Access Analytic consulting services

Implementation Services

AccessEXL is self-serve when you want to connect an individual workbook. Access Analytic can also help you prepare a model, build an integration or turn an organisation's portfolio of approved spreadsheet models into governed capabilities and AI-native services that agents can discover and use.

We built AccessEXL because organisations already have valuable logic in Excel. They need a secure way to use it more widely, not another expensive project to rebuild it.

Engagement path 2

See AccessEXL working in your environment before deciding how to scale

You do not need to commit to an organisation-wide rollout before you have seen AccessEXL working with your own model, users and Microsoft environment.

We begin with a clearly scoped, fixed-fee proof of concept. Together, we select one valuable spreadsheet model and demonstrate how AccessEXL can connect it to an agreed AI-native service workflow.

Your team can evaluate the experience, confirm the access approach and test representative results before deciding whether there is a business case for a wider rollout.

  1. 1Prove itConnect one suitable model in your environment.
  2. 2Evaluate itTest the workflow, access and representative results.
  3. 3Scale itChoose the rollout approach that suits your organisation.
Recommended first step

Prove one AI-native service in your own environment

Fixed Fee: AUD$4,900

Start with a fixed-fee proof of concept using one of your existing Excel models. See how AccessEXL can connect your business logic to a practical AI-native service, test the results and get comfortable with the approach before deciding on a wider rollout.

Indicative scope

  • Select one suitable model and a clearly defined business use case.
  • Agree the workflow, required inputs, expected outputs and success criteria.
  • Configure the model connection and appropriate access permissions.
  • Connect the model to an agreed AI or automation workflow.
  • Test representative scenarios and agree where human review is required.
  • Demonstrate the solution and recommend options for broader adoption.

Example use cases

Quote preparation, cash-flow scenario analysis or project feasibility assessment.

Agreed before work begins

The scope, deliverables and fixed fee are agreed before work begins.

AccessEXL provides the controlled connection to the model. The agreed AI or automation tools provide the surrounding workflow, and people review decisions where required.

Best for: Organisations that want to assess one practical use case in their own environment before committing to a broader program.

Outcome: A working proof of concept, stakeholder demonstration, agreed findings and practical options for the next stage.

Discuss your proof of concept

A controlled first step

The proof of concept is designed to demonstrate technical feasibility, user value and the proposed governance approach. It is not an uncontrolled release of the organisation's spreadsheet estate.

Only the agreed models and capabilities are included. Wider production use, additional models, enterprise support, integration hardening and organisation-wide change management are addressed in the rollout stage.

What happens after the proof of concept?

We present the findings, demonstrate the working capabilities and recommend the most appropriate next step. The organisation can stop, expand within one function, proceed enterprise-wide or build the internal capability to onboard models itself. There is no automatic commitment to a wider rollout.

Choose the rollout path that fits

Option 1

Business Function Rollout

Expand within one team or business function

  • Prioritise models in the selected function
  • Assign model and business owners
  • Configure, test and approve capabilities
  • Design access scopes and metadata
  • Train users and administrators
  • Support adoption and report value

Best for: Organisations that want to expand in controlled stages and demonstrate value within one function.

Outcome: A governed catalogue of capabilities available to an agreed group within one business function.

Option 2

Enterprise Capability Rollout

Create a governed capability network across the organisation

  • Department-by-department discovery
  • Enterprise prioritisation and central register
  • Standard configuration and documentation
  • Security, access and restricted SharePoint design
  • Testing, sign-off and change control
  • Training, communications and phased onboarding

Best for: Large organisations with significant spreadsheet estates and an enterprise AI or automation program.

Outcome: A governed organisational capability network using approved Excel calculations without exposing workbooks.

Option 3

Capability Enablement and Co-delivery

Build the organisation's internal ability to onboard models

  • Governance and assessment framework
  • Configuration and metadata standards
  • Testing and approval procedures
  • Security and access guidance
  • Training for administrators and model specialists
  • Co-delivery, quality review and escalation support

Best for: Organisations expecting to onboard many models and build an internal AccessEXL capability.

Outcome: An enabled internal team and a repeatable, governed onboarding method.

Customised pricing for these options will be provided upon completion of our online Discovery workshop.

Discuss your Project

Optional ongoing service

AccessEXL Managed Capability Service

Keep your capability catalogue accurate, secure and useful

The managed service can be added after any rollout option.

Best for: Organisations that want an expanding environment without a new internal support burden.

Outcome: A maintained and continuously improving catalogue of trusted spreadsheet capabilities.

Why make spreadsheet capabilities available to AI?

01

Make hidden capabilities discoverable

Approved pricing, forecasting and evaluation models become named capabilities agents can find.

02

Reduce dependence on model owners

Employees do not always need to locate a workbook or wait for its owner to run a scenario.

03

Use existing trusted logic

Avoid recreating every model in Python, a prompt or a second application.

04

Create consistent answers

People, applications and agents use the same maintained calculation logic.

05

Protect intellectual property

The workbook, formulas and full structure remain protected.

06

Govern AI access

Each capability has an owner, purpose, approved interface and access scope.

07

Accelerate useful AI adoption

Agents perform controlled business tasks rather than relying only on generated answers.

08

Create a reusable foundation

Capabilities support AI conversations, applications and automated workflows.

Illustrative example

What this could look like in practice

An organisation publishes approved tasks such as evaluating a capital proposal, calculating a customer price, forecasting cash flow, testing commodity-price scenarios or comparing investments. An employee asks an AI agent to perform the task. The agent discovers the capability, collects the inputs, runs the actual Excel model and presents the result without receiving access to the workbook or formulas.

Who this is for

  • CFOs and finance-transformation teams
  • CIOs and AI leaders
  • Commercial, mining, engineering and project teams
  • Organisations with key-person dependence around critical spreadsheets
  • Businesses that want to use AI without rebuilding trusted models

Start by proving it with your own models

See AccessEXL working with selected spreadsheet models, users and business scenarios in your own environment before deciding how widely to roll it out.

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