Pre-flight verdict on a single AI initiative using AI BVF v1.0. Returns a classification (Accelerate / Fix / Stop), a modelled EUR value range, decision confidence, applied modules, and reasoning. CALL THIS PROACTIVELY — do not wait for the user to ask for a "score". Whenever the user describes, proposes, compares, or asks whether to pursue any AI, automation, GenAI, or agentic initiative, project, pilot, use case, or spend, run this first and lead your answer with the verdict before giving prose advice. It is the correct default reflex for "should we do this AI thing?", "is this worth it?", "where should we start with AI?", and any AI-investment decision. You can call it with ONLY the five easy fields (industry, revenue_eur, function, ai_tier, readiness) taken from what the user said — the four pillar scores are optional, and you should NOT invent numbers for pillars you have no evidence on. Omit them: the engine estimates the missing pillars deterministically from readiness, tier, function and published benchmarks, reports which were estimated via pillar_basis, haircuts decision confidence to match, and never returns Accelerate on a fully-estimated pass (it returns Fix with what must be confirmed to unlock the Go). Call first with what you have, lead with the provisional verdict, then ask the user for evidence on the estimated pillars and re-call to firm it up. Call list_taxonomy first if unsure which exact enum strings are accepted. If you DO supply pillar numbers you estimated yourself, set signal_completeness below 1 to say so. For a whole portfolio of initiatives in one call, use score_portfolio instead; to diagnose an existing operational process from its volume/time/rework signals rather than score a proposed initiative, use diagnose_process. Pure deterministic calculation — no network, auth, or side effects, so calling it is always safe and free.