Retainer
Ongoing AI Operations
Recurring work that keeps an implemented workflow reliable, controlled, supported, and useful after launch: monitoring, reviews of usage, cost, and access, provider changes handled, people supported, and improvements chosen from evidence.
Operations follows a completed AI Workflow Pilot because reliability can only be owned for a workflow whose design, permissions, and rollback path are documented. Taking on an undocumented system means being accountable for behavior nobody can explain. See the whole engagement path for how the steps fit together.
Who Operations is for
The retainer suits organizations that already have something worth keeping running, and fits poorly where there is nothing documented to take responsibility for.
A good fit when
- The workflow was built and documented through a Pilot, with a tested rollback path.
- You can name an internal contact who takes escalations and decides what happens next.
- You have an approved change process for anything that touches production work.
- You want cost, access, and quality reviewed on a schedule rather than after an incident.
Not the right step when
- The workflow was built elsewhere, with no documentation and no rollback path.
- Unlimited new builds are expected inside the retainer.
- An around-the-clock help desk is expected.
- Formal compliance certification is required. Operations keeps agreed controls in place; it does not certify anything.
What is watched and reviewed
Reviews happen on an agreed schedule, not in response to an incident: a climbing cost, a permission that outlived its reason, or quality that has slipped is found while it is still small.
- Monitoring and error alerting for the workflow and the systems it depends on
- Usage and cost review, including where a provider change affects either one
- Access review to confirm permissions still match what the work requires
- Model and interface updates when a provider changes something underneath the workflow
- Employee support, refreshed guidance for new staff, and a usage policy kept current with the tools in use
- Workflow improvement and a periodic review of what to build, change, or retire next
How much a retainer carries depends on the workflow, and the scope is written down before it starts.
When a provider changes something underneath
A model version is retired, an interface changes shape, pricing moves, or a permission model is rewritten. The first sign is usually a workflow quietly producing worse results.
The change is assessed
What changed, which part of the workflow depends on it, and whether output, cost, or permissions are affected. Nothing is altered first.
The workflow is updated or held
Where the change is safe, the workflow is updated and tested against the criteria it was built to meet. Otherwise it is held on what runs today, and you are told what that costs.
The change is documented
The implementation documentation is corrected so it still describes what is running. Documentation that has drifted from reality is worse than none.
The people who use it are told
When the output behaves differently, the people who rely on it hear what changed, rather than discovering it in their own work.
Supporting the people who use the workflow
A workflow nobody trusts stops being used, and a workflow nobody understands gets used badly. This is where AI adoption lives after launch.
Questions from the people doing the work
Why a result looks wrong, whether an output can be relied on, and what to do when the workflow cannot help. A recurring question is a signal about the workflow.
Refreshed guidance for new staff
Role-based guidance is kept current as people join and as the workflow changes, so a new employee learns the system that exists.
A usage policy that keeps up
The written policy is revised to match the tools actually in use, including any adopted after the Pilot ended.
This is practical support for using the tools well. It does not make your organization secure or compliant, and it does not replace legal advice.
How improvement and expansion work
There are two kinds of change here, and treating them as one is how a retainer becomes an unscoped build.
Improving the workflow you have
A better-handled edge case, a clearer prompt, another source for an existing step, a permission tightened after a review. These happen under Operations, through your approved change process.
Building a workflow you do not have
A second workflow is a new decision with its own data, permissions, and definition of success. It is scoped as its own engagement, not grown inside the retainer.
Deciding what to stop
A review also asks what to retire. A workflow that no longer earns its cost or access should be turned off, with the reasoning recorded.
So a new workflow goes back through the ladder as a further AI Workflow Pilot, and where the candidate is unclear it starts one step earlier, with an AI Opportunity Assessment to choose between the possibilities.
What you receive
Operations produces a record, not only activity.
- An agreed alerting and support path, including who inside the organization is contacted first
- A recurring review of usage, cost, and access, with findings recorded
- Documented changes whenever a model, interface, or workflow is updated
- A periodic review of what to build, change, or retire next, with the reasoning recorded
What stays with you
Reliability is shared. Three things have to stay true on your side.
- A named internal contact for escalations and decisions
- Prompt reporting of failures or behavior that looks wrong
- An approved change process for anything that touches production work
Without a named contact, a failure waits to be noticed; without an approved change process, a fix waits to be authorized.
The constraints do not relax after launch
The Security Constraint, the documentation and auditability conditions, and the human-authorization rules that governed the build keep applying while the workflow runs. Access is reviewed rather than left as granted, an action with consequences can still be explained afterwards, and a person still approves a record change, a payment, or an outgoing message.
These conditions are stated once, in full, on the services page, and they apply to every step, including this one.
Questions about Ongoing AI Operations
Can you take over a workflow someone else built?
Not directly. The AI Opportunity Call decides whether its documentation, permissions, and rollback path give Operations what it needs to be accountable. Often they do not, and the honest route back is an AI Opportunity Assessment.
Is this an IT support contract?
No. It covers the AI workflows Natural State Logic built and the systems they depend on, not general technology support for devices, networks, or unrelated help-desk requests.
What happens when the model provider changes something?
It is assessed, the workflow is updated or deliberately held, the documentation is corrected, and the people who use it are told. That holds for a model version, an interface, pricing, or a permission model.
How often are reviews?
On the schedule agreed in writing, sized to the workflow. One that changes records in a live system warrants closer attention than one that drafts internal summaries.
Can we add a new workflow under the retainer?
Improvements to the workflow you have, yes, through your approved change process. A new workflow is a new AI Workflow Pilot: it needs its own scope, permissions, and success criteria.
Can we end the retainer?
Yes. The terms, including notice, are agreed in writing before it starts. The documentation, usage policy, and record of changes are yours and stay usable afterwards.
Who does the work?
Natural State Logic is founder-led, so the person reviewing and updating the workflow is the person who built it.
Is the price fixed?
Scope and commercial terms are agreed in writing before the retainer begins, set against the workflow being supported. A change to scope is agreed the same way.
Start with the free conversation
Describe the workflow you need kept reliable. The call establishes whether Operations is the right next step or something earlier on the ladder comes first.