Learning Center
The concepts behind verifiable AI, in plain language.
No vendor fog. These are the explainers we send to operations leaders and engineers who want to understand what “verified decision” actually means before they buy anything — from us or anyone else.
01
Audit trails for AI decisions
What a compliance-grade decision record contains, why post-hoc "explainability" isn't it, and what regulations are starting to expect.
2 min read
02
What is the Model Context Protocol?
A plain-language introduction to MCP — the standard that lets AI agents call external tools — and what it changes for operational software.
2 min read
03
Neuro-symbolic AI in practice
The architecture pattern combining language models with symbolic reasoning — why it exists and what it looks like in an operational product.
2 min read
04
Constraint solvers and unsat cores, explained
What an SMT solver like Z3 actually does, why its answers are trustworthy, and what an "unsat core" buys you in operations.
2 min read
05
LLMs as translators, not oracles
The single design choice that separates reliable language-model systems from impressive demos — and how to evaluate it from outside.
2 min read