Score a single AI initiative using AI BVF v1.0. Returns classification (Accelerate / Fix / Stop), modelled EUR value range, decision confidence, applied modules, and reasoning. Use this as a pre-flight check before recommending any AI deployment.

For an initiative classified Stop or Fix, return concrete, deterministic recommendations that would flip classification toward Accelerate. Pillar-level targets with named actions and rationale. Answers the "what do I do next" question after score_initiative.

Calculate annual Organisational Drag Cost in EUR from misalignment between AI tier and organisational readiness. The hidden cost of structural friction, not the cost of the AI build. Use to quantify the cost of NOT changing the operating model.

Check that a BVF portfolio document conforms to the AI BVF v1.0 schema before you score, store, or share it. Returns { valid: true } when well-formed, or { valid: false, errors: [...] } where each error names the failing JSON path and the rule it broke. Use this to catch malformed portfolios early; use score_initiative to evaluate a single initiative. Schema: https://bvf-app.vercel.app/protocol.

Look up the published benchmark rates for a business function and industry. Returns revenue/cost ranges, industry multiplier, and the cited source.

Return every accepted enum value for the AI BVF taxonomy: the full lists of industries, functions, ai_tier levels (gen1/gen2/gen3), and readiness levels. Call this first when unsure which exact strings score_initiative, recommend_improvements, calculate_pace_layer_drag, or get_benchmark will accept, so you pass valid values instead of guessing. Takes no parameters and has no side effects.