Vertex AI vs Bedrock vs Azure AI?

Vertex AI leads for BigQuery-centric enterprises and multimodal Gemini workloads. Bedrock leads on AWS. Azure AI leads on Microsoft. We evaluate per data estate, identity model and procurement.

Can we use Claude or Llama on Vertex?

Yes — Claude, Llama, Mistral, Gemma and other models run on Vertex Model Garden with the same governance layer as Gemini.

How do you enforce data residency?

Regional endpoints, VPC Service Controls perimeters, CMEK, and Model Armor policies — reviewed against your risk framework before rollout.

Google Vertex AI Implementation

Gemini and Model Garden, grounded on the data you already trust.

Vertex AI implementation — Gemini, third-party and open models with Vertex AI Search, Agent Builder and BigQuery grounding, governed by Google Cloud IAM, VPC-SC and CMEK.

Schedule a strategy session See reference architectures

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Google Vertex AI Implementation | pronix.ai

Gemini + Model Garden — grounded on BigQuery, governed by Google Cloud.

Gemini 1.5 / 2.0

Vertex AI Search

Agent Builder

BigQuery grounding

Stand-up

6–10 wk

Grounding

BigQuery-native

Context

1M+ tokens

How we deliver

Assess → Design → Pilot → Implement → Scale → Operate.

One delivery model that moves from strategy to production without handoffs — with managed operations built in.

See how we deliver

Implementation · Google Vertex AI Implementationphased delivery

Assess

Use cases, BigQuery estate and IAM model.

wk 1

Design

Vertex Search, Agent Builder and Gemini plan.

wk 3

Pilot

One BigQuery-grounded agent.

wk 5

Implement

Agents, RAG, VPC-SC and CMEK.

wk 7

Scale

LOBs, projects, regions, models.

wk 9

Operate

Managed prompts, cost and evaluations.

wk 11

6–10 wk

First grounded agent live

1M+

Token context (Gemini)

BigQuery

Zero-copy grounding

VPC-SC

Data perimeter enforced

Certified partner platforms

Google Vertex AI Implementation | pronix.ai

The enterprise challenge

Google Cloud shops need AI that lives next to their analytics.

Vertex AI is the fastest path when your data warehouse is BigQuery and your identity is Google Cloud IAM. Grounding models on the same tables analysts already trust removes an entire integration layer.

Gemini + Model Garden
Gemini 1.5 / 2.0 plus Claude, Llama, Mistral and open models on the same runtime.
Grounded on BigQuery
Vertex AI Search and RAG over BigQuery, Cloud Storage and third-party sources with IAM-scoped access.
Enterprise controls
VPC Service Controls, CMEK, data residency and Model Armor guardrails baked in.

Capabilities

Full-lifecycle Vertex AI delivery.

Gemini strategy

Right-size Gemini Flash, Pro and Ultra per workload for cost, latency and quality.

Vertex AI Search (RAG)

Enterprise search and grounding over BigQuery, GCS and third-party sources.

Agent Builder

Multi-agent workflows with tools, extensions and Google-grade grounding.

Model Garden

Third-party and open models (Claude, Llama, Mistral, Gemma) on one governed runtime.

Governance

VPC-SC, CMEK, Model Armor, evaluations and responsible AI toolkit.

Managed operations

Prompt regression, model refresh and cost optimization under one SLA.

Google Vertex AI Implementation | pronix.ai-certified talent

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Deploy specialists who have delivered Google Vertex AI Implementation | pronix.ai implementations across enterprise environments — from design and build through steady-state operations.

Certified engineers
Solution architects
Conversation designers
Delivery leads

US + India pods Rapid staffing

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How we deliver

A six-step model, from assessment to managed operations.

Every engagement follows the same rhythm — so business, IT and delivery stay aligned from opportunity to outcome.

Assess

Use cases, BigQuery estate and IAM model.

Design

Vertex Search, Agent Builder and Gemini plan.

Pilot

One BigQuery-grounded agent.

Implement

Agents, RAG, VPC-SC and CMEK.

Scale

LOBs, projects, regions, models.

Operate

Managed prompts, cost and evaluations.

Where it lands

Use cases already in production with enterprise clients.

Analytics copilots

Natural-language BigQuery Q&A with Gemini, grounded on your semantic layer.

Contact-center intelligence

Gemini + Vertex AI Search behind CCAI Insights and Agent Assist workflows.

Multimodal document AI

Gemini on invoices, forms, images and audio for ops and back-office automation.

Regulated RAG

VPC-SC + CMEK grounded assistants for FS, healthcare and public sector.

Industry patterns

Industries where this ships fastest

Financial Services
Healthcare Providers
Retail & E-commerce
BPO / GBS

See industry solutions →

Runs on

Grounded on your data. Governed on day one.

Every platform we implement is only as good as the retrieval, connectors and controls behind it. These are the horizontal solutions we ship with every engagement.

Not sure where to start? Score your organization in 10 minutes.Take the AI Readiness Assessment →

Frequently asked

Questions buyers ask us first.

Vertex AI vs Bedrock vs Azure AI?: Vertex AI leads for BigQuery-centric enterprises and multimodal Gemini workloads. Bedrock leads on AWS. Azure AI leads on Microsoft. We evaluate per data estate, identity model and procurement.
Can we use Claude or Llama on Vertex?: Yes — Claude, Llama, Mistral, Gemma and other models run on Vertex Model Garden with the same governance layer as Gemini.
How do you enforce data residency?: Regional endpoints, VPC Service Controls perimeters, CMEK, and Model Armor policies — reviewed against your risk framework before rollout.

Next step

Book a working session with our google vertex ai implementation team.

30 minutes. Your architecture, your data, your KPIs. You leave with a concrete pilot outline and a business case worth defending.

Schedule the session →Read the playbook