Google Cloud Platform
Google Cloud AI tools.
Your GCP dashboard builder.
Anything you can do in gcloud, your agent can do for you. Spin up instances, manage firewall rules, analyze billing, and optimize resources — all through conversation.
Every GCP service. One conversation.
camelAI connects to the GCP API and manages your infrastructure the same way you would — just faster. No context switching, no memorizing flags.
Compute Engine
Spin up, resize, or shut down VMs with a sentence.
Cloud Run
Deploy containerized services in seconds.
Cloud Storage
Manage buckets, permissions, and lifecycle rules.
BigQuery
Query petabytes. Build dashboards. Analyze anything.
Pub/Sub
Create topics, manage subscriptions, route events.
Cloud Functions
Deploy serverless functions from a chat message.
VPC & Firewall
Configure networks, subnets, and firewall rules.
IAM & Admin
Audit permissions, manage service accounts, enforce policies.
Replace 17 lines of gcloud with one sentence.
No more hunting for flags, remembering zone names, or chaining commands. Describe what you want.
$ gcloud compute instances create prod-api-v3 \--zone=us-central1-a --machine-type=e2-standard-4 \--image-family=debian-12 --image-project=debian-cloud \--boot-disk-size=100GB --boot-disk-type=pd-ssd \--network-interface=network=prod-vpc,subnet=api-subnet \--tags=http-server,https-server \--service-account=api-sa@proj.iam.gserviceaccount.com \--scopes=cloud-platform$ gcloud compute firewall-rules create allow-api-ingress \--network=prod-vpc --direction=INGRESS \--action=ALLOW --rules=tcp:443,tcp:8080 \--target-tags=http-server,https-server \--source-ranges=0.0.0.0/0$ gcloud compute instances add-metadata prod-api-v3 \--zone=us-central1-a \--metadata=startup-script="#!/bin/bash..."
“Spin up a new e2-standard-4 instance called prod-api-v3 in us-central1 on the prod-vpc api-subnet. Use Debian 12, 100GB SSD boot disk. Open ports 443 and 8080. Use the api-sa service account.”
Your infrastructure. At a glance.
camelAI builds you a custom infrastructure dashboard — not a generic monitoring view, but exactly what your team needs to see.
Instances
23
18 running
Cloud Run
12
all healthy
Monthly Spend
$11,000
+4.2% vs last
Alerts
3
1 critical
See where every dollar goes.
GCP billing exports are powerful but unreadable. camelAI turns them into dashboards your finance team will actually use.
Monthly Spend
$11,000
+4.2%Savings Identified
$2,535
23% of totalCost per User
$3.42
-12% vs Q3Spend by Service
March 2026Stop paying for resources you're not using.
Set up a nightly cron audit of your GCP resources. camelAI finds idle VMs, oversized instances, and unused storage — then tells you exactly how much you can save.
Total potential savings identified
Based on 14-day resource utilization analysis
$2,535/mo
4 idle VMs detected
dev-sandbox, test-runner-02, staging-old, and qa-legacy have had <2% CPU for 14+ days. Shutting them down saves $187/mo.
Projected savings
$187/mo
3 instances oversized
batch-processor, analytics-worker, and etl-runner are using <30% of allocated resources. Right-sizing to the next tier down saves $412/mo.
Projected savings
$412/mo
Committed use discounts available
5 instances have been running for 90+ days at stable utilization. A 1-year commitment on these saves 37% — approximately $1,840/mo.
Projected savings
$1,840/mo
Unused persistent disks
8 persistent disks (total 2.4TB) are not attached to any instance. Deleting or snapshotting saves $96/mo in storage costs.
Projected savings
$96/mo
Schedule a nightly cron job: “Every night at 2 AM, audit all GCP projects, flag waste, and send a summary to #infra on Slack.”
Already using BigQuery?
Our BigQuery page covers data-specific use cases — warehouse queries, live dashboards, and enterprise analytics. GCP infrastructure management and BigQuery analytics work even better together.
What will you build for your cloud?
“Connect to our GCP project and build a cost dashboard. Break down spend by service and project, show month-over-month trends, and flag any anomalies over $500. Set up daily cron updates.”
Try this prompt“List all Compute Engine instances across our three GCP projects. Flag any that have been running for 30+ days with less than 10% CPU. Give me right-sizing recommendations.”
Try this prompt“Deploy a new Cloud Run service from our container registry. Set min instances to 2, max to 20, and configure it with the prod-api service account. Open it to internal traffic only.”
Try this prompt“Audit our firewall rules across all VPCs. Find any rules that allow 0.0.0.0/0 ingress on non-standard ports and generate a security report with recommendations.”
Try this promptEnterprise-ready from day one.
Built for teams that take security, compliance, and cost governance seriously.
Authenticate with a service account key or Google OAuth. Credentials are encrypted at rest and never leave your organization's boundary.
camelAI respects your existing IAM policies. The agent can only do what the service account allows — principle of least privilege, enforced.
Every API call logged with user identity, timestamp, and affected resources. Integrates with Cloud Audit Logs for compliance.
Keep traffic within your security perimeter. camelAI supports Private Google Access and VPC-SC for the most sensitive workloads.
Manage multiple GCP projects from a single camelAI workspace. Switch context, compare costs, and enforce standards across your org.
Set per-project budget caps and get alerts before spend exceeds thresholds. camelAI won't provision resources beyond your limits.
23 instances. 12 services.
3 projects. One conversation.
Your entire Google Cloud — managed by AI.