What challenges did Trillet AI face before AI implementation?

Early voice assistants had high latency and spoke over callers. The system violated hard business constraints and hallucinated appointment bookings. Manual auditing of thousands of call logs created operational burden. The business was operating with about a 5% error rate and high infrastructure costs.

Source

GCPProductionEvidence: Medium65/100

Trillet AI: Gemini in Vertex AI + GKE to reduce call-center voice agent errors and costs

Use case typeCustomer service automationUpdated Jun 13, 2026

Trillet AI builds a voice application layer for enterprise that automates high-stakes customer interactions such as appointment rescheduling and government follow-ups. The company moved its infrastructure to Google Cloud, using Gemini in Vertex AI as the primary reasoning engine and Google Kubernetes Engine for autoscaling real-time voice traffic. It also used Speech-to-Text and Text-to-Speech for voice interactions, with the model ingesting extensive client-specific business logic and negative constraints.

Organization: Trillet AI
Industry: Tech & Comms
Location: United States
Published: May 2026

Reported outcomes

Conversion rate increase: +10%

Revenue & growth

Error rate reduction: 5 percentage points to under 1%Latency: 2 seconds

Catalog median for revenue & growth deployments: +40% across 67 reported metrics. Compare benchmarks →

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

Normalized claim

Error rate reduction: 5 percentage points to under 1%

Google Cloud Customer StoriesMay 31, 2026Customer storyExplicit claimMedium evidence strength

The transition to Google Cloud moved Trillet's error rate from 5% to well below 1%.

Normalized claim

Infrastructure cost reduction: 80%

Google Cloud Customer StoriesMay 31, 2026Customer storyExplicit claimMedium evidence strength

The efficiencies introduced by GKE brought infrastructure costs down by 80%.

Normalized claim

Latency: 2 seconds decrease

Google Cloud Customer StoriesMay 31, 2026Customer storyExplicit claimMedium evidence strength

With latency reduced to sub-two-second levels.

Normalized claim

Calls resolved without human intervention: 85%

Google Cloud Customer StoriesMay 31, 2026Customer storyExplicit claimMedium evidence strength

Trillet's agents now resolve 85% of complex calls without human intervention.

Normalized claim

Conversion rate increase: 10% increase

Google Cloud Customer StoriesMay 31, 2026Customer storyExplicit claimMedium evidence strength

For legal service clients, this shift in confidence resulted in a 10% increase in conversion rates.

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

Customer: Trillet AI
Provider: GCP
Maturity: Production
Linked source: Google Cloud Customer Stories

Manual auditing of thousands of call logs created operational burden

Customer identity supportedSource describes one deploymentMaturity supported

Primary read

Use case focus

Showing 3 of 3

1Conversational AI
2Customer Service Automation
3Voice AI

Migrated the platform to Google Cloud to improve control and latency.
Used Gemini in Vertex AI as the main reasoning engine with a large context window for client-specific business rules.
Deployed the core real-time application on Google Kubernetes Engine to scale automatically during traffic spikes.
Used Speech-to-Text API and Text-to-Speech API to support conversational voice interactions.

Technologies

Gemini in Vertex AI Vertex AI Google Kubernetes Engine Speech-to-Text AI Text-to-Speech AI Cloud Load Balancing

Increased conversion rates by 10% for legal aid clients.

Architecture

Trillet AI runs its real-time voice application on Google Kubernetes Engine and uses Gemini in Vertex AI as the primary reasoning engine. The model receives large amounts of client-specific business logic and 'negative constraints' to avoid invalid actions, while Speech-to-Text and Text-to-Speech services support live conversations.

Sources & evidence1

Evidence: Medium65/100Evidence strength