Enterprise AI architecture assessment
Create a coherent view of initiatives, production-architecture gaps, target principles, and the decisions that should come first.
Architecture advisory / Independent review
Get a focused outside view when an enterprise AI decision needs to be framed, a design challenged, or material risks made explicit.
01 / When this fits
Advisory work centres on a concrete decision, the evidence available, and a useful written or facilitated outcome.
Create a coherent view of initiatives, production-architecture gaps, target principles, and the decisions that should come first.
Challenge a proposed design before material investment or release and make assumptions, risks, and unresolved choices visible.
Review authority, tool use, identity, permissions, memory, human control, observability, and blast-radius decisions.
02 / How it works
The first conversation establishes the decision, urgency, available evidence, and whether Anton is the right person to help.
If there is a fit, the written scope makes the inputs, activities, outcome, timing, fee and any confidentiality arrangements clear before work begins.
03 / Useful reading
These practical articles show the methods behind the training and advisory work.
Architecture review
A practical 12-question AI architecture review checklist for business fit, data, RAG, agent authority, security, evaluation, operations, and ownership.
Enterprise AI architecture
A practical enterprise AI architecture framework covering five runtime layers, three control planes, and the questions that expose production gaps.
04 / Start a conversation
Describe the decision or architecture problem and the broad timing. Do not include confidential evidence in this first message.