Questions about implementing local AI

Hardware, access, costs, and ongoing operation depend on the deployment. These answers describe our approach. Your architecture and written scope establish what applies to your environment.

An orange request marker moves through six separated layers representing people, permissions, data, model execution, tools, and records.The request route

Storage, inference, connected tools, and support each need an explicit decision.

Conceptual architecture illustration

Architecture and access

Does local AI mean nothing leaves our environment?

Only if the complete deployment is configured and verified that way. Inference, retrieval, logs, backups, tools, and support channels need separate review. We document destinations and exceptions rather than infer them from the model location.

Do we need to buy new hardware?

That depends on model size, concurrency, response expectations, and existing capacity. The setup review evaluates your infrastructure before recommending additional hardware or a different deployment route.

Can employees see every connected document?

They should only retrieve material permitted for their role and task. Source permissions, indexing behavior, service accounts, and user access need to be designed and tested together.

Control and evidence

What is a bounded agent?

An agent with a stated purpose and explicit limits on sources, tools, destinations, duration, and actions. Requests outside those limits should be denied or sent for review, with the outcome recorded.

Can the workflow act without human review?

The agreed workflow determines which actions can run and which wait for approval. Initial pilots usually prepare drafts or recommendations. Write access, exports, and customer-facing actions require explicit decisions.

Does this eliminate prompt injection or incorrect answers?

No. Limited access, tool restrictions, source checks, testing, and review can reduce exposure. Models can still produce incorrect output, and new failure cases need an operating response.

What can we review after a run?

The agreed record plan can include the request, source references, model route, approvals, denials, tool activity, output, and reviewer decision. Availability and retention depend on the implemented configuration.

Delivery and commercial decisions

How long does implementation take?

We set milestones after reviewing the workflow, infrastructure, integrations, and access. We cannot give a reliable schedule before those dependencies are known.

What does it cost?

Pricing follows the agreed scope. Implementation, infrastructure, model or platform licensing, third-party tools, and ongoing support are separate cost considerations. The review identifies which are relevant.

Who owns the data and configuration?

The project agreement establishes ownership, licenses, access, and handover. The architecture defines where your records are held and how they can be retrieved. Local hosting alone does not settle every contractual ownership question.

What happens after handover?

Your named owners receive operating documentation and training. Monitoring, updates, workflow changes, and support response expectations are covered by the support scope you choose.

Have a workflow in mind?

Tell us what it involves and which systems it uses.

Request an AI setup review