Prax Labs runs webinars and seminars for the institutions we work with. We teach what AI is and is not, where it helps and where it is the wrong tool, its real risks, and how to bring it into a regulated business responsibly. Education first, because AI you do not understand is AI you cannot govern.
Sessions are tailored to the audience, from a board briefing to a working seminar for risk, compliance, and engineering. Live, interactive, and grounded in your industry rather than generic slideware.
Short, high-level sessions for leadership and boards: what AI changes, what it does not, and the questions to ask before you deploy it.
Hands-on sessions for risk, compliance, and technical teams on safe use, governance, and how AI decisioning fits real workflows.
Focused modules by function, for example model risk, SAR quality, or on-chain investigation, so each team learns what applies to them.
Each topic is a standalone brief. We assemble a program from the ones your teams need, from first principles to industry-specific judgment.
A plain-language grounding in modern AI: what a large language model is, how it is trained, and what it is really doing when it produces an answer. We separate genuine capability from hype, so teams can reason about AI instead of fearing or over-trusting it.
A short tour of the biological neuron, synapses, and how the brain learns, then a clear-eyed comparison to the artificial neurons inside a neural network. The goal is intuition: where the brain-inspired analogy holds, where it breaks down, and why that difference matters for what you can and cannot expect from AI.
The practices that keep AI trustworthy in a regulated setting: keeping a human in the loop, demanding evidence for every output, protecting sensitive data, versioning and logging decisions, and never letting a model take a binding action it was not authorized to take. Safety as a set of habits and controls, not a slogan.
Where AI goes wrong and how to catch it: hallucination and confident errors, bias inherited from data, prompt injection and misuse, over-reliance and skill atrophy, and the specific risk of sending confidential data to an external service. We cover how each failure mode shows up in practice and how to design against it.
The kinds of work AI is genuinely good at: reasoning over large, messy evidence, triaging volume, surfacing patterns a person would miss, and drafting defensible decisions with the evidence attached. We map these strengths to concrete jobs so teams can see where AI earns its place.
Judgment is the point. AI suits high-volume, evidence-rich decisions where reasoning can be checked and a human makes the final call. It is the wrong tool where the stakes demand certainty it cannot give, where data is too thin, or where a simpler rule would do. We give teams a practical test for deciding, case by case.
How AI decisioning shows up beyond finance, in security operations, critical infrastructure, defense, healthcare, and research, and what each field teaches about deploying it responsibly. Seeing the pattern across industries helps teams recognize what is fundamental and what is domain-specific.
Why the biggest model is rarely the right one for a regulated decision. We explain, without jargon, how a local, on-premise model specialized to your domain can match or beat a general frontier model on your task, while being ownable, auditable, cheaper, faster, and deployable inside your perimeter. This is the reasoning behind OraBrain, taught from first principles.
Frontier models are remarkable general-purpose tools. But for a specific, high-stakes, regulated decision, the trade-offs favor a model you specialize and own. Here is the comparison we walk teams through.
The goal is not the biggest model. It is the best decision on your task. A frontier model spreads its capacity across every subject imaginable. A specialized model concentrates it where you need it, and because you own and deploy it, you get the accuracy, privacy, cost, and auditability that a regulated business actually requires. That is the case for OraBrain, and we teach it from first principles so your teams can judge it for themselves.
Tell us your audience and what you want them to walk away understanding, and we will shape a webinar or seminar around it.
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