Agentic AI Comparison:
aiMotive vs May Mobility

aiMotive: 7

aiMotive develops L2+–L4 autonomous driving and ADAS software stacks, simulation, and hardware acceleration IP but does not itself operate public autonomous fleets. Its aiDrive software targets multiple use cases (highway pilot, automated parking, and higher levels of autonomy), and aiSim provides an ISO‑26262‑certified virtual testing environment, enabling extensive training and validation in simulation. As a technology supplier, aiMotive’s autonomy manifests via integration into OEM programs (e.g., Stellantis’ STLA AutoDrive roadmap) rather than branded, fielded services. The score of 7 reflects strong technical capabilities and simulation depth, but with fewer publicly documented, end‑to‑end Level 4 deployments visible to the public compared to May’s city‑scale, branded microtransit services. The autonomy is also more distributed across many potential use cases and development stages at OEM partners, making evaluation less concrete from a service‑outcome perspective.

May Mobility: 8

May Mobility operates Level 4 autonomous shuttles in geo‑fenced areas, with services in multiple U.S. cities and Japan. Its MPDM framework allows the vehicle to simulate and evaluate thousands of potential trajectories 10–15 seconds into the future, modeling interactions among multiple agents and selecting context‑appropriate behavior. This architecture is designed for high‑autonomy, complex urban environments (pedestrians, cyclists, intersections) rather than only highway use. Historically, May has used safety drivers/vehicle operators, but it has begun rolling out driverless microtransit vans in controlled domains (e.g., Peachtree Corners deployments) as confidence and regulatory approvals increase. The score of 8 reflects robust domain‑specific Level 4 capability in live service, balanced against the geo‑fenced and use‑case‑specific nature of its autonomy and ongoing reliance on operational constraints.

aiMotive: 6

aiMotive’s primary users are automotive engineers, OEMs, and Tier 1 suppliers integrating aiDrive software, aiSim simulation, and aiWare IP into vehicle platforms and SoCs. For these technical customers, aiMotive emphasizes toolchain integration, open interfaces, and hardware‑agnostic design, which can improve developer usability. However, its products require significant engineering resources, functional safety processes, and system integration at the OEM level. There is no direct consumer‑facing interface or turnkey service akin to May’s app‑based microtransit; the end rider experiences aiMotive’s technology indirectly as part of the vehicle’s ADAS or automated driving features. Consequently, while usability may be strong for professional developers, from a broad “agent” perspective encompassing typical mobility stakeholders and end users, ease of use is lower and more specialized than May’s turnkey services.

May Mobility: 8

May Mobility designs its services to be simple for riders and city partners. For riders, services such as A2Go in Ann Arbor use a familiar app‑based, on‑demand model with 18 designated stops over a 2.64‑square‑mile area; users simply hail shuttles via app and board at marked locations, similar to other microtransit and ride‑hailing experiences. Vehicles are shared, on‑demand, and integrated into local mobility ecosystems, aiming to reduce the friction of using transit and improve rider experience. For municipalities and agencies, May offers end‑to‑end project support—route design, operations, and fleet management—reducing integration complexity for non‑technical stakeholders. The presence of autonomous vehicle operators (where applicable) also adds perceived usability and reassurance for first‑time riders. These factors support a high ease‑of‑use score from the end‑user and city‑partner perspective.

aiMotive: 8

aiMotive’s offerings are designed for broad flexibility across OEM programs and deployment contexts. aiDrive is hardware‑agnostic software that can support multiple levels of automation (from ADAS to higher autonomy) and a variety of use cases (highway pilot, urban pilot, parking). aiSim, as a simulation platform, is also highly configurable, supporting different sensor configurations, environments, and validation workflows, and has been developed to meet stringent automotive safety standards. aiWare IP can be integrated into diverse chip designs, giving hardware partners flexibility in how they implement neural network acceleration. Furthermore, as part of Stellantis, aiMotive technology is positioned to be used across multiple vehicle platforms and brands within the STLA AutoDrive framework. This broad, platform‑level adaptability across many programs and regions supports a higher flexibility score compared with May’s more focused service domain.

