Hardware-as-a-service (HaaS) is gaining momentum across a variety of industries. Many of the early adopters of HaaS are in robotics, offering robots-as-a-service (RaaS) to decrease barriers to entry and improve overall value to customers. Others offer machine-as-a-service (MaaS), device-as-a-service (DaaS), or equipment-as-a-service (EaaS).
Some companies pitch outcomes more than assets, offering data-as-a-service or platform-as-a-service models. From network-as-a-service to facades cleaning; managed service providers (MSPs) to managed security service providers (MSSPs); and autonomous construction equipment to diagnostic sensors and 3D printers, these companies are on the cutting-edge of their fields.
This post is part of a series about modern hardware companies, their business models, and the future of HaaS. For more, see posts from early and late March, early and late April, and early and late May.
Fieldwork Robotics develops autonomous soft-fruit harvesting systems built for delicate, high-value crops like raspberries. Their lead platform, Fieldworker 1, combines four robotic picking arms, AI-enabled computer vision, 3D sensing, and machine-learning models that detect ripeness, identify fruit position, and optimize harvest timing. Designed for unstructured environments like polytunnels, the system handles soft fruit without damage and can operate as part of a supervised fleet, in which a single operator monitors multiple robots. The machine’s modular design allows it to adapt to different crop layouts, and its perception stack uses colour imaging, depth sensing, and spectral analysis techniques to minimize missed fruit and reduce waste.
The company’s primary commercial strategy is Harvesting-as-a-Service, a subset of hardware-as-a-service (HaaS). In this model, the company retains ownership of the robots and growers pay based on harvested output (typically per kilogram of berries). This converts seasonal labor costs into a predictable operating expense while reducing growers’ upfront investment. Fieldwork also offers direct robot sales for customers that prefer ownership, supported by recurring service and maintenance contracts. The company also plans to develop data and analytics subscriptions from harvested imagery and yield data, creating a future recurring software layer. This mix of service-based harvesting, optional CapEx ownership, and emerging data services positions Fieldwork as a hybrid HaaS business with a strong services backbone.
“Harvesting-as-a-Service lets growers start small, prove labor savings in real operating conditions, and scale with confidence before committing to full fleet ownership,” explains Fieldwork’s CTO Sid Shaikh. “We offer HaaS, direct sales, and leasing models to align with growers at the different stages of their technology adoption.”
Solinftec
Solinftec develops a hybrid hardware-and-software platform designed to optimize agricultural operations from planning through execution at field scale. At the core of its offering is the ALICE AI Platform, a cloud-based agronomic intelligence system that processes trillions of data points each year to support real-time decision-making across agronomy, logistics, and fleet operations. ALICE is complemented by SOLIX, a solar-powered autonomous field robot designed to live permanently in the field, performing continuous scouting, targeted spraying, pest control, and crop development monitoring. Together, the platform enables plant-level visibility and intervention across millions of acres, with a focus on increasing productivity while reducing chemical use, fuel consumption, and environmental impact.
Solinftec operates a hybrid business model that combines enterprise SaaS with full robotics-as-a-service deployments. The ALICE AI Platform is sold as subscription software to farmers, ag retailers, and service providers, generating recurring revenue tied to acres managed, fleets monitored, and operations optimized. SOLIX extends this model into the physical world through a service-based approach marketed as “Clean Field as a Service,” in which autonomous robots, AI models, and field operations are bundled into recurring, outcome-driven engagements rather than sold as one-time equipment purchases. Hardware, sensors, software, and ongoing support are delivered together, allowing Solinftec to scale recurring revenue through both digital and in-field services.
Yanmar
Yanmar delivers a broad portfolio of agricultural and industrial equipment designed for durability, efficiency, and long service life. The company’s U.S. offerings include compact tractors, utility vehicles, diesel and industrial engines, marine propulsion systems, and related implements for farming, landscaping, construction, and OEM applications. While Yanmar’s global R&D pipeline includes autonomous and robotics-enabled platforms, the U.S. portfolio remains centered on proven equipment deployed at scale, complemented by embedded controls and optional connectivity features that support performance, diagnostics, and lifecycle management.
Yanmar operates a primarily hardware-led, hybrid HaaS business model. Equipment is sold as CapEx through an extensive dealer network, with recurring revenue generated through parts, service programs, maintenance contracts, and optional digital features. Telematics and connected capabilities—such as machine health monitoring, diagnostics, usage tracking, and maintenance alerts—are available on select equipment through systems like SmartAssist, typically bundled with the machine or offered as add-on services. These digital capabilities play a meaningful role in sustaining recurring revenue by supporting service engagement, uptime optimization, and long-term customer relationships.
ISEE
ISEE develops fully autonomous yard truck solutions designed to modernize logistics yards and distribution hubs. Its system combines autonomous driving software, sensors, onboard compute, and vehicle integration to enable safe, predictable, and continuous operation in complex, mixed-use yard environments. Built to operate alongside people and conventional equipment, ISEE’s technology focuses on anticipating unexpected behavior and adapting to dynamic conditions, helping customers improve throughput, safety, and consistency while reducing labor constraints and operational variability. The company’s autonomous yard trucks are deployed in live customer environments, with over 100,000 fully autonomous moves completed to date.
ISEE operates a solution-led business model that bundles autonomous driving software with vehicle hardware and ongoing operational support. Rather than selling autonomy as a standalone product, ISEE delivers an integrated system that includes continuous software updates, safety validation, and yard-level integration over time. Its deployments align most closely with a hardware-as-a-service model, in which hardware and software are bundled together under recurring commercial agreements. This approach reflects the operational realities of industrial autonomy, where reliability, uptime, and continuous improvement are central to customer value.
Zippedi
Zippedi delivers an end-to-end retail intelligence system built around autonomous in-store robots and a cloud-based computer vision platform. Its mobile robots navigate live retail environments—grocery, home improvement, and mass retail—scanning shelves label by label and capturing more than one million high-resolution images per day. These images are processed through Zippedi’s AI stack to create a continuously updated digital twin of each store, enabling real-time detection of out-of-stocks, planogram non-compliance, pricing and label errors, backroom inventory issues, and in-store pickup inefficiencies. The software layer converts shelf data into prioritized, actionable tasks delivered through Zippedi’s Bruno mobile app, guiding store associates to exact shelf locations for restocking, relabeling, auditing, and order picking.
The company operates a robotics-as-a-service (RaaS), OPEX-led business model rather than selling robots as one-time CapEx equipment. Retailers subscribe to a bundled service that includes robot access, cloud AI, continuous algorithm updates, analytics dashboards, and operational support. A defining element of Zippedi’s model is its proprietary consortium structure, which spreads costs across retailers, CPG brands, and distribution or last-mile partners who all benefit from shared shelf-level data. This enables recurring revenue through subscriptions and data monetization while lowering per-participant costs and supporting rapid, phased rollouts across store networks.