Conrad is an evidence-controlled AI governance adviser. Instead of an open-ended chat response, you get a structured briefing: grounded in a ranked source hierarchy, checked against advisory boundaries, rated for confidence, and reviewed before it reaches you. Built for boards, executives, risk teams, and transformation leaders who need governance guidance they can actually act on.
Drawn from ranked legal, regulatory, and framework sources.
Evidence is pulled from curated sources and checked against an authority hierarchy before it gets used.
Every briefing carries a confidence level, worked out across ten source and context factors.
A human operator reads every pilot response before it goes out to the client.
Boards and executives can already get a confident-sounding answer out of a general AI tool in seconds. That's not the gap Conrad fills. The real question is whether that answer is fit for governance use: sourced, current, bounded, aligned to recognised frameworks, and honest about what it doesn't know. Most of the time, it isn't. That's the gap Conrad exists to close.
Generic AI produces confident statements that aren't tied to a source hierarchy, a governance framework, or a current regulator position. There's no way to tell a well-grounded claim apart from one that just sounds plausible.
Most tools don't separate general governance guidance from legal, financial, cybersecurity, employment, or certified compliance advice. That means responses often go further than any unregulated advisory service should.
Governance decisions need a repeatable method: an evidence trail, a confidence level, a limitation statement, a review step. A raw model response gives you none of that. Whatever's missing becomes your problem to catch.
Most organisations picked up generative AI tools well before they built the policies, ownership, and review steps to govern them properly. That gap between how fast people started using AI and how ready the organisation actually is keeps widening. Conrad is built to help close it.
Adoption climbs fast because anyone can open a chatbot and start using it. Governance readiness climbs slowly because it depends on policy, training, and oversight actually getting built. The distance between the two is where the risk sits.
Conrad is built for the people who actually carry AI governance decisions: board members, risk executives, transformation leads, compliance officers, and the advisers who support them. The briefing lands in your inbox. No portal, no integration, just a sourced, structured answer to the governance question that matters today.
Governance structures, accountability models, decision rights, AI registers, and oversight processes, all aligned to recognised frameworks.
Turning responsible AI principles into policies and operating procedures that actually hold up under internal and external scrutiny.
Spotting AI-related risks, control gaps, and mitigation actions, mapped to risk-management frameworks instead of general opinion.
Helping boards work out what to ask, what evidence to demand, and what controls need to exist before any AI use gets approved.
Acceptable-use policies, use-case approval workflows, and review requirements built on real governance standards.
Vendor governance, due diligence questions, procurement controls, and what ongoing monitoring should actually look like.
Every claim in a Conrad briefing traces to a ranked source. Primary material is prioritised over commentary, and the tier is declared in the output so the client can assess the basis themselves.
Confidence is not a label appended to satisfy a checklist. Where confidence is medium or low, the briefing explains the specific reasons, so the client knows what additional input would change the assessment.
Authoritative sources agree, the question sits clearly inside advisory scope, and the guidance is stable and settled.
The direction is clear, but how it applies depends on organisational details you haven't given us yet. Directionally sound, still needs your judgment.
The topic is emerging, sources disagree, the question is too broad, or this is really something a regulated professional should weigh in on first.
Confidence weighs ten factors, including source authority, recency, and jurisdiction clarity. See all ten factors →
Controls are built into the advisory process itself. Each one exists because uncontrolled AI advice fails in a specific, predictable way, and the control is there to catch it. These are design decisions, not marketing language.
Advice is grounded in an approved source hierarchy. General model memory never counts as evidence for a claim.
Every question gets checked against defined in-scope and out-of-scope categories before any analysis starts.
Material claims get checked against the evidence before a briefing is finalised. Anything unsupported gets flagged or cut.
A human operator reads every pilot response before delivery. Nothing ships without sign-off.
Scope is assessed before every briefing. Where a question approaches the boundary between general guidance and regulated professional advice, the briefing identifies it and recommends qualified professional input.
During the pilot, Conrad answers one AI governance question a day. The briefing lands in your inbox, structured, sourced, assigned a confidence level, and reviewed before it's sent. A lightweight sign-in (no password, no portal to integrate) is all it takes to try the service before committing to a full deployment.
