SOMA across nine hardware-enabled credit verticals.

GPU compute facilities sit at an acute convergence of hardware depreciation (around 50% in three 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 navigating that nuance rather than relying on market-feel LTVs.

Battery storage is now a scaled debt market, but the credit case depends less on the battery hardware alone and more on the revenue stack, offtake and tolling structure, degradation and augmentation assumptions, warranty and O&M coverage, and grid interconnection execution. SOMA's IRM scores integration risk between battery management software and grid dispatch systems — a failure point that has caused material curtailment events at operating BESS facilities. The MDRA evaluates State of Health degradation curves and replacement readiness across the facility's capital life. Post-close OTTM monitoring captures SoH metrics before they reach the financial statements, giving lenders early warning that quarterly reporting cannot provide.

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.

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 medical device finance is not generic medical equipment leasing. The distinction matters: a connected device's value — and its ability to generate reimbursement revenue — depends on regulatory software certifications, clinical workflow integration, and data transmission continuity that sit largely outside the borrower's control. An FDA 510(k) re-classification or HIPAA compliance update can render hardware non-deployable overnight without any mechanical fault. SOMA's IRM scores that regulatory software dependency specifically. The Contract Financeability Score evaluates whether reimbursement contracts and hospital agreements contain technology refresh or force majeure provisions that alter the debt service profile. SOMA's TCS assigns a continuity score that accounts for both device life and regulatory software runway.

IoT is best understood as a horizontal capability layer across SOMA's other asset classes rather than a standalone collateral category. The most financeable IoT exposures sit inside specific operating assets — fleets, industrial equipment, infrastructure nodes, metering, vending hardware, or healthcare devices — where identifiable asset ownership, telemetry rights, recurring service revenue, maintenance workflows, and a visible installed base can be assessed individually. SOMA's MDRA evaluates deployment readiness and the risk of maintaining firmware currency across distributed hardware networks at scale. The IRM scores connectivity dependency — specifically the degree to which device functionality is contingent on third-party cloud APIs or network agreements that can be altered unilaterally. Post-close OTTM monitoring can leverage IoT telemetry data directly as an early warning system, turning the asset class's native data richness into a lender monitoring advantage.

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.

Drone network financing is promising but still early — better characterised as contract-backed operating-company finance than a mature ABF market against drone fleets. Recoverable value does not sit in the airframe alone; the real underwriting stack includes software, airspace permissions, operating approvals, control systems, maintenance capability, batteries, telemetry, spare parts, and customer contracts. SOMA's IRM scores airspace regulatory software risk — the dependency of drone operations on certifications that may be altered by aviation authority rulemaking mid-facility, without triggering a default under conventional loan documentation. The Continuity and Step-In Playbook is particularly relevant here, given the limited secondary market infrastructure available to a lender seeking to execute a workout.

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.