AI strategy should begin with maturity, feasibility, risk, and governance, not tools. An overview of the FelixSchallerCOM advisory services for AI strategy, safety, and technical due diligence.

AI strategy should not begin with tools. It should begin with maturity, feasibility, risk, and governance.
At FelixSchallerCOM we have published a four-page overview of our AI Strategy, Safety, and Technical Due Diligence advisory services. The document outlines how we support organisations, investors, and engineering leadership in evaluating AI initiatives before major capital, technical, or reputational commitments are made.
A key focus of our work is the model-based AI Strategy Maturity Matrix: a structured framework to assess how far an organisation has progressed in AI adoption, which prerequisites are missing, and which initiatives are technically realistic, governable, and economically meaningful.
AI strategy should not be driven by hype, vendors, or isolated use cases. It should be built around one question: what conditions must be fulfilled before AI can be trusted to act?
The four-page service sheet covers all advisory areas, the methodology, and how engagements are structured. It is suitable for sharing with leadership, investment teams, or technical partners evaluating external advisory support.
[Link the PDF on import: AI Strategy, Safety & Technical Due Diligence, Advisory Overview.]

Formal motion estimation is dismissed as good only for small motion. A benchmark against pixel-exact ground truth shows that is false: large scaling and rotation are solved to sub-pixel accuracy. The real ceiling is the affine assumption, and it collapses at exactly the depth boundary that 3D reconstruction is made of.
Most perception stacks reason one frame at a time. The network detects, tracking is bolted on afterwards, and the system never really carries the world forward. A snapshot machine cannot validate cleanly, because the thing that would make its output trustworthy is the thing it discards between frames: continuity.
Gödel's incompleteness theorem, Hume's induction problem, the halting problem, and AI hallucination are not isolated failures of reason. They point to the same missing term: context.