Services · AI Consulting

ChatGPT and Codex Consulting

Plan OpenAI ChatGPT and Codex workflows, integrations, team guidance, and evaluation around your organization’s requirements.

We identify the appropriate working environment for assistant tasks, coding work, and API-backed automation.

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AI Consulting overview

Scope and planning

Choose the right deployment approach

Separate an application workflow from a custom integration.

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A team may need a managed assistant workspace, a coding workflow, or a service connected through an API. We assess those approaches against the task, current systems, administrative needs, and budget. Features and access are checked for the selected product and plan.

The assessment identifies users, approved information, output destinations, and who accepts the work. We also record what should remain manual. Purchasing additional access is useful only when the resulting workflow meets a defined need.

Set boundaries for tools and development

Control access and review actions that change systems.

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For connected workflows, we evaluate the available integration method and verify which data and functions it exposes. MCP servers can provide access to external services; we assess trust, permissions, and the approval requirements for sensitive actions.

For Codex work, we define project access, execution boundaries, source-control practices, and review before production use. Testing must assess the intended behaviour, and the team needs a way to restore a previous state if a change fails.

Evaluate quality and operating cost

Compare completed work rather than prompt volume.

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Pilot tasks include ordinary requests and difficult examples. We record acceptable results, corrections, and failure handling. Staff training covers giving useful context, verifying important claims, and reviewing generated changes or drafts.

Costs can include user access, API usage, tools, hosting, and staff review. We verify how the chosen deployment is billed and which limits are enforceable. XL AV can deliver a configuration, workflow guidance, evaluation results, and documented handover within the agreed scope.

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Connect approved AI tools to business systems through scoped MCP servers, with authentication, testing, and documented ownership.

AI Training and Team Adoption

Train staff to use AI on real work, check results, handle company information appropriately, and follow repeatable workflows.

AI Cost Controls and Usage Management

Understand AI subscriptions, API consumption, usage limits, and automation costs before expanding deployment.

AI Governance, Data Access, and Quality Assurance

Define permitted AI use, information access, output review, and operational ownership before expanding connected workflows.

AI Middleware and Token Optimization

Use AI-assisted development and reusable middleware to reduce unnecessary model calls, repeated context, and token consumption.

Local and Offline AI Model Deployment

Plan local, on-premises, offline, or hybrid AI models with suitable hardware, data boundaries, performance testing, and maintenance.

Platform documentation

Product capabilities, access, and commercial terms are checked against the selected plan during project design.

Plan your AI project

Tell us which workflow you want to improve, the systems you use, your existing AI subscriptions, and your requirements for data access, budget, and staff training.

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