Minimum useful data
Start by asking which fields are actually needed. Use fake, sample, or minimised data where that is enough to design and test the system.
Data and AI principles
Use practical AI carefully, with people still in control.
DG Workflow's public story depends on trust. The goal is to make small-business systems clearer without collecting unnecessary data, hiding AI uncertainty, or pretending demos are real client results.
Human-reviewed AI
AI outputs are drafts or decision-support material. Customer-facing, financial, legal, safety, or reputational outputs need a person to review them before use.
Synthetic demos only
Public demos use fake businesses, fake messages, fake spreadsheet data, and fake reports. Real client data belongs only in agreed client work.
No autonomous high-impact decisions
DG Workflow should not start with autonomous legal, financial, medical, HR, safety-critical, regulated, or sensitive personal-data decisions.
Provider transparency
A project should explain which hosting, database, automation, email, AI, analytics, or file-storage providers process system data.
Practical AI, not AI theatre
AI is useful for extracting fields, summarising, drafting, classifying, and turning scattered inputs into reviewable structure. It is not the whole product.
Website posture