xenonstack.com/use-cases) [Case Study](https://www.xenonstack.com/case-studies) [Videos](https://www.xenonstack.com/videos/) [EBooks](https://www.xenonstack.com/e-book) [Presentations](https://www.xenonstack.com/presentations/)

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✕

## Agent SRE for Reliability and Observability Solutions

 AI continuously monitors systems for risks before they escalate. It correlates signals across logs, metrics, and traces. This ensures faster detection, fewer incidents, and stronger reliability

- ![Performance Icon](https://www.xenonstack.com/hubfs/performance.svg)Proactive detection of performance and availability issues
- ![Root Cause Icon](https://www.xenonstack.com/hubfs/root-cause.svg)Root-cause analysis across microservices and environments
- ![Remediation Icon](https://www.xenonstack.com/hubfs/remediation.svg)Automated remediation playbooks to reduce MTTR

[Explore Agent SRE](https://agentsre.ai/)

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✕

## Physical Surveillance with Vision AI Agent Technology

 AI converts camera feeds into instant situational awareness. It detects unusual motion and unsafe behavior in real time. Long hours of video become searchable and summarized instantly

- ![Motion Icon](https://www.xenonstack.com/hubfs/motion.svg)Real-time detection of suspicious motion or intrusion
- ![Video Search Icon](https://www.xenonstack.com/hubfs/video-search.svg)Natural language video search and instant playback
- ![Summary Icon](https://www.xenonstack.com/hubfs/summary.svg)Smart summaries for audits, investigations, and compliance

[See Vision AI in Action](https://www.xenonstack.ai/)

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✕

## Agentic Data Intelligence Across Your Full Data Stack

 Your data stack becomes intelligent and conversational. Agents surface insights, detect anomalies, and explain trends. Move from dashboards to autonomous, always-on analytics

- ![Connects warehouses](https://www.xenonstack.com/hubfs/data-icon.svg)Connects to warehouses, lakes, and streaming sources
- ![Question Answering](https://www.xenonstack.com/hubfs/answers.svg)Question-answering in natural language
- ![Continuous monitoring](https://www.xenonstack.com/hubfs/monitoring-2.svg)Continuous monitoring for anomalies and KPI deviations

[See in Action](https://elixirdata.co/)

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✕

## Intelligent Diagnostic for Self-Healing System Automation

 Agents identify recurring failures and performance issues. They trigger workflows that resolve common problems automatically. Your infrastructure evolves into a self-healing environment

- ![Diagnostics Icon](https://www.xenonstack.com/hubfs/diagnostic.svg)Automated diagnostics for recurring errors
- ![Playbook Icon](https://www.xenonstack.com/hubfs/playbook.svg)Playbook execution: restart services, scale pods, clear queues
- ![Feedback Icon](https://www.xenonstack.com/hubfs/feedback.svg)Feedback loop for improving remediation strategies

[See in Action](https://agentanalyst.ai/)

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✕

## Agentic GRC - Monitoring Risk and Compliance Controls

 AI continuously checks controls and compliance posture. It detects misconfigurations and risks before they escalate. Evidence collection becomes automatic and audit-ready

- ![Controls Icon](https://www.xenonstack.com/hubfs/controls.svg)Continuous control checks across infrastructure and SaaS
- ![Audit Icon](https://www.xenonstack.com/hubfs/audit.svg)Automated evidence collection for audits
- ![Risk Icon](https://www.xenonstack.com/hubfs/risk.svg)Risk scoring and prioritized remediation recommendations

[Explore Agent GRC](https://agentgrc.ai/)

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✕

## Agentic Finance and Procurement Intelligent Agents

 Financial and procurement workflows become proactive and insight-driven. Agents monitor spend, vendors, and contracts in real time. Approvals and sourcing decisions become faster and smarter

- ![Visibility Icon](https://www.xenonstack.com/hubfs/visibility.svg)Real-time visibility into spend and commitments
- ![Anomaly Icon](https://www.xenonstack.com/hubfs/anomaly.svg)Anomaly detection on invoices and vendor performance
- ![Workflow Icon](https://www.xenonstack.com/hubfs/workflow.svg)Intelligent workflows for approvals and sourcing decisions

[Optimize Finance & Procurement](https://www.xenonify.ai/)

![agentic-finance-and-procurement](https://www.xenonstack.com/hubfs/responsible-ai-aviators-banner-illustration.svg)

```json
{
  "@context" : "http://schema.org",
  "@type" : "Organization",
  "address" : {
    "@type" : "PostalAddress",
    "addressCountry" : "USA",
    "addressLocality" : "Plano",
    "addressRegion" : "Texas",
    "postalCode" : "75024",
    "streetAddress" : "7700 Windrose Ave. "
  },
  "description" : "XenonStack is the #1 Data and AI foundry and technology services company to simplify and scale Enterprise and Generative AI Journeys.",
  "email" : "business@xenonstack.com",
  "logo" : "https://f.hubspotusercontent30.net/hubfs/8161231/Xenonstack-Serives%20-3-2-2021-10.png",
  "mainEntityOfPage" : {
    "@id" : "https://www.xenonstack.com/use-cases/retail-analytics-automation",
    "@type" : "WebPage",
    "description" : "Discover retail analytics automation with xenonStack’s AWS vision platform for enhanced efficiency and data-driven decision-making."
  },
  "name" : "XenonStack",
  "sameAs" : [ "https://www.facebook.com/XenonStack", "https://www.linkedin.com/company/xenonstack/", "https://www.youtube.com/c/XenonStackOfficial", "https://twitter.com/xenonstack" ],
  "telephone" : "",
  "url" : "https://www.xenonstack.com/"
}
```