What challenges did Brain Corp face before AI implementation?

Brain Corp faced the challenge of scaling autonomous robot operations that generate extensive structured and unstructured data requiring real-time processing, reliability, and security. Their existing monolithic AI platform limited scalability and innovation speed, and running on AWS incurred high infrastructure costs. Robots operated in dynamic public spaces with complex navigation and interaction challenges.

What was the impact of the AI solution?

Infrastructure costs reduced by 60%, achieving significant operational savings over running thousands of robots. Software update deployment time reduced from over an hour to 10-15 minutes, enabling six times faster delivery. Improved robot mobility, customer interaction, and deployment scale with over 26,000 autonomous mobile robots operating globally. Accelerated innovation with new AI-powered retail services like Store Vision AI and virtual store tours, enhancing customer and partner insights.

Source

GCPProductionEvidence: Medium65/100

Brain Corp powers autonomous mobile robots with BrainOS on Google Cloud

Use case typeRetail analytics platformUpdated Jun 13, 2026

Brain Corp is an AI software leader that powers the world's largest fleet of autonomous mobile robots operating in commercial indoor public spaces. To scale and improve its AI platform 'BrainOS', the company migrated from AWS to Google Cloud and redesigned BrainOS from a monolithic architecture to a modern microservices architecture using 28 Google Cloud native services. The migration enabled real-time robot-cloud communication instead of syncing every 60 seconds, improving robot performance and customer interactivity with a mobile app providing real-time robot status. Key Google Cloud services used include Google Kubernetes Engine Autopilot, Cloud Storage, Pub/Sub, BigQuery, Firestore, Cloud Logging, and Identity-Aware Proxy for security. This infrastructure supports data ingestion, storage, real-time analytics, and security requirements. The migration process took six months, with thousands of robots migrated globally without impacting customer experience. Subsequently, software updates can be deployed six times faster. Brain Corp achieved cutting yearly infrastructure costs by 60%, scaling workload efficiently without exponential cost growth, and accelerating new AI-powered retail services including Store Vision AI for inventory insights and virtual store tours.

Organization: Brain Corp
Industry: Retail
Location: United States
Published: May 2026

Reported outcomes

−60%

costCost savings

10-15 minutestime

Strategic outcomes

Speed & agilityEnabled real-time robot-cloud communicationNew product / capabilityAccelerated AI-powered retail servicesCustomer experience & trustImproved robot performance and interactivityScale & capacityScaled autonomous robots globally

Why do we believe this?Outcome claims, sources, and evidence checks

Normalized claim

Cost: 60% decrease

Google Cloud Customer StoriesMay 10, 2026Customer storyInferred claimMedium evidence strength

Infrastructure costs reduced by 60%, achieving significant operational savings over running thousands of robots.

Normalized claim

Time: 10-15 minutes decrease

Google Cloud Customer StoriesMay 10, 2026Customer storyInferred claimMedium evidence strength

Software update deployment time reduced from over an hour to 10-15 minutes, enabling six times faster delivery.

Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks

Customer: Brain Corp
Provider: GCP
Maturity: Production
Linked source: Google Cloud Customer Stories

Subsequently, software updates can be deployed six times faster

Customer identity supportedSource describes one deploymentMaturity supported

Primary read

Use case focus

Showing 3 of 3

1Autonomous Robotics
2Cloud Migration
3Real-Time Analytics

Brain Corp faced the challenge of scaling autonomous robot operations that generate extensive structured and unstructured data requiring real-time processing, reliability, and security.
Their existing monolithic AI platform limited scalability and innovation speed, and running on AWS incurred high infrastructure costs.
Robots operated in dynamic public spaces with complex navigation and interaction challenges.

Migrated BrainOS AI platform from AWS to Google Cloud adopting a microservices architecture with 99% new code.
Leveraged 28 Google Cloud native services including Google Kubernetes Engine Autopilot, Cloud Storage, Pub/Sub, BigQuery, Firestore, Cloud Logging, and Identity-Aware Proxy to automate and secure robotic processes.
Enabled real-time communication and insights for robots via cloud and mobile app.
Integrated robotic data with operational business data in BigQuery for enhanced analytics and partner/customer data sharing.

Technologies

Google Kubernetes Engine Autopilot Google Cloud Storage Cloud Pub/Sub BigQuery Firestore Cloud Logging Identity-Aware Proxy

Infrastructure costs reduced by 60%, achieving significant operational savings over running thousands of robots.
Software update deployment time reduced from over an hour to 10-15 minutes, enabling six times faster delivery.
Improved robot mobility, customer interaction, and deployment scale with over 26,000 autonomous mobile robots operating globally.
Accelerated innovation with new AI-powered retail services like Store Vision AI and virtual store tours, enhancing customer and partner insights.

Architecture

BrainOS platform redesigned from monolithic to microservices architecture using 28 Google Cloud native services including Google Kubernetes Engine Autopilot, Cloud Storage, Pub/Sub, BigQuery, Firestore, Cloud Logging, and Identity-Aware Proxy for security. Detailed real-time robot-cloud communication and analytics enablement with mobile app integration.

Sources & evidence1

Evidence: Medium65/100Evidence strength