CloudGoBring a question worth answering.
Choose one cloud decision or workflow that your team is working through. A focused starting point makes it easier to see which context matters and how useful the output is.
- Choose the questionExamples include planning a modernization, prioritizing optimization work, or assessing an environment for risk and delivery effort.
- Bring relevant contextUse approved architecture, infrastructure information, internal standards, runbooks, and business priorities. Discuss access requirements before connecting an environment.
- Review the result with your teamCheck assumptions, inspect source context, and decide what needs validation. Use the output as a starting point for accountable human decisions.
Welcome to CloudGo.ai
Build and Evolve Cloud Infrastructure with Confidence
CloudGo.ai is a cloud intelligence platform designed to help teams analyze, plan, and execute cloud infrastructure work with accuracy and consistency. It is built for teams that need to make defensible infrastructure decisions and turn those decisions into reliable, repeatable delivery.
The platform operates in two complementary modes:
- Advisor, focused on analysis, recommendations, planning, and stakeholder-ready outputs
- Engineer, focused on execution, infrastructure generation, and operational artifacts
Together, these modes cover the full cloud infrastructure lifecycle, from early design decisions through production delivery and ongoing optimization across AWS, GCP, and Azure.
What CloudGo.ai Does
Analyze Existing Infrastructure
CloudGo.ai can connect to cloud environments using read-only access to understand what is actually running today. Instead of relying on manual documentation or tribal knowledge, teams get a current and objective view of their infrastructure state.
This enables teams to review architecture, configuration, and service usage; identify security, reliability, and compliance risks; detect cost inefficiencies and optimization opportunities; and surface configuration drift or inconsistent patterns across environments. CloudGo.ai then produces clear, structured summaries that work for both technical and non-technical stakeholders.
The result is a shared, up-to-date understanding of infrastructure without the overhead of manual audits or documentation.
Design New Architecture
CloudGo.ai supports early-stage and greenfield architecture work by helping teams move from high-level ideas to concrete, implementable designs.
Teams use it to explore architecture options for common workloads, compare services and patterns across cloud providers, and understand tradeoffs related to cost, reliability, and operational complexity. The platform produces architecture summaries, reference designs, and diagrams, and translates decisions into Terraform-ready plans.
This allows teams to make informed design decisions before committing to implementation.
Architecture Research and Decision Support
CloudGo.ai provides decision support grounded in authoritative and current sources, including official cloud provider documentation, service pricing and constraints, Terraform providers and resources, and well-architected and security frameworks.
This makes it useful for evaluating alternative services or deployment models, reviewing proposed designs before implementation, answering architecture questions with traceable sources, and supporting design reviews and internal approval processes.
Infrastructure Understanding and Mapping
CloudGo.ai builds a structured view of infrastructure state and relationships. It captures what services are deployed and where, how components interact across environments, and where data flows and trust boundaries exist.
This enables more precise answers and recommendations that reflect the realities of a specific environment rather than generic examples.
Advisor and Engineer: How the Product Is Used
CloudGo Advisor
Advisor is used when the primary goal is analysis and judgment rather than raw code generation. It supports architecture reviews, tradeoff analysis, migration and modernization planning, and cost, security, and SLA assessments. Advisor is also commonly used for SOWs, estimates, engagement planning, and customer-facing outputs such as reviews and QBRs.
Advisor outputs are structured, explainable, and designed to be shared with leadership, customers, and partners.
CloudGo Engineer
Engineer is used when teams need production-ready artifacts that can be executed, deployed, or operationalized. It generates Terraform projects and reusable modules, CI/CD pipelines and deployment workflows, runbooks and operational documentation, and infrastructure standards and templates.
Engineer outputs integrate directly into engineering workflows and support repeatable delivery across environments.
Why CloudGo.ai Is Different
CloudGo.ai is built specifically for cloud infrastructure work, not as a general-purpose AI assistant. Its analysis is based on real cloud environments accessed via read-only connections, and its recommendations are grounded in official provider documentation and up-to-date Terraform knowledge.
The platform includes built-in validation to reduce errors and unsupported configurations, and it maintains a clear separation between analysis in Advisor and execution in Engineer. This makes CloudGo.ai well suited for teams that need accurate, defensible infrastructure decisions and reliable implementation artifacts. Learn more about how CloudGo.ai compares to generic LLMs in our case study.
Who Uses CloudGo.ai
CloudGo.ai is used by teams across the organization, including platform and DevOps teams managing shared infrastructure, engineers designing and shipping new services, architects and technical leaders reviewing designs, and services teams supporting multiple customer environments. Finance and security teams also use it to assess cost and risk.
The platform supports both internal infrastructure teams and external service providers such as systems integrators and managed service providers. Learn more about the difference between Advisor and Engineer in our use cases page.
Plans and Capabilities
Advisor Plan
The Advisor plan is focused on analysis, planning, and decision support. It includes architecture reviews and recommendations, cost, security, and performance insights, cloud service comparisons, tradeoff analysis, Terraform guidance, and migration planning.
It is best suited for teams making frequent infrastructure decisions who need clear, well-supported guidance.
Engineer Plan
The Engineer plan includes everything in Advisor, plus execution-focused capabilities. It adds end-to-end Terraform generation, deployment workflows and CI/CD templates, validation across cost, security, and scaling concerns, and operational artifacts and documentation.
This plan is best suited for teams responsible for delivering and operating production infrastructure.
Getting Started
CloudGo.ai offers a free trial so teams can explore real infrastructure analysis and design workflows before committing. The goal is simple: help teams make better cloud infrastructure decisions and execute them with less risk and less rework.