# Business Model and Go-To-Market ## Motion: Land → Prove → Expand High-touch enterprise, **not** self-serve. The sequence: `Discovery → technical workshop → data review → narrow paid pilot → ROI report → expansion → multi-year contract` Beachhead is **tier-1 LNG operators**, starting in **Qatar**, then the broader **GCC**. Land on 1–3 assets, prove lead-time on a paid pilot, expand to the train and then the fleet. See [[Selling AI MOC]] and [[Renacore/Pilot Structure and KPIs]]. ## Pricing (inconsistent across documents — diligence flag) | Source | Figure | | ------------------ | ---------------------------------------------------------------------------- | | Company Overview | "multi-million ARR per train" | | Traction summary | "~USD $500k ARR per LNG train" | | Pitch deck | "$3–9M ARR per customer" | | BMC recommendation | pilots **$25k–$250k+**; first offer **$50k–150k** paid pilot over 3–6 months | | | | | | | | | | The spread between a $500k and a multi-million per-train figure is large and unreconciled. The BMC's modest pilot pricing is the most grounded number; the ARR headlines are aspirational. Pressure-test in diligence. See [[Industrial AI Unit Economics]]. ## Defensibility Renacore's durability rests on three of the [[7 Powers]]: switching costs (embedded in OT + workflows once trusted), counter-positioning vs. legacy reactive incumbents, and process power (physics-first quality). The relationship moat is real but not a Power on its own. See [[Defensibility Principles MOC]] and [[AI era Defensibility]]. ## Related - [[Renacore MOC]] - [[Renacore/Traction and Pipeline]] - [[Renacore/Buying Committee and Personas]] - [[The Age of Vertical Models]] - [[AI Eats Services Not Software]]