Enterprise AI / Google Cloud

Vertex AI and Gemini
for enterprise workflows

Mativyx helps organizations design and deploy Google Cloud AI systems that combine Gemini models, Vertex AI services, BigQuery data foundations, GKE workloads, RAG pipelines, agent orchestration, evaluation, and governance.

Plan Vertex AI Adoption Compare Multi-LLM

Google Cloud AI Services

From Gemini prototype to governed production platform

We design the full operating model around your AI use cases, data boundaries, integration needs, and governance controls.

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Vertex AI Architecture

Reference architectures for Gemini, Model Garden models, embeddings, batch jobs, APIs, private networking, IAM, and environment separation.

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Enterprise RAG on Google Cloud

Document ingestion, chunking, embeddings, vector search, BigQuery integration, access-aware retrieval, citations, and answer quality evaluation.

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Gemini Agents

Agents that call enterprise tools, trigger workflows, reason over private knowledge, and produce auditable actions with human approvals.

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BigQuery + AI

AI-ready analytics foundations that connect warehouse, lakehouse, semantic layers, and operational systems to LLM applications.

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Safety & Governance

Prompt policies, content filters, model evaluation, data loss controls, audit logs, approval workflows, and compliance reporting.

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LLMOps on GCP

Deployment pipelines, prompt/version management, observability, regression tests, cost controls, and production release gates.

Delivery Model

A practical roadmap for Google AI adoption

  • Assess: classify workflows by value, risk, data sensitivity, latency, and integration complexity.
  • Design: choose Gemini, partner, or open models; define retrieval, evaluation, IAM, and cost policies.
  • Build: ship APIs, apps, agents, and data pipelines with measurable acceptance criteria.
  • Operate: monitor quality, drift, cost, latency, safety events, and business outcomes.

Best-fit workloads

  • Enterprise knowledge search and assistant experiences
  • Document extraction, summarization, and validation
  • Customer service copilots and support automation
  • Operations, compliance, tender, and contract intelligence
  • AI-enabled analytics over BigQuery and lakehouse data

Build on Google Cloud without locking into one model.

We can start with a Vertex AI architecture review and define the right path for Gemini, RAG, agents, and model governance.

Request a Vertex AI Review