Responsible AI
Automation should make a process better without hiding who is responsible for the outcome.
What we run by default
Human accountability
AI can assist a decision, but responsibility for material business outcomes remains with a named person or client function.
Transparency
Where appropriate, users should be told when an interaction or output is AI-assisted.
Data restraint
Do not send more data to a model or provider than the use case needs.
High-impact caution
Employment, healthcare, finance, legal, and other high-impact uses require stronger review and domain-specific controls.
Failure paths
Design escalation, fallback, and manual handling for the cases the automated path cannot safely resolve.
Measurable quality
Track the workflow against agreed business and quality measures instead of relying on demo performance.
Free workflow review
Find the workflow worth automating next
Bring one process that is slow, repetitive, expensive, or leaking opportunities. We will map the current workflow, identify the bottleneck, and tell you whether automation is worth pursuing.
No obligation. If automation is not the right answer, we will say so.