We turn the potential of Google Cloud into solutions for your business. Modern applications, data that informs decisions and artificial intelligence connected to your operations.
Google Cloud, engineered by NewInntech
We connect your applications, information and team through purposeful architecture. We work with you from the first decision through launch and ongoing improvement.
We design projects, networks, identities and environments. We assess what to migrate or modernize and organize the transition in stages, with testing and a rollback plan.
Cloud governance · IAM · Networking · Infrastructure as codeWe build APIs, microservices and integrations. We use Cloud Run to run applications on managed services and GKE when the solution needs Kubernetes.
Cloud Run · Google Kubernetes Engine · Cloud SQLWe integrate sources, transform information and design data models for analysis. We bring insights to your team with clear standards for quality, access and freshness.
BigQuery · Dataflow · Pub/Sub · LookerWe develop assistants, document search and machine learning solutions. We evaluate quality, permissions and consumption before bringing models into your processes.
Gemini Enterprise Agent Platform · The evolution of Vertex AIWe connect repositories, tests and deployments in a traceable process. We automate infrastructure and controls so that every release is verifiable and repeatable.
CI/CD · Containers · Infrastructure as codeWe make service health and consumption visible. We review capacity, budgets and priorities to balance performance, continuity and operating costs.
Observability · Budgets · Resource optimizationThree ways to put it into practice
Explore a scenario. Discover its components and the decisions we work through together to turn it into a useful solution.
A reference for portals, APIs and containerized services. Cloud Run executes the application; Cloud SQL and Cloud Storage serve its data and file needs.
A reference pipeline that receives events, transforms data and prepares it for analysis. BigQuery and Looker bring that information closer to decision makers.
An assistant that retrieves information from authorized sources and uses it as context to generate answers. The application integrates Gemini, document retrieval and access controls.
Simplified references, not deployment diagrams. Connections, networking, permissions, availability and recovery are designed around each project’s requirements.
Engineering judgment in every decision
We use the six pillars of the Google Cloud Well-Architected Framework as a reference to review the solution and agree on improvement priorities with your team.
Explore Google Cloud Well-ArchitectedMonitoring, procedures and clear ownership to operate and improve.
Access, information protection and controls based on your requirements.
Availability, backups and recovery defined for each service.
Resources and design matched to workloads and response times.
Visible consumption, budgets and capacity reviews.
Efficient resource use and less unnecessary work.
A path from start to finish
Every stage connects a business decision to a verifiable technical outcome. We define scope, responsibilities and acceptance criteria from the start.
We review systems, data and objectives. We prioritize a use case and clarify dependencies, constraints and operational needs.
We define architecture, access and estimated consumption. We agree on a migration or development plan and how to validate the results.
We build in stages and verify integrations, data and behavior. We prepare for launch and recovery from failures.
We deliver documentation and training. We agree on monitoring, support and improvements based on real use of the solution.
Clarity before you begin
Yes. We review architecture, deployments, data, consumption and operations. Based on the findings, we agree on a prioritized plan to modernize applications, improve controls or extend capabilities while accounting for existing dependencies.
We inventory applications and data, assess dependencies and define a strategy for each workload. We agree on testing, change windows, validation and rollback. Where needed, we design a transition that lets the current environment and the cloud coexist.
We estimate infrastructure, storage, transfer and processing for the expected usage scenario. For analytics and AI, we include queries, models and execution frequency. We define budgets and consumption reviews; Google Cloud services and NewInntech’s work are itemized separately.
A concrete objective and authorized access to a relevant information sample. We review quality, permissions and constraints, then define a trial with criteria for evaluation, cost and human review. Integration and ongoing support are agreed upon within the project scope.
From possibility to the next step
An application, a data platform or a new use of AI? Tell us what you want to achieve and let’s design a path on Google Cloud.
Let’s talk about your project
