Services

Our AI Approach

A structured methodology to move from AI curiosity to production value. We assess readiness, set governance, and deliver in phases — so AI ships inside your ERP, not beside it.

Guiding principles

How we think about AI for ERP

Four principles that shape every AI engagement — from first conversation to production rollout.

Production First

We only propose AI that ships. Every initiative targets a measurable outcome inside your live Business Central environment — not a sandbox demo.

Platform Before Custom

Start with what Microsoft already provides: native Copilot, standard agents, AppSource apps. Custom AI fills gaps, not the foundation.

Governance by Design

Data residency, consent, and compliance are decided before the first model runs — not retrofitted after launch. EU Data Boundary alignment is non-negotiable.

Smallest Stack That Works

We recommend the minimum technology surface for your outcome. No unnecessary middleware, no vendor lock-in, no complexity for its own sake.

Implementation phases

From assessment to adoption

Six phases that take you from AI strategy to measurable business value — aligned with your Business Central release cadence.

1

Readiness Assessment

We evaluate your data quality, licensing posture, infrastructure, and team readiness. You get a clear picture of what's possible today and what needs preparation.

2

Use-Case Prioritisation

Together we identify high-impact, low-risk AI use cases across your operations — finance, procurement, sales, operations. Each is scored on effort, value, and data readiness.

3

Governance & Compliance

We define data classification, EU Data Boundary configuration, admin consent policies, and security controls. Copilot and agent permissions are set before anything goes live.

4

Pilot Delivery

The top-priority use case is built and deployed to a controlled user group. We measure adoption, accuracy, and business impact against defined KPIs.

5

Scaling & Rollout

Proven pilots are rolled out across the organisation. Additional use cases are activated. Change management and training ensure adoption sticks.

6

Continuous Improvement

Ongoing monitoring, new Microsoft wave features, and user feedback drive iterative improvement. AI is a capability you build, not a project you finish.

Governance framework

AI governance built for regulated industries

Enterprise AI requires more than technology — it requires controls, transparency, and accountability.

EU Data Boundary

Business Central Copilot features align with Microsoft's EU Data Boundary. We configure tenant settings to keep your finance data within scope.

Admin Consent

Every Copilot experience and autonomous agent requires explicit admin enablement. We document who approved what, and when.

Role-Based Access

AI capabilities inherit Business Central's permission model. Users only see what their role allows — no shadow data access.

Audit Trails

Agent actions, Copilot interactions, and AI-generated outputs are logged. Full traceability for compliance and internal review.

Model Transparency

We document which AI models power each feature, where they run, and what data they access. No black boxes.

Opt-In by Default

Features that process data outside the EU boundary — like Copilot Cowork with Anthropic models — are disabled by default. You choose what to enable.

Frequently Asked Questions

Common Questions

How do you assess whether our organisation is ready for AI?

We run a structured readiness workshop covering data quality, Business Central version and licensing, infrastructure (cloud vs. hybrid), team skills, and governance posture. The output is a readiness scorecard with a prioritised action plan — not a generic slide deck.

How long does it take to go from assessment to production AI?

A focused engagement — readiness assessment, governance setup, and one pilot use case — typically runs 6 to 10 weeks. Broader programs with multiple agents, Copilot Studio, and Azure AI integrations align with your next BC wave and can span a quarter.

What if we don't know which AI use cases to pursue?

That's exactly what the prioritisation phase is for. We bring a framework of proven use cases across finance, procurement, and operations, then score them against your data and processes. You leave with a ranked backlog, not an open-ended list of ideas.

Can we start small and expand later?

Absolutely — that's the recommended approach. Start with native Copilot features already included in your license, prove value with a single pilot, then expand to custom agents and Azure AI as confidence and data maturity grow.

How do you handle data privacy and EU compliance for AI?

We configure deployments within Microsoft's EU Data Boundary for Dynamics 365. Any feature that routes data outside the EU — such as Copilot Cowork with Anthropic models — is disabled by default and only enabled with explicit admin consent. Governance decisions are documented before go-live.

Do we need to hire AI specialists internally?

Not necessarily. Our approach is designed to work with your existing BC team. We train key users, build runbooks for ongoing operations, and offer managed services for monitoring and iteration. AI becomes part of your ERP operations, not a separate department.

Ready to start your AI journey?

Book a readiness assessment. We'll evaluate your environment, identify high-impact use cases, and define a governance framework — in weeks, not months.

Start your AI assessmentExplore Copilot capabilities →