Google Vertex AI (Gemini)

Fluents + Google Vertex AI (Gemini) ensures seamless campaign orchestration and compliance, integrating AI voice agents with superior analytical capabilities to enhance your workflows.

The same Gemini conversation engine Fluents runs — deployed on your Google Cloud infrastructure.

Fluents on Vertex AI: Enterprise Gemini for Regulated Industries

Fluents uses Google Gemini as its conversation engine. For enterprise customers who require data residency, private endpoints, or Google Cloud-native compliance controls, Fluents accesses Gemini through Google Vertex AI — keeping model inference within your chosen cloud region and under your data governance policies.

This is particularly relevant for healthcare systems, financial institutions, and government-adjacent organizations that cannot send data to shared public API endpoints. Vertex AI gives you the same Gemini capability with the control your compliance team requires.

Deploy Fluents agents on Gemini via Vertex AI for data residency control — keeping model inference within your chosen GCP region

Access enterprise Gemini models with higher rate limits and dedicated throughput for high-volume call operations

Meet HIPAA, SOC 2, and other compliance requirements with Google Cloud's enterprise data handling agreements

Healthcare Networks: HIPAA-Compliant Conversation AI at Scale

A regional hospital network running 50,000 patient calls per month needs both performance and compliance. Through Vertex AI, Fluents accesses Gemini within a HIPAA Business Associate Agreement framework, with data processed in a US-region GCP environment. Patient names, appointment details, and health information stay within the compliant boundary — and the AI quality that makes those conversations work doesn't get compromised.

Financial Services: Data Residency for Cross-Border Compliance

A wealth management firm operating across the EU and US has data residency requirements that preclude shared API endpoints. Vertex AI lets Fluents route European client conversations through EU-region model endpoints and US client conversations through US-region endpoints — meeting GDPR and SEC requirements simultaneously. Same model, same quality, different data boundaries.

Government and Public Sector: FedRAMP-Adjacent Infrastructure

Organizations that serve government clients often require their technology stack to meet specific infrastructure standards. Google Cloud's FedRAMP authorization and Vertex AI's enterprise controls give Fluents the infrastructure foundation to support these requirements. Contact the Fluents team to discuss specific public sector deployment configurations.

Enterprise-grade AI calling for organizations that can't compromise on data governance

Calls That Just Work

No per-minute taxes. No brittle workflows. Just enterprise-grade reliability with API-level flexibility.

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FAQs

Questions about Fluents' Vertex AI configuration.

What's the difference between using Gemini directly vs. through Vertex AI?

The public Gemini API and Vertex AI run the same models. The difference is infrastructure: Vertex AI offers dedicated throughput, data residency controls, enterprise SLAs, and Google Cloud's compliance certifications (HIPAA, SOC 2, ISO 27001). For regulated industries or high-volume deployments, Vertex AI is the recommended path.

Does Fluents support private endpoint deployment on Vertex AI?

Yes. For enterprise customers, Fluents can be configured to route model inference through private Vertex AI endpoints in your GCP project. This means model calls never traverse shared infrastructure. Contact the Fluents enterprise team for deployment architecture details.

Is there a performance difference when using Vertex AI vs. the standard Gemini API?

Enterprise Vertex AI deployments offer dedicated throughput and provisioned capacity, which can actually improve latency consistency at high call volumes compared to shared public API endpoints. For operations running thousands of simultaneous calls, this matters significantly.

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