Data and documents
Where the files live, how they are named, who may open them, and whether a search would retrieve the right version. Retrieval-augmented generation, which means searching your corpus before a model answers, fails when this layer is weak. We look at a sample, not at an abstract architecture diagram.
Processes and volumes
Which steps are repeated often enough to matter, where a draft would save time, and where a person must still decide. Volume without a stable process is a poor place to start. We ask for numbers the team already trusts rather than inventing a baseline.
Skills and ownership
Who would run a live assistant on a Tuesday morning when the vendor is quiet. If the answer is “the innovation committee”, we treat that as a finding. Ownership needs a named role close to the process, with time in the diary after the launch week.
Controls and legal exposure
What personal data would move, to which service, in which region, and on what retention clock. We help you pose those questions clearly for counsel. Guidance on this site does not constitute legal advice. Sector overlays such as financial or clinical rules are flagged so you can take them to the right specialist.
Economics of running a model
Licence lines, usage fees, staff time to review drafts, and the cost of keeping documents in a searchable state. A cheap chat seat can become expensive once retrieval, logging, and human review are counted. We put those lines next to the process you hope to change.