SOMA across five intelligent-hardware verticals.

GPU compute facilities sit at an acute convergence of hardware depreciation (useful-life assumptions run from three to five and a half years), deep software dependency, virtualisation, orchestration, and hyperscaler API lock-in, and capital cycles that can extend well beyond a device's useful life. SOMA's Integration Risk Map scores GPU model generation risk, interconnect obsolescence, and customer concentration in the contract stack, the three factors most likely to impair collateral value mid-facility. The Technical Continuity Score quantifies how much revenue relies on third-party orchestration layers the borrower does not control. The strongest structures in this market now combine asset and contract backing; SOMA's advance rate guidance gives credit committees a scored operational basis for giving credit committees a scored operational basis for that nuance, rather than relying on market-feel LTVs.

RaaS financing is a real but still emerging debt story, better characterised as provider-fleet equipment finance than a mature ABS market. The collateral case depends on hardware standardisation, redeployability, uptime reliability, maintenance capability, telemetry, customer diversification, and spare-part economics. SOMA's IRM scores the integration risk between edge AI inference software and mechanical hardware, a failure point where a software update that breaks robot calibration directly impairs revenue without any visible financial precursor. The TCS captures software depreciation risk as AI capabilities advance. Advance rate guidance reflects the residual value uncertainty inherent in purpose-built autonomous machinery, which rarely has an established secondary market.

Connected vehicle finance spans two distinct sub-markets that warrant separate treatment. Connected fleets and full-service leasing, where telematics, utilisation data, and servicing contracts are mature, represent the established debt market. Autonomy-linked fleets and robotaxi platforms represent the frontier, where software dependence and milestone risk become structurally more important to lenders. SOMA's IRM assesses OTA update dependency, the degree to which vehicle performance, regulatory compliance, or revenue-generating features depend on software the borrower does not control. The CFS evaluates whether fleet contracts contain technology refresh or software-change provisions that alter the debt service profile mid-term. SOMA's MDRA and OTTM provide dual-dimension monitoring across both hardware and software in a market where a single regulatory software change can impair an entire fleet's operational status.

EV charging debt is a real and growing market, but selectivity matters: scaled operators with better utilisation, high-quality sites, responsive maintenance, and route-critical locations are more financeable than fragmented early portfolios. SOMA's IRM scores charger-network software integration and CMS reliability, the two operational dimensions most frequently cited in downtime events. The Contract Financeability Score evaluates whether underlying agreements are structured around throughput KPIs that can support debt service in a below-forecast utilisation scenario. SOMA's monitoring triggers capture charger uptime and CMS continuity in near-real time, providing the early warning that quarterly operator reporting cannot.

Intelligent vending is more financeable than it may first appear, especially where telemetry, cashless payments, route density, shrinkage control, and location contracts are strong. Smart vending machines combine proprietary hardware with cloud-connected software (inventory management, dynamic pricing, remote diagnostics) and capital typically structured against machine count and throughput revenue. SOMA's IRM scores the degree to which machine functionality depends on network connectivity and third-party payment processing software, a risk frequently underestimated when a single provider services an entire estate. The MDRA assesses the operator's capacity to service a hardware portfolio at scale, which is the most common operational failure point in vending network roll-outs. The TCS captures software depreciation risk from evolving payment standards.