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Governed automation control plane

Ship infrastructure changes fast.
Prove control at every step.

Cantilever-Engineering is an intelligent service catalog spanning every orchestration layer, service management, observability and FinOps tool you run — bound to a single Zero Trust, policy-enforced framework. Every run is identity-scoped, policy-checked and audit-ready before anything touches production — and agentic AI scores the risk before you approve it.

See the full integration coverage

Overlay model — keep the tools you already own · Customer-managed, SaaS or hybrid · Air-gapped capable

governed run · deploy-prod
cantilever run deploy-prod --service payments-api --env prod resolving inventory… MCP inventory.lookup aws+azure+k8s owner=platform-eng tier=critical terraform plan +12 ~3 -0 OPA/Rego tenant-isolation.rego ALLOW OIDC identity verified · JIT role issued ttl=15m change window + CMDB CI check PASS ansible aap job cfg-prod-221 site.yml complete servicenow RITM-4829101 → CHG-903344 approved datadog deploy monitor OK · SLO burn stable evidence bundle exported to audit timeline
Governs what you already run
Terraform Ansible AAP GitHub Actions GitLab CI Harness ServiceNow Jira HashiCorp Vault OPA / Rego Datadog Splunk Kubernetes Infracost Cloudability
The problem

Speed and control are fighting, and control is winning slowly.

Most enterprises did not buy a bad toolchain. They bought eight good ones. What is missing is the layer that makes them answer to a single policy.

01

Automation sprawl

Playbooks in three repos, pipelines in two CI systems, a Terraform module nobody owns. Every team automates; nobody can say what runs where, or who approved it.

02

Standing privilege

Long-lived service accounts and static credentials sit in pipelines because rotating them breaks deploys. Your Zero Trust programme stops at the CI runner.

03

Audit as archaeology

Evidence gets reconstructed after the fact from logs, Slack threads and change tickets that were filled in retroactively. Every audit costs weeks of engineering time.

How it works

One path from request to governed execution.

Three control points, applied to every run regardless of which engine does the work.

Step 01

Request from the catalog

Engineers pick a versioned, parameterised catalog item instead of running an engine CLI. Inventory context resolves automatically — owner, tier, environment, dependencies.

  • Parameter validation and mandatory inputs
  • Live multi-cloud + Kubernetes inventory targeting
  • Natural-language intent translated to a structured plan
Step 02

Govern before execution

CIPF evaluates identity, scope and policy before anything runs. A failed gate blocks the run and returns a structured violation report with remediation guidance.

  • OIDC/SAML identity + JIT least-privilege role
  • OPA/Rego checks against the Terraform plan
  • AI risk score and blast-radius estimate
Step 03

Prove it afterwards

Execution produces an immutable record linking identity, permissions, policy decisions, inputs, outputs and the ITSM change — automatically, as a by-product of running.

  • ServiceNow RITM/CHG and Jira issue linkage
  • Datadog deploy events and SLO burn on the timeline
  • Exportable evidence bundles for SOC 2, FedRAMP, ISO 27001
60+
catalog-delivered capabilities across 13 domains
4
public clouds plus Kubernetes-native inventory
30–50%
MTTR reduction in customer benchmarks*
21
named AI agents on LangGraph + MCP servers

* Based on customer benchmark engagements. Methodology available on request during an architecture review.

By role

What changes for your team

The same control plane reads differently depending on what you are accountable for.

CISO

Zero standing privilege, provable at audit time

Every run is authenticated through your IdP, scoped with a JIT role that expires, and checked against OPA/Rego before a single resource changes. The audit evidence is a by-product of execution, not a quarterly fire drill.

What you get
  • OIDC/SAML federation with your existing identity provider
  • JIT least-privilege roles — no standing credentials in pipelines
  • Runtime secret injection from Vault, Akeyless, AWS/Azure/GCP KMS
  • Immutable execution lineage mapped to SOC 2, FedRAMP and ISO 27001 evidence
Platform

Eight domains. One governed fabric.

75+ capabilities, documented in full — not a feature wall with nothing behind it.

Walkthroughs

Watch it work

Four narrated walkthroughs. Sound on.

Platform tour

The control plane

A guided walkthrough of where infrastructure meets agentic AI.

Flagship

Cantilever-Engineering.AI mesh

The full platform story — governed DevSecOps and autonomous operations in one take.

Service catalog

Click to compliant

Inside the automation supply chain — from request to audit-ready execution.

Zero Trust

The Zero Trust automation fabric

Every execution step identity-scoped and policy-enforced.

Trust

Built for the environments that get audited.

Financial services, healthcare, government and energy. Zero Trust controls and compliance posture are architectural decisions here, not a regulated-customer configuration exercise.

ZT

Zero Trust execution

OIDC/SAML, JIT access, fine-grained RBAC, hard tenant isolation.

PaC

Policy-as-code

OPA/Rego at every gate, environment-specific policy sets, plan-time checks.

🔒

Secrets hardening

Short-lived credentials injected at runtime. Never stored in templates.

Compliance packs

FedRAMP, HIPAA, PCI-DSS posture support and CIS benchmark automation.

Evaluation kit
  • Executive datasheet — overview, deployment options, decision context
  • Technical engineering blueprint — architecture, integration and policy model
  • Agentic AI capability map — the 21 agents and what each one does
  • Competitive positioning matrix — how we compare to adjacent platforms
Get the evaluation kit
Resources

Everything your review board will ask for.

One form, one business day, the whole package — executive summary through to policy model and agent architecture. No drip sequence, no gated PDF maze.

Questions

The things evaluators actually ask

Do we have to replace Terraform, Ansible or ServiceNow?
No. Cantilever is an overlay control plane. Your existing engines keep executing the work — Cantilever governs how they are invoked, by whom, under what policy, and records the evidence. Most deployments connect to tools that are already in production.
How is this different from a CI/CD platform or an IDP like Backstage?
CI/CD platforms execute pipelines; developer portals catalogue them. Neither enforces identity-scoped, policy-gated execution with ITSM-linked change evidence across multiple engines. Cantilever sits above both: one catalog, one policy framework, one immutable audit trail spanning Terraform, Ansible, GitHub Actions, GitLab CI and Harness.
Can it run in an air-gapped or sovereign environment?
Yes. Customer-managed deployment supports air-gapped and sovereign environments, including private AI deployment options so the agentic layer never calls an external model provider. SaaS and hybrid models are also available.
What does the AI layer actually do — and can we turn it off?
The agentic layer runs inside the same policy boundary as everything else: risk scoring and blast-radius modelling before execution, RCA correlation after incidents, and natural-language queries over inventory and execution history. Agents propose; CIPF still governs. The module is optional on Tiers 1–3 and can be disabled entirely.
How long does a deployment take?
Foundation Onboarding typically runs as a scoped engagement covering platform deployment, IdP/SSO integration, RBAC design, initial catalog build and connector validation. Scope depends on your toolchain breadth — an architecture review gives you a concrete estimate.
Who does the implementation work?
We do. Cantilever-Engineering Corp builds the platform and delivers the engagements — onboarding, automation library migration, custom integrations, custom agents and compliance work. The engineers who wrote the connector framework are the ones who write your connector. There is no partner hand-off and no gap between what was sold and what gets built.
Next step

See a governed run against your own stack.

Bring your toolchain and one real workflow. In 30 minutes you will see it requested from the catalog, gated by policy, executed and evidenced — end to end.

30 minutes · tailored to your stack · no slideware