The answer is somewhere.
Your team has to find it.
Diagrams, runbooks, IaC, cost reports. Valuable on their own. Hard to reason across together.
THE CLOUD KNOWLEDGE LAYER FOR PEOPLE + AI
Your cloud. Understood.
CloudGo gives your people and AI the cloud context to plan faster, review the evidence, and reuse what they learn. One knowledge layer connects your infrastructure, company standards, and decision history.
Less repeated work. Traceable decisions. Knowledge that carries forward. Explore the knowledge layer
Reduce cloud wasteIdentify and eliminate unnecessary spend across your infrastructure
De-risk cloud decisionsMake confident, data-backed architectural choices every time
Standardize best practicesEnforce consistent cloud patterns across every team and project
CloudGo WorkspaceAC
FROM CONTEXT TO CLARITY
One question. The full picture.
GROUNDED IN YOUR CONTEXT
Start with the dependencies.
Move with a plan.
Keep the shared database in place for wave one. Move stateless services first, with rollback checkpoints at every stage.
Explore this workflow The evidence, connected
01
Architecture overviewShared database dependency
02
Release runbookRollback and change windows
03
Business prioritiesCustomer availability first
Sources and constraints you can review.
Connected knowledge. Shared understanding.Context that carries forward
Grounded in your environment.
Connected to your cloud.
aws⌣Microsoft AzureG Google Cloud Terraform Your knowledge
Trusted by innovative organizations
THE CONTEXT GAP
Your AI knows the cloud.
Does it know your cloud?
Your team already uses AI. But the architecture is in one place, the decision history is in someone’s head, and the business constraints are in another document. Every new task starts with rebuilding context.
The answer is somewhere.
A plausible answer
isn’t a workable plan.
Recommendations need to account for your dependencies, internal standards, and business priorities.
The next project
starts from scratch.
Decisions lose their history across chats, tools, and handoffs. Your organization keeps relearning what it already knows.
MEET YOUR SHARED KNOWLEDGE LAYER
Your knowledge.
A compounding advantage.
Built specifically for cloud decisions, CloudGo connects provider expertise with your organization’s knowledge—and preserves the context behind your decisions.
- Knowledge graph What your organization knows
- Infrastructure, dependencies, provider guidance, and internal standards, connected.
- Context graph What your team learns
- Conversations, constraints, and recorded decisions that carry into the next project.
CLOUD KNOWLEDGE + DECISION CONTEXTOne foundation. People + AI.
WHAT CONNECTED CONTEXT CHANGES
Less reconstruction. More progress.
Spend less time assembling context, make review easier, and put past decisions to work.
Get to a useful plan faster.
Bring infrastructure, internal standards, and business goals together so every task starts with the context it needs.
Less time rebuilding the background
Make review easier.
Connect a recommendation to its sources, constraints, and assumptions so experts can assess whether it fits.
Evidence your team can review
Let expertise carry forward.
Keep conversation and decision context available for the next person, project, or AI workflow.
Less repeated explanation and rework
ONE FOUNDATION. TWO WAYS TO USE IT.
In your team’s hands.
Inside your existing AI.
The same cloud knowledge and decision context powers both. Use the Scale workspace or scope a Context integration with the AI tools your team already uses.
CloudGo ScaleFOR YOUR PEOPLE
Your cloud decision
workspace.
From assessment to architecture to an implementation plan, give your team a shared place to work through what comes next.
PLATFORM MODERNIZATIONFrom analysis to alignment.
Technical implementation plan ↗
Executive business case ↗
Risk & rollback plan ↗
CloudGo ContextFOR YOUR AI
Your knowledge layer.
Your tools. Your way.
Explore an API integration that gives your copilots, agents, and internal applications the organizational context they need.
CloudGo ContextCloud knowledge + decision context
CopilotsAI agentsInternal tools
FOR TEAMS ALREADY PUTTING AI TO WORK
For the leaders and teams
turning AI into delivery.
CTOs & cloud teams
Make cloud and AI investment accountable. Review cost, risk, and delivery tradeoffs with the evidence behind each recommendation.
Turn complexity into a planConsultancies, MSPs & SIs
Apply your methodology across engagements. Give senior experts the context and evidence to review more delivery work.
Scale the reach of your expertiseAI & engineering teams
Ground existing agents and copilots in your cloud knowledge. Reuse sources and decision context as your tools evolve.
Put your knowledge inside your AICLOUDGO IN PRACTICE
From complex questions
to concrete plans.
BERNERINDUSTRIAL IoT · AWSCLOUDGO / CUSTOMER STORY
AWS AUDIT & MODERNIZATION
A phased AWS remediation roadmap, delivered in days.
Berner International used CloudGo to connect the dots across its AWS IoT platform and turn hidden dependencies, security gaps, and cost drivers into an actionable plan.
Read the storytelosDEVELOPER TOOLS · AWSCLOUDGO / CUSTOMER STORY
MIGRATION PLANNING
An AWS migration plan in one day. A clearer decision on when to move.
Telos needed to understand how to scale beyond Render, and when a move to AWS would become economical. CloudGo connected the architecture decision to the growth and cost model.
Read the storyspread
goodness®EDUCATION TECHNOLOGY · GCPCLOUDGO / CUSTOMER STORY
goodness®EDUCATION TECHNOLOGY · GCPCLOUDGO / CUSTOMER STORY
GCP AUDIT & GOVERNANCE
From GCP governance gaps to a phased improvement roadmap.
