GOOGLE CLOUD AI
Vertex AI consulting to build, evaluate, and operate AI solutions.
We use Vertex AI to build and run AI components on Google Cloud, with data, evaluations, security, monitoring, and integration.
DIRECT ANSWER
What is vertex ai consulting?
Vertex AI is the Google Cloud platform for developing, adapting, evaluating, and operating AI models and applications in an enterprise environment.
Who it is forData, engineering, and product teams that need to take models, RAG, or generative AI into production on Google Cloud.
CONTEXT
Technical decisions with an operational view.
Picking a model is only one decision. Context quality, evaluation, latency, cost, privacy, and integration determine the value in production.
We design reproducible experiments, evaluation sets, pipelines, and observability. The architecture can combine foundation models, embeddings, search, functions, and custom services.
We also handle IAM, networking, secrets, logging, and lifecycle so the prototype does not turn into an exception nobody can govern.
OUTCOMES
What the initiative has to deliver.
Technical goals only matter when they improve security, speed, cost, experience or the ability to decide.
- 01AI architecture on Google Cloud
- 02Reproducible evaluations
- 03RAG and integrations
- 04MLOps pipelines
- 05Security and observability
- 06Costs tracked
WHEN IT MAKES SENSE
Signs that it is time to act.
- Notebooks have to become production
- The team is comparing models
- RAG quality is poor
- There is no consistent evaluation
- Cost and latency swing
- The solution has to integrate with enterprise systems
HOW WE WORK
From assessment to operations.
Short stages, visible criteria and knowledge transfer at every decision.
Use case and metric
We define the task, the data, and the quality criteria.
Experiment
We compare approaches with reproducible evaluation.
Production
We integrate, secure, and automate the deployment.
Operations
We monitor quality, cost, usage, and drift.
DELIVERABLES
Clarity on what gets finished.
- Vertex AI architecture
- Proof of value
- Evaluation set
- Pipelines
- Inference API
- Monitoring and governance
FREQUENTLY ASKED QUESTIONS
Straight answers.
Are Vertex AI and Gemini Enterprise the same thing?
No. Vertex AI is a platform for building and operating AI solutions; Gemini Enterprise provides an enterprise experience for agents and search. They can complement each other.
Can we use our own models?
Yes, depending on support and architecture. You can also combine models from the Google ecosystem with custom components.
Do you implement RAG?
Yes. Sources, chunking, embeddings, ranking, permissions, evaluation, and observability are all part of the project.
How do we control cost?
We measure volume, tokens, caching, model, latency, and architecture per use case, with limits and telemetry.
Technical sources and references
EVIDÊNCIA EM CAMPO
A Google partnership backed by presence in the ecosystem.
We attend Google Cloud Next, the Partner Summit and working sessions with the Google team, turning announcements, platform and relationships into better decisions for clients.
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Tell us the situation. We help you see the best path.
A focused conversation to understand context, risk, priority and the first workable step.