Goldman Sachs projects annual humanoid shipments reaching 1.4 million units by 2035 and values the market at $38 billion, a sixfold upward revision in a single year. Morgan Stanley puts the long-term opportunity at $5 trillion and roughly 1 billion units in service by 2050. Scale is no longer the question. Timing is.This is not a 2035 story. It is happening now. Tesla is running Optimus in its own factories and converting Fremont toward million-unit annual capacity.Agility's Digit is in paid commercial deployment across nine enterprise sites and is going public through a $2.5 billion transaction (AGLT).China's MIIT already mandates lifecycle tracking for more than 28,000 humanoids on a national ID platform. The robots are deploying. The infrastructure to keep them provable is not.Three structural forces are converging at once: the collapse in AI compute and training costs, bipedal actuator and battery technology reaching industrial-grade reliability as unit cost falls about 40% to the $30,000 to $150,000 range, and a U.S. manufacturing labor shortfall near 500,000 unfilled jobs today and projected to approach 2 million by the early 2030s (Deloitte and the Manufacturing Institute).The OEMs themselves are now naming the gaps. In July 2026, Agility Robotics CEO Peggy Johnson published six policy pillars for scaling industrial humanoids, calling for technician training pipelines, apprenticeships, industry-led safety frameworks, and robots as a service (RaaS) financing models. When OEM leadership petitions Washington for workforce and trust infrastructure, the inflection is no longer a forecast. It is on the record.Hardware production is accelerating. The operational infrastructure required to deploy, maintain, certify, and finance these fleets safely and reliably at scale does not yet exist.OEM leadership now says so publicly. Agility's six-pillar policy framework (July 2026) calls for expanded technician training and voluntary, industry-led safety frameworks. Voluntary frameworks only sustain public trust when compliance is verifiable, and no OEM can serve as the neutral verifier of its own fleet. The gap is now acknowledged from inside the industry.A CFO can justify the capital, a lender can finance the fleet, and an underwriter can price the risk, but only when maintenance history, parts provenance, and performance data are certified and auditable. CHRT™-certified technicians, predictive maintenance, and insurance-grade records are how that proof gets built.This ensures every stakeholder is connected within the RobotCare™ services ecosystem.Every calibration, sensor swap, and repair is cryptographically attested in the Robot Health Passport™🛡️, compounding into a cross-OEM dataset no single manufacturer can assemble. Our patent-pending HR IV™ (Humanoid Robot Insurable Value) algorithm converts that verified history into a pricing rail for insurers, lenders, and resale markets, translating maintenance quality directly into lower premiums, financeable collateral, and higher residual value.This is also how small and medium enterprises (SMEs) get in. OEMs are now pointing to robots as a service (RaaS) models to unlock SME adoption, and RaaS only works when residual values are underwritable. HR IV™ converts verified maintenance history into exactly that underwriting rail, turning the Robot Health Passport™🛡️ into financeable collateral for large enterprises and SMEs alike.