Cloud Assistant for governed automation
Use natural language to provision services, investigate incidents, optimize cost, and tighten security posture without forcing operators through brittle manual runbooks.
Deployment blueprint
What teams get on day one
Natural language to infrastructure plans
Describe the environment you need and get an actionable deployment plan with dependencies, cost signals, and rollout guidance.
Automated troubleshooting loops
Ask about latency spikes, error surges, or failing services and receive evidence-backed triage suggestions across logs, metrics, and configs.
Cost optimization recommendations
Surface rightsizing, idle-resource, and storage-tier opportunities with concrete savings estimates instead of generic advice.
1 prompt
to launch common workflows
40%
fewer repetitive ops tasks
24/7
policy-aware guidance
5 min
to first action plan
Core capabilities
Purpose-built for modern engineering teams
Natural language to infrastructure plans
Describe the environment you need and get an actionable deployment plan with dependencies, cost signals, and rollout guidance.
Automated troubleshooting loops
Ask about latency spikes, error surges, or failing services and receive evidence-backed triage suggestions across logs, metrics, and configs.
Cost optimization recommendations
Surface rightsizing, idle-resource, and storage-tier opportunities with concrete savings estimates instead of generic advice.
Security and compliance posture review
Continuously inspect cloud configurations against internal controls and external frameworks with remediation priorities attached.
Guardrailed operator actions
Require approvals or policy checks before high-impact actions so AI assistance speeds work up without bypassing governance.
Unified operating memory
Retain decisions, infrastructure changes, and past incidents so future recommendations stay aligned with how your platform actually runs.
Delivery flow
How teams adopt cloud assistant
The platform is designed to reduce setup friction, standardize delivery, and give every team a clear operating model from day one.
Describe the task in operator language
Use plain English for provisioning, diagnostics, or optimization requests without translating them into multiple tool-specific commands first.
Review the generated execution plan
Inspect the proposed changes, dependencies, approval gates, and expected outcomes before any action is taken.
Execute with telemetry and policy checks
Run approved actions while the platform records operator context, validates constraints, and reports the outcome back to the team.
Use cases
High-impact scenarios teams run on VxCloud
Self-service platform requests
Let application teams request environments, data services, or access paths through a governed AI interface instead of filing slow manual tickets.
FinOps and platform reviews
Regularly assess spend, idle assets, and scaling policies with AI support that understands architecture context and business priorities.
Security operations support
Accelerate remediation planning for exposed resources, risky IAM patterns, and compliance drift across cloud accounts.
Integrates with your existing stack
Bring current tooling forward instead of rebuilding workflows. Standard integrations are available immediately, with deeper automation on top.
Operator outcome
Teams get a sharper developer loop, stronger governance, and a cleaner production handoff without adding separate point tools to manage.
Build the next workflow on top of Cloud Assistant
Start in minutes with VxCloud-managed infrastructure, AI-assisted setup, and a production-ready baseline your team can extend safely.