Agent operations runbook
Guardrails, approval gates, and audit checkpoints for putting agents to work on real operations.
- agents
- runbook
- governance
In progress - coming soon.
Resource library
Filter guides, articles, templates, tools, and references by format or topic. Each asset links back into the product, solution, or pricing it explains - so you can go from reading to evaluating without losing the thread.
Running projects and operations on infrastructure you control - on-prem, local cloud, or your own tenancy.
3 resourcesStructuring work so AI agents can execute against it safely, with the right guardrails and audit trail.
3 resourcesToken economics, admin budgets, and BYOK - paying for what you use instead of per-seat licences.
3 resourcesHow to run projects and operations on infrastructure you control - deployment posture, vendor jurisdiction, and keeping agents without giving up sovereignty.
What it takes to structure work so AI agents can execute against it safely - guardrails, agent-first vs. bolt-on, and a staged rollout.
Why per-seat pricing breaks down, how token-metered economics work, and how to budget AI usage without overage shock.
17 resources
On-prem, local cloud, and managed tenancy compared - with the reference architectures behind each.
Reference page
Where your data lives, who can reach it, and the controls that keep execution inside your boundary.
Reference page
What a token is, how collaborator seats stay free, and how admin budgets cap spend before it happens.
Reference page
How teams under audit and residency requirements map their controls onto sovereign work execution.
Delivery-led teams running client work with agent assistance and per-engagement budget control.
The structured surface agents and people share - sheets, views, and the execution graph beneath them.
How to run projects and operations on infrastructure you control - deployment posture, vendor jurisdiction, and keeping agents without giving up sovereignty.
8 min read
What it takes to structure work so AI agents can execute against it safely - guardrails, agent-first vs. bolt-on, and a staged rollout.
7 min read
Why per-seat pricing breaks down, how token-metered economics work, and how to budget AI usage without overage shock.
7 min read
The jurisdiction questions to put in your RFP - sub-processors, access process, and why region alone doesn't settle it.
4 min read
What to check when the deployment has to live inside your perimeter - and how to keep agents while you do it.
4 min read
Which project workflows to make agent-ready first, and how to recognise the ones with the right shape.
3 min read
Why the architecture underneath decides whether AI stays a sidebar or becomes a reliable operator.
3 min read
Forecast token spend from workload, set per-team caps, and review usage by workflow - predictable from day one.
3 min read
Two ways to pay the AI cost: bring your own model keys, or let the platform bundle it. How to choose.
3 min read
Guardrails, approval gates, and audit checkpoints for putting agents to work on real operations.
In progress - coming soon.
An interactive estimate of monthly tokens from team size and workload - no seat maths required.
In progress - coming soon.
Worked scenarios
Illustrative, fully-labeled scenarios that put the playbooks into a concrete deployment shape.
Start free on the managed sovereign cloud, or talk to our team about deployment, security, and procurement.