AWS, Azure & GCP inventory in seconds. 65+ production agents (scaling to 180) that discover, prioritize, and fix issues across your cloud, AI, GPU, and automation estate.
Cloud teams already use CSPM, CNAPP, CIEM, FinOps, observability, and DR tools. All of them excel at showing problems — but very few help fix them.
Thousands of "critical" findings stay open
Shadow AI endpoints and GPU spend spike unpredictably
Automation agents drift out of policy
Tool sprawl → more noise, not more progress
Posture stagnation → audit panic → board frustration
Tools tell you what's wrong. CloudDiscovery tells you what to fix first — and helps you fix it.
Multi-cloud + AI inventory in under a minute.
Full visibility across:
CloudDiscovery's 65+ production agents continuously analyze your estate across:
Each issue is scored by:
risk × blast radius × exploitability × cost impact × AI impact × effort to fix
Outcome:
A short list of the 20 fixes that move the needle.
resource "aws_s3_bucket" "data" {
- acl = "public-read"
+ acl = "private"
+ block_public_acls = true
}CloudDiscovery generates:
Then:
Apply with one click — or route to your existing workflows.
"12-week cloud assessment → completed in minutes."
Comprehensive coverage across every cloud domain
¹65 agents in production, more released weekly
Misconfig detection, toxic permission analysis, path-based risk scoring, automation-agent drift, shadow AI discovery.
Idle resources, rightsizing, GPU scheduling, AI inference & training drift, spend attribution by team.
Well-Architected alignment, SPOF detection, DR posture, workload right-sizing, AI pipeline reliability.
SOC2/ISO/PCI mapping, AI governance baselines, automated evidence generation.
SLO coverage, observability gaps, alert noise analysis, dependency mapping.
Data sprawl detection, segmentation, network path exposure, cross-cloud relationships.
One map. One backlog. Unified remediation.
Clear visibility into risk, spend, AI usage & improvement velocity.
Cloud & AI attack surface clarity. Evidence-backed posture improvement.
Reduced toil. Ready-to-deploy fixes. Faster, safer delivery.
Cost attribution across teams and AI workloads. Rightsizing & GPU optimization.