Implementation
One clearly scoped process. Connected to your systems, tested on realistic cases and built around clear approvals for your team.
These stages describe technical implementation, particularly the design and pilot phases of our overall approach. A separate AI Opportunity Check is not required. Duration and internal effort depend on the agreed process.
01
We document the current process and measure the baseline: time, volume and error patterns.
02
We define the workflow, system integrations, checkpoints and escalation rules before building.
03
The workflow is tested on real cases, including difficult ones. Quality criteria determine the outcome, rather than impressions.
04
We use the agreed criteria to decide whether to go live, refine the workflow or deliberately stop.
Hello Ms Weber, thank you for your enquiry about two locations. Which services do you need, and when would you be available for a short call this week? We can also discuss whether a November start is possible.
Source: customer email03 · Your team decides
Your team checks the content and next step.
Read, copy details, write a reply
Details organised. Reply drafted.
For IT, departments and decision-makers
This is a review framework, not a security or service commitment that has already been fulfilled. The specific architecture and responsible people are defined for your project.
At every handoff, review access rights, stored data and responsibilities. Providers and storage locations have not yet been selected for your project.
01 · IT + data protection
Which service may process which source?
Document systems, interfaces, test access, data types, providers and regions, access roles and retention periods. Explicitly review model training and subprocessors.
02 · Department + EVORI
When is the workflow good enough?
Agree examples, errors and edge cases, human checkpoints and measurable acceptance criteria. Testing only straightforward success cases is not enough.
03 · Process owners + team
Who uses, reviews and decides?
Document roles and training needs. Involve the works council where applicable. Clarify use of learning and activity data before rollout.
04 · Operator + department
What happens if something fails?
Assign responsibility for monitoring, cost limits, backups, recovery, escalation and falling back to the previous process. Record response times in the contract.
Already have a pilot? Discuss the remaining questions →
A clearly scoped workflow with agreed interfaces, test cases, approval points and acceptance criteria. Documentation and the agreed team onboarding are included. The scope and duration of support after handover are recorded in the proposal.
A contact person in the relevant department, accessible example cases and involvement from your IT team. You receive the scope, duration and price before commissioning. Ongoing provider and model costs, and any subsequent maintenance, are listed and agreed separately.
Every workflow has defined checkpoints: a person approves anything sent externally or made binding. Exceptions, including unclear cases, unusual values and sensitive topics, are deliberately escalated rather than resolved by guesswork. We explain how we define checkpoints in the article Defining human-in-the-loop in practice.
We use the technology that fits the case, whether language models, fixed rules or retrieval from your knowledge sources (RAG), and document why. Tools serve the outcome.
Already have a process in mind? We can discuss implementation directly. If you want to assess several candidates first, the AI Opportunity Check is a separately agreed starting point, with no requirement to complete it before every workflow project.