AI managed services

What managed means

An AI subscription gives you a tool. A managed service puts an agreed workflow around it: approved inputs, a useful output, a named reviewer, and someone responsible for maintenance.

Sekora AI is developing this service through internal use. We’re starting with discovery conversations and discussion of scoped pilots, not a ready-made package for every business.

The intended service covers setup, team training, and ongoing management under a written agreement. A conversation helps determine whether a pilot makes sense. It does not reserve a deployment date.

What we’d agree to deliver

Each proposal would define the work and its limits. A scoped workflow would include:

• A brief describing the task, approved information, expected output, and success criteria.
• A configured process, with only the permissions it needs.
• Reviewed example outputs and tests for errors or missing information.
• An operating guide and training for the people using it.
• Written responsibilities for support, maintenance, costs, and stopping the service.

You supply the business context and decide who reviews the work. Sekora’s maintenance responsibilities, account ownership, hosting, and escalation arrangements must be agreed before work starts.

Start with something worth testing

Preparing a source-linked brief or drafting a procedure from approved files may be a useful starting point. These are illustrative use cases, not finished packages or customer results.

We’ll also consider existing software or simpler automation. AI is the wrong choice when a fixed rule does the job, inputs are unsuitable, or nobody can check the result.

AI will not replace humans. It enhances a person’s job by taking over repetitive tasks that keep them from doing what they’re good at.

A bounded service, not unlimited automation

Custom development, integrations, model usage, and support need explicit limits. A managed-service agreement would not automatically include unlimited usage, every business system, or 24/7 support.

It would not provide regulated professional advice or permission to spend money, publish content, or change records without agreed controls.

Read how a pilot would work, privacy and control requirements, and the proposed pricing structure.

Questions before getting started

How is this different from buying ChatGPT or another subscription?

A subscription provides access to software. The proposed service adds workflow scoping, configuration, testing, training, and defined ongoing management. If a subscription alone meets your needs, we should say so.

What makes a good first task?

Choose recurring work with clear inputs, a recognizable output, and a person who can check it. Avoid high-consequence actions as a first experiment. Agree on success criteria before testing.

Will we need to replace our existing software?

Not necessarily. We start with your current process. Any integration depends on available permissions, technical testing, costs, and your approval. Replacing software is a separate decision.

Can we start without connecting accounts?

We can discuss a pilot using synthetic examples or explicitly approved documents. We would first check whether those inputs can answer the business question. Account connections are not a starting requirement.

Who reviews the output, and what if the AI is wrong?

Your business names a reviewer. AI can invent facts, miss context, or misread a source. The reviewer checks important claims before use. Pilot tests should cover errors and missing information, with a clear way to pause work.

Can it send messages or change records automatically?

Not by default. Any external action needs a separately agreed permission boundary and testing. Consequential actions require human approval. A draft-only workflow is often the better starting point.

Where does our information go, and who can access it?

That depends on the selected configuration. Before deployment, we must document storage, model providers, logs, retention, and access. Our proposed boundary is no standing Sekora access to client data or secrets. Any support exception must be approved, time-limited, and audited. See privacy and control.

Are local and cloud options both possible?

Both are options to evaluate, not universal service commitments. Model quality, hardware, cost, data requirements, and support needs determine fit. A local model alone does not prove that nothing leaves your network.

What would ongoing management cover?

The proposal would name maintenance tasks, support hours, response expectations, usage arrangements, and review intervals. New workflows and substantial changes need separate scope. Ongoing management would begin only by agreement after evaluation.

Who owns our accounts, data, and custom work?

The intended model keeps your business information under your control. Account ownership, billing responsibility, software licenses, and rights to custom work must be explicit in the agreement. We do not treat those details as implied.

What happens if we stop?

Agree on the exit path before starting. It should cover exporting agreed materials, revoking access, final charges, retention and deletion, and who handles the handover. Backup copies and provider limits also need an explicit explanation.

Discuss one workflow

Tell us what repeats, what you use today, and who checks the result. Discuss a workflow before committing to a tool or a pilot.