{"id":4781,"date":"2026-03-10T14:36:00","date_gmt":"2026-03-10T13:36:00","guid":{"rendered":"https:\/\/xoo.city\/?page_id=4781"},"modified":"2026-03-17T12:56:27","modified_gmt":"2026-03-17T11:56:27","slug":"network","status":"publish","type":"page","link":"https:\/\/xoo.city\/en\/network\/","title":{"rendered":"network"},"content":{"rendered":"\t\t
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The physical world is the largest uncomputed environment on earth.<\/h1>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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XOO builds that system<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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We build a street\u2011scale physical AI network that makes cities machine\u2011readable.<\/p>

Every street, building, and public space generates continuous signal \u2014 movement, occupancy, density, environmental state, context. None of it has ever been understood at scale, because no system existed that could perceive it, process it, and act on it in real time. Multimodal AI, running on our own hardware, deployed into the fabric of cities.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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01 - THE PROBLEM<\/h6>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Perception without intelligence is noise. <\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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None of it thinks. <\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Cities have been instrumented for decades. Sensors on every corner. Cameras on every block. Screens on every street. The infrastructure of observation is already there. The devices stay isolated, the data stays siloed \u2014 no shared model of what is actually happening in physical space, no system that sees across environments, infers meaning, and exposes that intelligence at scale. The gap is not sensors. The gap is cognition.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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02 - THE SOLUTION<\/h6>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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XOO: Physical AI network for city\u2011scale inference.<\/h1>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Every node runs multimodal AI. Every event feeds one global model.<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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On\u2011device models convert raw street\u2011level signals \u2014 movement, acoustics, environment, context \u2014 into structured events at the edge. XOO does not build the sensors that capture those signals; it builds the physical AI layer that turns any sensor mix into decision\u2011grade context. Those events feed a single intelligence layer \u2014 one schema, one context model, one data layer. With every new node the model compounds, and physical space starts to behave like software infrastructure.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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EDGE AI<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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On\u2011device models process multimodal sensor input <\/h4>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Movement, acoustics, environment, context \u2014 from existing infrastructure and emit structured events in milliseconds. Raw data never leaves the node. Only anonymized, structured events hit the network \u2014 privacy guaranteed by architecture, not policy.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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BACKEND<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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One global intelligence layer<\/h4>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Edge events feed a unified time\u2011series backend. Partners and operators consume structured context \u2014 feeds, dashboards, direct integrations \u2014 all reading from the same model. Because XOO owns the node, XOO owns the schema. That is not an integration advantage. It is a structural moat.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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SERVICES<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Built to fund rollout<\/h4>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Data products and programmatic services run directly on the event layer. Each node is economically self\u2011sustaining from day one. Every deployment expands the network, improves the model, and creates value across all stakeholders simultaneously.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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03 - THE PLATFORM<\/h6>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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XOO builds the nodes.<\/h1>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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The compute engine runs inside.<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Every XOO node is a purpose\u2011built multimodal compute unit deployed into public space under visible functions like charging infrastructure, screens, or street furniture. The node does not exist to capture more raw data \u2014 it exists to run physical AI on top of the sensors that are already there. Models on\u2011device fuse visual, acoustic, and environmental input into structured events and decision\u2011grade context. XOO owns the edge and the inference layer; the underlying sensor mix can change without touching the intelligence.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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HARDWARE<\/strong>: <\/em>Purpose\u2011built multimodal compute nodes with embedded inference \u2014 attached to existing sensors and host functions like charging, media, or monitoring.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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PROCESS<\/strong><\/em>: On\u2011device physical AI. Raw sensor data never leaves the node; models fuse multimodal input into structured, anonymized events and decision\u2011grade context.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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CLOUD<\/strong><\/em>: Edge events feed time\u2011series models and real\u2011time context surfaces, exposing one unified intelligence layer via APIs and dashboards.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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COMPOUND<\/strong>: <\/em>Every node improves model accuracy. Every deployment increases network value for every node already live.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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04 - USE CASES<\/h6>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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One inference layer. Many markets.<\/h1>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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One node. Multiple revenue lines.<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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The physical AI layer is built once. Use cases are different reads of the same events \u2014 not separate products and not separate deployments. One multimodal node generates decision\u2011grade signal for every vertical simultaneously. Adding a vertical means updating a model, not installing new hardware.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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\n\t\t\t\t\t\t\t\tAd Tech \t\t\t\t\t\t\t<\/h3>\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\tMedia that measures itself\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t<\/div>\n\t\t\t
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\n\t\t\t\t\t\t\tPhysical inventory that measures itself. Anonymized, real\u2011time audience signals turn any screen network into impression\u2011true, programmatic DOOH \u2014 no individual tracking, no new sensors.\n\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\n\t\t\t\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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\n\t\t\t\t\t\t\t\tStreet telemetry that becomes city services\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t<\/div>\n\t\t\t
