AI Opportunity Sprint

Choose one process worth improving.

Together, we move from ideas to an informed decision about your first implementation.

Discuss your sprint
A glass core connected to three tools, illustrating an AI agent.
01Indicatively 2–3 weeks
02One business area
033–5 stakeholder conversations
04Assessment of 5–10 use cases

What you take away

  • A map of problems and the process
  • Value and feasibility ranking
  • Risks and an indicative business case
  • Recommended implementation backlog

The sprint ends with a joint review with the process owner. The recommendation connects potential value with costs, risks and organisational readiness.

What do we need to start?

  • An owner for the selected process
  • Access to the people doing the work
  • Examples of tasks and available data
  • Time for a joint review of findings

Timing and pricing depend on scope and access to people, data and environments. Deferring the investment can also be a valid outcome.

HOW WE WORK

A decision you can act on.

01

Understand the work

Conversations with the people doing the tasks and a review of examples reveal repetitive work, exceptions and dependencies.

02

Compare use cases

We assess value, data availability, delivery cost and required controls, including options that do not require AI.

03

Agree the next step

We present a ranking, business case and backlog, then decide together whether to implement, prepare data or defer.

GOOD TO KNOW

Before we begin.

Do we need to replace our existing systems?

We start with your current environment, integration options and access constraints. We only consider replacement if the assessment shows it is needed, with a separately agreed scope.

How do you choose a model and platform?

We compare options using tasks from your process. We assess quality, cost per correctly completed case, integrations, agreements and data constraints. Sometimes a simpler automation without AI is the better choice.

Who will have access to our data?

Access follows user roles, process purpose and organisational policies. Before deployment, we agree on data sources, providers, logging scope and retention periods.

When is human approval needed?

It depends on the risk and consequences of an action. For sensitive operations, we design approvals outside the model, for example before sending a message, changing data or initiating a payment.

How do we measure the result?

Before deployment, we measure volume, time, costs and exceptions. Afterwards, we compare the same measures and include model, integration, review and maintenance costs. Recovered capacity is reported separately from cash savings.

What happens after deployment?

We hand over documentation and knowledge, and agree on monitoring, reviews, incident handling and rollback. Ongoing care can use a defined subscription scope, with further development priced separately.

LET’S START A CONVERSATION

One process. A good place to start.

What takes the most time or causes errors today? Tell us about the task, your team and the systems you use.

Discuss your process