Skip to main content

Solutions

Four ways to work together, each for a different decision

Do not begin with a technology label. Begin with what remains uncertain today. The right engagement makes the process, evidence, delivery, and ownership progressively clearer.

Prepare an intake

Choose by uncertainty

Which step fits your current situation?

The ladder is not a mandatory sequence. Start with the smallest engagement that can answer the current decision reliably.

  1. 01No clear use case yetAI Scan
  2. 02Clear use case, feasibility still uncertainAI Proof of Concept
  3. 03Clear process and desired outcomeAI Workflow Automation
  4. 04Multiple processes or a structural roadmapAI Implementation Partner

Clear expectations

An engagement promises only what its boundary can support

No fixed price, timeline, or outcome is stated. Scope, source data, quality criteria, and operating responsibilities are made explicit at each step.

01

AI Scan

Best-fit situation

For organisations without a clearly bounded use case or priority.

Core question

Which process problem deserves an evidence-based next step first?

Typical activities

  • Define the process, owner, and friction
  • Review available data and system context
  • Compare opportunities by value, feasibility, and risk

Concrete outputs

  • Prioritised opportunity map
  • Bounded use-case definition
  • Recommendation for a PoC, implementation, or stop

Boundaries

  • No working prototype or production implementation
  • No business case without available source data

Next step

Select one use case for validation or delivery.

02

AI Proof of Concept

Best-fit situation

For teams with a clear use case but uncertain technical or operational feasibility.

Core question

Can the critical assumption be assessed in a controlled trial?

Typical activities

  • Define the hypothesis and acceptance criteria
  • Build a bounded technical trial
  • Evaluate quality, exceptions, and human control

Concrete outputs

  • Bounded prototype
  • Recorded test findings
  • Go, adjust, or stop recommendation

Boundaries

  • Not a disguised production environment
  • No guarantee that scaling is appropriate

Next step

Use the evidence to decide whether and how implementation continues.

03

AI Workflow Automation

Best-fit situation

For teams with a clear process, owner, and desired operating outcome.

Core question

How can the process be automated reliably, using AI only where interpretation is required?

Typical activities

  • Design the workflow and system boundaries
  • Build software, integrations, and targeted AI steps
  • Set up QA, exception handling, and handover

Concrete outputs

  • Integrated workflow within agreed scope
  • Testing and quality controls
  • Documentation and operational handover

Boundaries

  • No AI where fixed rules are sufficient
  • Monitoring and recovery only when explicitly in scope

Next step

Validate operation and improve only from available operational data.

04

AI Implementation Partner

Best-fit situation

For organisations with multiple processes or a structural implementation roadmap.

Core question

How can priorities, architecture, and governance remain coherent across phases?

Typical activities

  • Prioritise the process portfolio and dependencies
  • Define shared architecture and quality principles
  • Guide phased delivery, governance, and knowledge transfer

Concrete outputs

  • Prioritised roadmap
  • Coherent architecture guardrails
  • Phased delivery and handover agreements

Boundaries

  • No big-bang transformation
  • Ownership, decisions, and scope remain explicit per phase

Next step

Start with the first value stream that is sufficiently clear and testable.

01

Technology follows the process

Fixed rules call for predictable software; AI gets a bounded role only where interpretation is required.

02

Production quality is explicit

QA, human control, monitoring, and recovery are designed when the agreed scope requires them.

03

Ownership remains transferable

Documentation, decision boundaries, and knowledge transfer prevent the solution from becoming a black box.

Shared delivery path

The quality discipline remains consistent

Depth varies by engagement, but analysis, architecture, validation, human control, and handover stay visible.

  1. 01

    Analyse

    Map the process, owners, friction, data, and baseline.

  2. 02

    Prioritise

    Compare value, feasibility, risk, and dependencies.

  3. 03

    Architect

    Design rules, AI tasks, integrations, and human control.

  4. 04

    Implement

    Build the workflow and integrate existing systems.

  5. 05

    Validate

    Test quality, exceptions, security, cost, and adoption.

  6. 06

    Monitor

    Make operation, errors, lead time, and consumption observable.

  7. 07

    Improve

    Use evidence to iterate and transfer knowledge completely.