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Multi-cloud visibilityCompliance mappingDrift detection

Turn cloud chaos into Control.

Cloud Explorer maps AWS, Azure, and GCP to frameworks like NIST & CIS, detects drift over time, and turns inventory + findings into evidence—without turning operators into full-time spreadsheet archeologists.

Unified inventoryDrift detectionControl evidenceGuardrailed AI

No install required. Early access supports bring-your-own-cloud integrations.

Stop turning cloud chaos into audit chaos.

The hard part isn’t collecting data—it’s turning it into evidence and keeping it true as environments change. Explorer Details shows how Cloud Explorer does that end-to-end.

Outcome
Faster decisions with evidence and traceability
Fabric
Topology + inventory as the source of truth
Action
Guided execution that stays auditable

What it is

Cloud Explorer transforms raw multi-cloud metadata into a living inventory and topology model, then layers explainable analysis and narrative output on top—so teams can understand what exists, how it connects, what it implies, and what actions are safe to take.

Security-first by design

Scoped access, traceable output, evidence-friendly workflows.

Relationships matter

Inventory isn’t enough—dependencies and trust paths reveal risk.

AI with guardrails

Summarize and explain; execution stays deterministic and policy-bound.

Architecture Diagrams

Evolution from original system view to governance-aware topology.

Original Architecture

Original Cloud Explorer architecture diagram

Governance-Aware Architecture (v2)

Cloud Explorer governance-aware architecture diagram

The updated architecture introduces a governance-aware topology model as the authoritative fabric, enabling explainable analysis and policy-bound execution.

Core System Model

Discovery → Mapping → Cognition → Narration → Visualization

Discovery Engine

  • Connects to provider APIs using scoped, time-bounded access
  • Enumerates inventory, identity, and policy metadata into snapshots
  • Feeds mapping continuously to support drift awareness

Mapping Engine

  • Normalizes inventory into a queryable model
  • Encodes governance semantics (permissions, tags, dependencies)
  • Becomes the fabric for evidence and visualization

Cognition Engine

  • Hybrid reasoning: deterministic checks + AI assistance
  • Compliance-aware interpretation (NIST/CIS/FedRAMP mappings)
  • Produces evidence-backed findings and recommendations

Narration Engine

  • Exec + technical summaries tied to evidence
  • Dialogue exploration (why is X risky?)
  • Reporting designed for audit workflows

Visualization Engine

  • Interactive inventory exploration (and topology where applicable)
  • Overlays for risk, drift, and compliance context
  • Narration links directly back to the underlying evidence

What it enables

  • Unified multi-cloud inventory with change awareness over time
  • Compliance-aware snapshots and control evidence generation
  • Queries like: “show internet-facing resources linked to non-compliant identities”
  • Summaries that stay tethered to evidence (not vibes)

Cloud Explorer