Normalized claim
Quantified impact: 30 x increase
Scaled 30X to handle more than 250,000 interactions daily.
Callers case study - Google Cloud
Use case typeCustomer service automationUpdated Jun 13, 2026
Callers is a voice and text AI communications platform for B2C brands. The company needed to scale fully autonomous AI agents across voice, SMS, chat, and WhatsApp while keeping latency low and response quality high. Callers migrated infrastructure to Google Cloud, moved deployment to Google Kubernetes Engine, used Gemini as the core engine for natural-sounding voice conversations, and used Vertex AI for use-case-specific workflows. The system maintains customer context across channels and routes insights back to clients' CRMs.
- Organization
- Callers
- Industry
- Tech & Comms
- Location
- Israel
- Published
- May 2026
Reported outcomes
−30%
quantified impactTime & speed
30xquantified impact
Strategic outcomes
Scale & capacityScaled autonomous AI across channelsSpeed & agilityReduced communication latencyCustomer experience & trustImproved response qualityCustomer experience & trustEnabled revenue recovery from cold leads
Why do we believe this?Outcome claims, sources, and evidence checks
Normalized claim
Quantified impact: 30% decrease
Reduced latency by 30%.
Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks
- Customer
- Callers
- Provider
- GCP
- Maturity
- Production
- Linked source
- Google Cloud Customer Story
Migrated infrastructure to Google Cloud and deployed on Google Kubernetes Engine (GKE)
Customer identity supportedSource describes one deploymentMaturity supported
Primary read
Use case focus
Showing 3 of 4
- 1Conversational AI
- 2Customer Service
- 3Contact Center
- Scaling autonomous AI agents across multiple customer communication channels with low latency and high response quality.
- Coordinating systems across multiple clouds while improving engineering velocity and customer experience.
- Migrated infrastructure to Google Cloud and deployed on Google Kubernetes Engine (GKE).
- Adopted Gemini as the core engine for natural-sounding voice agents.
- Used Vertex AI for use-case-specific workflows.
- Implemented a single AI brain that retains full customer context across voice, chat, SMS, and WhatsApp and routes insights back to customers' CRMs.
Technologies
- Scaled 30X to handle more than 250,000 interactions daily.
- Reduced latency by 30%.
- Improved response quality.
- Increased connect rates and deal closures.
- Helped customers recover revenue by reviving cold leads with real-time voice AI.
Architecture
Callers migrated its infrastructure from multiple cloud environments to Google Cloud and deployed on Google Kubernetes Engine. The platform uses Gemini as the core engine for voice conversations and Vertex AI for use-case-specific workflows, with a single AI brain retaining context across voice, SMS, chat, and WhatsApp and pushing insights back into client CRMs.
Sources & evidence1
Evidence: Medium65/100Evidence strength
- Customer explicitly identified
- Deployment status explicitly supported
- Primary source available
- Quantified outcome available
- Technical implementation details available
Type: Customer StoryPublished: May 27, 2026Publisher: Google CloudEvidence: PrimaryConfidence: High
AI-generated summary. Verify important details with the linked sources before relying on this case.
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