Spread Goodness® used CloudGo to understand authentication, third-party data flows, and monitoring across an evolving education platform.
Read the storyMEASURED IN OUR TOKEN-EFFICIENCY STUDY
Turn traditional LLMs into cloud architects.
CloudGo.ai’s intelligent context management dramatically reduces token usage while delivering more accurate results on cloud planning tasks.
Token usage comparison
46%Fewer tokensSame cloud task, half the cost
Lower costs
~46%Comparable reduction in API costs compared to Claude + MCP servers.
Fewer messages
1 turnCloudGo completed every benchmark in a single turn, versus 4.4 for ChatGPT and 8.8 for Claude.
Better responses
3x more sourcesCloudGo provides 3 times more cited sources per recommendation.
Based on identical infrastructure planning tasks across 20 benchmark runs. Read the study
CLARITY YOU CAN EXPLAIN
Don’t just get
a recommendation.
Understand why.
Trace a recommendation to its source and the constraint that shaped it. Review the assumptions, apply your priorities, and keep a record of the decision. Give your team the evidence to explain and stand behind its work.
See how the evidence connectsDECISION RECORD / EXAMPLE
Keep customer data in-region.
The proposed architecture follows the residency requirement in your internal data policy.
Internal data policy · § 4.2
“Customer records must remain within the approved region.”Illustrative source excerpt
SourceConstraintRecommendation
FROM THE PEOPLE USING IT
Why people love CloudGo.ai
See what industry leaders are saying about our platform.
“CloudGo.ai helped our portfolio companies launch faster, scale effortlessly, and secure funding more easily. It's been a game-changer for startups.”
Lucas PolsGP of Pegasus Angel Accelerator
“CloudGo.ai helps me explore new ideas and always provides the latest answers and insights, it's an essential tool for anyone serious about turning concepts into successful products.”
Leonidas KontothanassisSr. Director of Engineering at Google
“CloudGo.ai helped us cut our Supabase-to-AWS migration from weeks to days. No external contractors needed. As a bonus, it gave us clean cost and recurring-spend projections we could drop straight into our financial model during fundraising.”
Blake PickellVP of Enterprise Products at GoodRX
EXPLORE USE CASES
See how our AI agent helps teams
analyze and design cloud architectures.
January 29, 2026CloudGo.ai Capabilities
How to unlock the full potential of CloudGo.ai: what it does out of the box, and what changes when you connect your cloud and documentation.
Read moreDecember 22, 2025CloudGo.ai vs Generic LLMs
A decision-grade comparison of CloudGo.ai, Claude, and Cursor for cloud infrastructure planning, migration, and validation.
Read moreDecember 30, 2025Consultancy Use Cases
CloudGo.ai use cases for systems integrators, MSPs, and consultancies.
Read moreCLOUDGO.AI FAQS
Answers to common questions.
How CloudGo.ai helps with cost, risk, Terraform, and getting started.
How does CloudGo.ai help reduce cloud costs on AWS, GCP, or Azure?
CloudGo.ai helps you identify major cloud cost drivers and find practical savings opportunities before you make changes. We can review your cloud architecture, highlight likely waste (like overprovisioned compute, idle resources, or expensive patterns), and recommend a prioritized cost optimization plan. If you connect your cloud account credentials, CloudGo can give more specific guidance based on your actual environment.
Can CloudGo.ai audit my existing cloud architecture for risk and reliability?
Yes. CloudGo.ai is built to help you optimize and de-risk an existing cloud environment. We can review your architecture for common reliability and operational risks, such as single points of failure, weak backup strategies, limited observability, or scaling bottlenecks, and then give you a step-by-step improvement plan based on your priorities.
Does CloudGo.ai monitor my cloud and automatically fix issues?
CloudGo.ai is primarily an AI cloud advisor for planning, auditing, and decision support. It helps you diagnose issues, evaluate tradeoffs, and create action plans for cost, performance, and reliability. It does not replace your runtime monitoring stack, but it can help you decide what to improve and what to implement next.
Can CloudGo.ai help with Terraform and infrastructure as code?
Yes. CloudGo.ai can help you plan and structure infrastructure as code workflows, recommend Terraform module patterns, and generate Terraform guidance/snippets for AWS, GCP, and Azure. For teams that need full Terraform project generation or repo-level validation workflows, those are available in higher-tier CloudGo.ai plans.
How technical do I need to be to use CloudGo.ai?
CloudGo.ai is designed for both technical and non-technical users. Founders, product teams, and engineers can use it to get clear cloud guidance without needing deep cloud expertise upfront. If you already have a DevOps or platform team, CloudGo also helps speed up architecture reviews, cloud audits, and infrastructure planning.
What information should I share to get the best cloud audit results?
To get started quickly, share your primary cloud provider (AWS, GCP, or Azure), your top goal (reduce cloud spend, improve performance, or reduce risk), and a rough sense of your environment (production stage, key services, or monthly cloud spend range). You can also connect cloud credentials if you want a deeper, environment-specific review.
Why choose CloudGo.ai instead of a generic AI assistant or cloud chatbot?
CloudGo.ai is focused specifically on cloud architecture, cloud optimization, and infrastructure planning. Instead of generic answers, it is designed to guide you through real cloud decisions—like cost optimization, reliability improvements, provider strategy, and infrastructure-as-code planning—across AWS, GCP, and Azure.
ONE WORKFLOW. A MEASURABLE START.
Start with a project.
See the difference.
Revisit a past assessment or migration plan. Compare delivery time, review effort, and traceability against your current approach.
Plan your evaluation