May Mobility: 7

May Mobility provides flexible, on‑demand microtransit services that can be tailored to individual cities’ challenges, including custom route design and service models in collaboration with municipalities. Its MPDM decision‑making framework is explicitly designed to handle a wide range of behaviors by simulating numerous possible futures and selecting context‑appropriate policies (e.g., driving faster or slower depending on environment), which adds behavioral flexibility in complex urban settings. May can adapt service footprints over time (e.g., adding stops, extending coverage within a geo‑fence) and deploy in diverse settings (U.S. cities, Japanese cities, academic campuses). However, its operational model is focused on shared microtransit within geo‑fenced domains; it does not span the full breadth of driving scenarios (e.g., long‑distance highway, personal‑vehicle integration across OEMs). Thus, it is flexible within its service niche but narrower in overall automotive use‑case coverage.

aiMotive: 8

aiMotive’s primary revenue sources are likely software licensing, engineering services, and IP agreements for aiDrive, aiSim, and aiWare, especially after its acquisition by Stellantis. For OEMs and Tier 1s, using aiMotive’s modular, hardware‑agnostic stack and simulation tools can reduce development time and cost versus building an entire autonomous driving ecosystem in‑house, especially around safety‑critical simulation (aiSim) and neural network acceleration (aiWare). Because aiMotive does not bear the capital expenditure of operating fleets or running transportation services, its cost structure is relatively lighter than an operator’s; costs accrue mainly to R&D and integration support, which can be amortized across many vehicle programs. For OEM customers, this can be cost‑efficient compared with ground‑up development. Thus, from a technology procurement standpoint, aiMotive scores higher on cost efficiency than a service operator like May.

May Mobility: 7

May Mobility operates a service‑based model where cities, transit agencies, campuses, or private partners procure turnkey autonomous microtransit solutions rather than purchasing vehicles outright. From a city’s perspective, this can be cost‑effective for specific corridors or first‑/last‑mile needs, particularly when compared with traditional fixed‑route expansion or fully human‑operated shuttle services, because AVs can operate at lower incremental labor cost once scaled and can be right‑sized for demand. May’s model of shared, on‑demand rides also aims to reduce per‑rider costs over time by improving vehicle utilization and encouraging mode shift from private cars. However, autonomous microtransit still involves substantial upfront and ongoing expenses (vehicles, sensors, operations, safety operators where required, maintenance, software updates), and unit economics are not publicly detailed. Relative to a pure software/IP supplier, May’s cost base is high, but for city partners, the bundled service can be economically attractive within targeted use cases, meriting a mid‑high cost score.

aiMotive: 8

aiMotive has strong recognition within the automotive technology and AV/ADAS engineering communities. It has been a well‑known independent AV technology supplier with multiple high‑profile partnerships, and its acquisition by Stellantis—one of the world’s largest automakers—significantly amplified its industry visibility. aiMotive technology is a core component in Stellantis’ STLA AutoDrive strategy, which is planned across multiple global brands and vehicle platforms, positioning aiMotive at the center of a large‑scale, multi‑brand deployment roadmap. While it may not be widely recognized by consumers, within OEM, Tier 1, and AV/ADAS engineering circles—where adoption decisions are made—aiMotive enjoys high awareness and credibility, warranting a higher popularity score relative to May in the broader automotive technology ecosystem.

May Mobility: 7

May Mobility has built a notable presence in the autonomous shuttle/microtransit segment. It operates or has operated eight unique fleets in the U.S. and Japan and has moved more than 300,000 riders worldwide. It partners with cities, agencies, and innovation ecosystems (e.g., MCity, Ann Arbor SPARK, Peachtree Corners) and positions itself as a key player in transforming urban mobility through equitable, shared transit. While it is not as globally visible as large consumer brands (e.g., Tesla, Waymo), within the niche of autonomous shuttles and public‑sector AV pilots, it has strong recognition and frequent coverage in mobility and transit media. Its brand is known in academic and municipal circles focused on AV pilots, justifying an above‑average popularity score.