Less repetitive work. More useful decisions.

Strong first candidates are frequent, repetitive tasks with relatively clear rules and significant manual effort: sorting or transferring information, generating documents, sending reminders, qualifying requests, consolidating data or searching internal knowledge. We prefer a focused use case where value can be measured quickly rather than a large AI programme whose business impact is difficult to prove.

No. We follow the principle of least privilege: a workflow or assistant receives only the data and permissions required for its task. Data sources, service accounts, API keys and access rights are deliberately scoped. This avoids giving an automation broad organisational access simply because it would be easier from a development perspective.

For higher-risk processes, we do not let a language model make decisions without safeguards. Depending on the use case, we combine controlled sources, deterministic business rules, citations, format validation, confidence thresholds and human approval. We also define what the system should do when information is missing or when the answer cannot be established reliably.

Yes. We can connect services through APIs, webhooks and available automation platforms, then add business logic tailored to your process. The objective is not to replace every existing tool. In many organisations, the fastest return comes from removing manual work between the systems employees already use every day.

Before implementation, we define a few practical indicators such as time spent, error rates, processing time, volume or operating cost. We measure the same indicators after the pilot. If the improvement is meaningful, we harden and scale the solution; if the value is insufficient, we change the approach or stop rather than maintaining automation for its own sake.