Amber Mobile — Document AI + Vertex AI/MLOps for multimodal game analytics
Use case typeIntelligent document processingUpdated Jun 13, 2026
Amber Mobile modernized its data lake and warehouse on Google Cloud and integrated AI/ML to deliver real-time insights, improve computer vision inspection and prediction accuracy, and automate document information extraction at scale. The customer story describes use of BigQuery, Cloud Storage, Dataproc, Cloud Composer, Vertex AI, Document AI, BigQuery ML, Looker Studio, and GKE/Ray on GKE.
- Organization
- Amber Mobile
- Industry
- Tech & Comms
- Location
- Singapore
- Published
- May 2026
Reported outcomes
99.9%
accuracyQuality & accuracy
+99%quantified impact
Strategic outcomes
New product / capabilityAutomated document extraction at scaleBetter decisions & insightFaster insights for decision-makingScale & capacityExpanded data service capacityNew product / capabilityImproved prediction and inspection accuracy
Catalog median for quality & accuracy deployments: +90% across 270 reported metrics. Compare benchmarks →
Primary read
Use case focus
Showing 3 of 4
- 1Computer Vision
- 2MLOps
- 3Document Processing
- Amber Mobile needed to modernize its data platform and integrate AI to support faster insights and higher-accuracy predictions.
- The company also needed to automate extraction from unstructured documents at scale and improve large-scale training workflows.
Amber Mobile migrated to fully managed BigQuery and Cloud Storage for its data lake and warehouse, used Dataproc and Cloud Composer for processing and orchestration, Vertex AI for model building, BigQuery ML for offline batch deployment, Document AI for document extraction, and GKE with Ray for distributed reinforcement-learning training.
- Reduced data insights acquisition time to within one day.
- Delivered five times the data service capacity.
- Boosted AI/ML-driven computer vision inspection and user behavior prediction to 99%.
- Document AI accuracy reached up to 99.9%.
Implementation partners1
Sources & evidence1
Groundedness: 5/5Type: Customer StoryPublished: May 21, 2026Publisher: Google CloudEvidence: PrimaryConfidence: High
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