Sign inContact Us
AgenticOps platform

Autonomous agents for cloud infrastructure — under your policy

CloudThinker deploys autonomous AI agents that detect, analyze, remediate, and verify production cloud operations — with brokered credentials, sandboxed execution, deterministic tokenization, and tamper-evident audit. You set the policy; engineers stay on the loop.

Start freeBook a Demo

Connect a read-only account

The problem

Cloud operations doesn't scale by adding more on-call

Every layer of tooling makes the signal louder. None of them close the loop from problem to verified fix without a human doing the work.

The alert firehose outgrew the team

Observability and AIOps compress signal into alerts, but a human still investigates, decides, and acts on every one. MTTR stays bottlenecked on the person in the loop.

Static scripts break when reality drifts

Runbook automation runs a fixed sequence and gives up the moment the environment doesn't match. The judgment calls fall back to on-call, at 3am, again.

'Autonomous' usually means 'unsafe'

Handing an agent standing keys and prod access is a security incident waiting to happen. Without brokered credentials and audit, autonomy is a liability, not leverage.

The DARV loop

A closed loop from problem to verified fix

Every CloudThinker agent runs the same four-step loop. It's what turns a raw signal into a reversible, audited production change — automatically.

D

Detect

Agents ingest signal from your existing observability, cost, and security tools, cluster the noise, and surface what actually needs action.
A

Analyze

They reason about root cause across the dependency graph, pull context and prior incidents from memory, and pick the matching remediation.
R

Remediate

Inside a sandbox, with brokered credentials, they execute the fix — a scaled resource, a rolled-back deploy, a right-sized instance — within your guardrails.
V

Verify

They confirm the fix held, roll back if it didn't, and write a tamper-evident receipt so you review the outcome, not every keystroke.

New to the model? Read what the DARV loop is and what AI SRE means.

Graduated autonomy

You decide how much rope each agent gets

Autonomy isn't a switch — it's a dial. Promote each capability one level at a time as it earns trust, per environment, with a hard approval gate at every step.

L1

Observe & recommend

Agents watch and propose. Zero write access. This is where every capability starts.
L2

Draft for approval

Agents prepare a scoped remediation as a reviewable change. A human clicks approve before anything runs.
L3

Act within guardrails

Agents execute low-risk, reversible actions inside a defined boundary — and page a human for anything outside it.
L4

Autonomous playbooks

Trusted playbooks run end-to-end without a human in the path — each one leaving a tamper-evident receipt.

More on the model: graduated autonomy and engineers on the loop.

Governance by default

What makes autonomy safe against production

These controls aren't add-ons — they're the substrate every CloudThinker agent runs on. It's the difference between an agent you can trust with prod and one you can't.

Brokered credentials

No standing keys. Scoped, short-lived credentials are issued per task and live in the sandbox, never in the prompt.

Learn more

Sandboxed execution

Every action runs in an isolated environment with a bounded blast radius — not directly against your control plane.

Learn more

Deterministic tokenization

Sensitive data is tokenized deterministically before it ever reaches an LLM, keeping PII and secrets out of model context.

Learn more

Tamper-evident audit

Every agent action produces an immutable receipt — who, what, when, and why — ready for review and compliance.

Learn more

Outcomes

What teams get when agents close the loop

The point isn't automation for its own sake — it's shifting engineers from running operations to supervising them.

Faster time-to-resolution

Parallel investigation and memory of prior incidents mean the loop closes without waiting on the person who paged in.

Less toil, fewer 3am pages

Recurring, well-understood work graduates to autonomous playbooks, so on-call gets the exceptions instead of the routine.

Audit-ready by construction

Because every action is brokered and receipted, the evidence trail for security and compliance is a byproduct, not a project.

Specialist agents

Adopt one workflow at a time

CloudThinker ships purpose-built agents for the highest-toil workflows, all on the same governed platform. Start where the pain is worst.

Resolve

Incident response and AI SRE — detect, investigate, and resolve production incidents with memory that compounds.Explore

CloudKeeper + CostOps Agent

Continuous rightsizing and cloud cost control — find and safely apply savings without a spreadsheet marathon.Explore

Oliver + Cyber

Security operations — surface, prioritize, and remediate exposures across your cloud and code under the same governance.Explore

See the whole picture: the CloudThinker platform and what AgenticOps is.

FAQ

Questions teams ask before they connect

What are autonomous agents for cloud infrastructure?

Autonomous agents for cloud infrastructure are AI agents that detect, analyze, remediate, and verify production cloud operations without a human driving every step. CloudThinker runs them under team policy: each agent works through the DARV loop (Detect, Analyze, Remediate, Verify), uses brokered per-task credentials, executes inside a sandbox, tokenizes sensitive data deterministically at egress, and writes a tamper-evident audit record. Engineers stay on the loop — they set policy and review outcomes rather than running every command by hand.

How is this different from a runbook automation or an observability tool?

Observability tools collect telemetry and AIOps tools compress it into alerts — both stop at surfacing a problem for a human to act on. Static runbook automation runs a fixed script but cannot reason when reality drifts from the script. CloudThinker agents take the alert as input, reason about root cause, choose and execute the matching remediation inside a sandbox, then verify the fix held. It carries the work through to a reversible, approved production change instead of stopping at a dashboard.

Can I control what the agents are allowed to do?

Yes. CloudThinker uses graduated autonomy across four levels. At L1 agents observe and recommend only; at L2 they draft a remediation for human approval; at L3 they execute low-risk, reversible actions within a defined guardrail and page a human otherwise; at L4 they run approved playbooks autonomously with an audit receipt. You promote each capability one level at a time as it earns trust, and every level is bounded by per-environment approval gates.

How do you keep credentials and sensitive data safe?

Agents never hold standing keys. Credentials are brokered per task — scoped, short-lived, and issued at execution time — and they live inside the sandboxed environment, not in the prompt. Any sensitive data leaving that environment is tokenized deterministically before it reaches an LLM, and every action produces a tamper-evident audit record. This is what makes autonomous action safe enough to run against production.

Which parts of cloud operations can CloudThinker agents handle?

CloudThinker ships specialist agents for the highest-toil workflows: the Deep Response Engine for incident response and AI SRE, CloudKeeper with the CostOps Agent for cloud cost, Kai for Kubernetes operations, and Oliver with Cyber for security. Assessment maps your environment and Connections wires the agents to your existing tools. You adopt one workflow at a time rather than replacing your whole stack.

How do we get started?

Connect a read-only account and let CloudThinker run an Assessment of your environment — no changes are made until you promote a capability past L1. Most teams start with a single high-toil workflow (incident response or cost) in observe-only mode, review the receipts, then graduate autonomy as trust builds. You can start free in the app or book a demo to see it run against a scenario like yours.
Put agents on your infrastructure

Run autonomous agents against production — safely.

Start in observe-only mode, review the receipts, and graduate autonomy on your terms. Engineers stay on the loop the whole way.

  • No standing credentials
  • Tamper-evident audit
  • Start free, no rip-and-replace
Book a DemoStart Trial