Assisted
People do the work; AI supports them.
AI finds information, summarises or prepares a draft. Your team reviews the result and carries out the next step.
Example: preparing a response to a customer enquiry.
Discover AI opportunities
Where can AI take work off your team’s hands?
We examine your workflows and develop concrete AI scenarios. Together, we clarify what rules can automate, where AI helps and where people should decide.
AI scenarios
Assisted. Partially autonomous. Agentic.
How much responsibility can AI take on? We compare three scenarios — including combinations.
Partially autonomous
AI handles clearly defined steps.
A defined workflow combines rules and AI. Routine cases run automatically within agreed boundaries; exceptions and approvals go to your team.
Example: classifying incoming documents, extracting information and flagging unclear cases for review.
Agentic
AI pursues a goal; people retain oversight.
An agent plans steps, uses approved tools and checks intermediate results. Your team sets goals and boundaries, supervises the workflow and approves important actions.
Example: preparing a case across several systems for a decision and submitting it for approval.
Agentic work can remove a substantial workload when entire task sequences run independently. Whether it offers the greatest value also depends on reliability, integrations and review effort. Sometimes targeted assistance is enough to make a noticeable difference.
Starting point
High-volume processes: small savings, repeated often.
Handling enquiries, checking documents, transferring information: high-volume processes repeat similar tasks. Saving just a few minutes per case can add up across many cases.
We look at case volumes, processing time, errors and rework. We also consider data access, exceptions and who needs to review the result. This turns an idea into an initial assessment of potential value.
Automation
Fixed rules or AI? Often, a combination works best.
Deterministic vs non-deterministic automation: the difference lies in how a result is produced and how we verify it.
Deterministic: fixed rules
The same inputs under the same conditions produce the same result. This suits calculations, required-field checks and clear if–then decisions.
Non-deterministic: variable results
Generative AI can process text, documents and open-ended tasks. We use suitable guardrails and verification tools: clear instructions, automated tests and targeted approvals help validate results.
Discovery workshop
From your workflow to a concrete next step.
Prepare
We select a specific process. You bring typical cases, known exceptions and someone who understands the workflow.
Explore together
In the workshop, we walk through the process: what repeats? Where do people wait, search or rework? Which decisions follow rules, and which need judgement?
Agree the next step
We compare suitable scenarios by value, effort and risk. You receive a recommendation, the prerequisites and a proposal for an initial trial.
Your outcome
Know what to test next.
You receive the mapped workflow, suitable AI scenarios and a reasoned recommendation. We record assumptions about value, open questions and the data needed.
The next step could be a prototype, simple automation or an improvement to the existing process. We agree the workshop’s scope and price upfront.