CloudGo.ai Capabilities

Cloud decisions need a shared foundation.

CloudGo connects infrastructure context, architecture, documentation, provider guidance, and business priorities. Teams can use that foundation to assess an environment, explore tradeoffs, and develop plans.

Understand your environmentMap the relationships and constraints behind a cloud decision. Use connected context to surface the questions that matter before you choose a path.
Turn analysis into a planDevelop architecture options, migration sequences, cost assumptions, risk controls, and role-specific outputs that teams can review.
Explore context for your own AICloudGo Context supports a scoped conversation about supplying organizational knowledge to existing copilots, agents, and internal tools.

This document outlines how to unlock the full potential of CloudGo.ai.

How Connected Data Sources Transform Your Cloud Intelligence

CloudGo.ai provides intelligent cloud infrastructure guidance out of the box. But the more context you provide, the more powerful and personalized that guidance becomes. This document explains what CloudGo.ai can do at each level of integration, from standalone use to fully connected cloud environments and company documentation.

What CloudGo.ai Does Without Any Connections

Even without connecting external data sources, CloudGo.ai offers substantial cloud expertise. Our platform includes a curated knowledge base covering AWS, Azure, and GCP documentation, including Well-Architected Frameworks, service FAQs, pricing guides, migration whitepapers, and prescriptive guidance. We also maintain a Terraform Knowledge Graph with indexed provider documentation and module configurations across all major cloud providers.

With just a natural language prompt, CloudGo.ai can:

Research cloud services
Compare options, explain trade-offs, and recommend architectures based on your described requirements.
Generate Terraform scaffolding
Produce infrastructure-as-code templates for common patterns, validated against security best practices.
Plan migrations
Provide generic migration playbooks for common source-to-target scenarios (e.g., BigQuery to Redshift, GKE to EKS).
Answer technical questions
Explain cloud concepts, troubleshoot configurations, and clarify service capabilities.

This is useful, but it’s inherently generic. CloudGo.ai doesn’t know your actual infrastructure, your financial commitments, your team’s skills, or your contractual constraints. The recommendations are technically sound but may not account for your organizational reality.

Connecting Your Cloud Environment

When you connect CloudGo.ai to your cloud environment via read-only CLI credentials, the platform gains the ability to see your actual infrastructure; not simply what you describe, but what truly exists.

What We Can Access (and what we can’t)

CloudGo.ai’s cloud execution agent uses read-only CLI access (gcloud, aws, az) to retrieve:

Infrastructure inventory: Compute instances, clusters, databases, storage buckets, networking configurations, and service deployments
Usage telemetry: CPU/memory utilization, query volumes, storage access patterns, and API call frequencies
Cost and billing data: Current spend by service, committed use discounts, reserved instance utilization, and savings plan coverage
Security posture: IAM configurations, service account permissions, network exposure, and encryption settings

What This Enables

With cloud environment access, CloudGo.ai moves from theoretical recommendations to grounded analysis.

Without Cloud Connection

"You should optimize your BigQuery costs"
"Consider your existing commitments before migrating"
"Plan for data transfer costs"

With Cloud Connection

"Your BigQuery spend is $54.8K/month, with 80% on internal analytics. Here are three specific queries to optimize."
"You have $180K remaining on GCP committed use discounts. Migrating now forfeits that value."
"You have 520 TB in US regions and 120 TB in EU regions. Here's a phased transfer plan with cost estimates."

For migrations between cloud providers, you can connect multiple environments simultaneously. This gives CloudGo.ai complete visibility into both your source and target infrastructure, enabling precise migration planning that accounts for actual resource configurations, not assumptions.

Connecting Your Company Documentation

Cloud environment data tells CloudGo.ai what your infrastructure looks like. Company documentation tells CloudGo.ai why it looks that way, and what constraints shape your decisions.

When you upload documents to CloudGo.ai, they are embedded into a secure, isolated Qdrant vector database. Each customer’s documentation exists in a private collection with no cross-tenant access. During analysis, CloudGo.ai queries this collection to retrieve relevant context that informs its recommendations.

Documentation Types: From Most to Least Critical

While we can ingest any and all data formats you elect to give us, not all documentation is equally valuable for cloud decisionmaking. The following categories are ranked by their typical impact on recommendation quality.

Tier 1 — High-Impact Documentation

Customer Contracts and SLAs
Enables CloudGo.ai to identify which services specific customers actually access, allowing targeted migration or optimization that satisfies contractual requirements without unnecessary scope expansion.

Billing and Financial Commitments
Enables CloudGo.ai to factor financial obligations into migration timing and avoid forfeiting committed-use discounts.

Architecture Decision Records (ADRs)
Helps CloudGo.ai understand why past decisions were made and prevents recommendations that repeat past mistakes or ignore institutional knowledge.

Tier 2 — Important Supporting Documentation

Team Skills Assessments
Helps CloudGo.ai recommend technologies your team can actually operate.

Data Governance Policies
Helps CloudGo.ai identify regulatory constraints on data movement and residency.

Vendor Integration Documentation
Helps CloudGo.ai surface hidden timeline dependencies that shape realistic migration timelines.

Tier 3 — Valuable Context

Incident Postmortems
Allows CloudGo.ai to incorporate operational history and lessons learned from past outages.

Runbooks and Operational Procedures
Helps CloudGo.ai align recommendations with your existing operational patterns.

Internal Technical Standards
Ensures generated Terraform, account structures, and configurations conform to your established conventions.

How We Keep Your Data Safe

We know that connecting cloud environments and uploading internal documentation requires trust. Here’s how CloudGo.ai protects your data:

Read-only cloud access
Our cloud execution agents operate exclusively with read-only CLI credentials. They can observe your infrastructure but cannot modify, create, or delete any resources.
Isolated vector collections
Each customer’s documentation is embedded into a dedicated Qdrant collection with no cross-tenant access.
No human access
Your cloud data and documentation are processed by CloudGo.ai agents. CloudGo.ai staff do not review customer data.
You control the connection
You can revoke cloud CLI access or delete your documentation collection at any time.

Get Started Right Here

Ready to unlock CloudGo.ai’s full potential? Choose your starting point here:

Connect your cloud environment
Link your AWS, GCP, or Azure CLI credentials for infrastructure-aware recommendations.
Upload company documentation
Add contracts, ADRs, policies, and other documents to your secure collection.
Do both
For the most powerful experience, connect your cloud environment and upload relevant documentation. CloudGo.ai will synthesize both to deliver recommendations that are technically sound, financially aware, and organizationally realistic.

Questions about data security or integration options? Contact our team at support@cloudgo.ai.