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\n\t\t\t\t\t\t\tOperational intelligence from street telemetry.\nLive event streams turn multimodal sensor data into anomaly alerts, utilization signals, and predictive maintenance flags \u2014 so cities move from reactive firefighting to model\u2011driven planning, through one interface instead of another data silo.\n\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\n\t\t\t\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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\n\t\t\t\t\t\t\t\tMovement patterns that become demand signals\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t<\/div>\n\t\t\t
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\n\t\t\t\t\t\t\tMovement as infrastructure signal.\nPedestrian and vehicle flows become structured time\u2011series that drive utilization curves, demand forecasts, and location intelligence \u2014 every new node sharpening every existing model.\n\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\n\t\t\t\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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\n\t\t\t\t\t\t\t\tMeasurements that become city\u2011scale surfaces\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t<\/div>\n\t\t\t
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\n\t\t\t\t\t\t\tPhysical AI for environmental grids.\nDense, multimodal sensor networks become city\u2011scale air\u2011quality surfaces structured for ESG compliance, regulatory reporting, and urban planning \u2014 all from the same intelligence layer accessed via API.\n\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\n\t\t\t\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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\n\t\t\t\t\t\t\t\tAnomalies detected without surveillance infrastructure\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t<\/div>\n\t\t\t
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\n\t\t\t\t\t\t\tAnomaly detection as a software update.\nXOO\u2019s physical AI layer runs on nodes already in the field, turning multimodal signals into drone and threat detection without new hardware, without new sensors, and without building a separate surveillance infrastructure.\n\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\n\t\t\t\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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\n\t\t\t\t\t\t\tPhysical AI turns flow events into time\u2011window audience cohorts, so media buyers target against real reach signals instead of modeled estimates \u2014 outdoor inventory finally behaves like performance media.\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\n\t\t\t\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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05 - WHY NOW<\/h6>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Four forces have aligned.<\/h1>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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The window is open right now.<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Edge hardware is cheap enough, regulation is pushing privacy-first design, outdoor media is going data-driven, and cities can’t afford to build infrastructure the old way. The company that moves now defines the standard \u2013 before the market consolidates around someone else’s schema.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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1<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Edge hardware has crossed the cost threshold Running <\/h4>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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AI directly on street-level sensors is no longer expensive. The hardware race is over. What remains is the software layer that turns raw sensor data into structured intelligence \u2013 and whoever ships that layer first owns the installed base.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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2<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Outdoor media needs real audience data <\/h4>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Programmatic DOOH is growing fast, but it’s flying blind at street level. Advertisers are buying impressions they can’t verify. A physical AI layer that measures actual movement and attention becomes the attribution standard the industry is waiting for.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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3<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Regulation rewards on-device AI <\/h4>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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GDPR and its successors make centralized tracking architectures slow and legally fragile. Systems that process data on-device and emit only anonymized events can scale in markets where traditional surveillance infrastructure stalls.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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4<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Cities need infrastructure that pays for itself <\/h4>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Demand for public charging, monitoring, and safer streets is rising. Budgets are not. The only question is how to fund rollouts without constant subsidy.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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06 - TEAM<\/h6>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Built for city scale deployment<\/h1>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Most teams can do one of three things: build hardware, train models, or ship platform infrastructure at city scale. XOO does all three \u2014 integrated, under one stack.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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Mat Schubert<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t
CEO & Co-Founder<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Scaled mobility hardware across Europe \u2014 Bosch Mobility Services, Coup scooter sharing. Owns rollout architecture, partner distribution, and network economics. Knows how physical infrastructure gets deployed and financed at scale \u2014 asset leasing, revenue share, operator relationships.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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Tim Sch\u00f6llhammer<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t
Head of Plattform Engineering<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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10 years in system engineering and platform development. Builds the event layer that turns edge inference into structured context for partners and operators. Background in sourcing and procurement \u2014 engineers for real-world rollout constraints, not ideal conditions.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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Marc Zimmermann<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t
CPO & Co-Founder<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Builds the product narrative and vertical use cases \u2014 Ad Tech, ESG, Safety. Drives go-to-market from pilot to repeatable city rollout. Founded urbanmates, managed Flynn electric scooter. Knows how to turn an infrastructure deployment into a market position.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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Carlo Fritz<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t
AI and Data Modeling<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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5 years in computer vision and AI. 3 years in context analytics and graph architecture. Turns multimodal sensor signals into a robust event and context model \u2014 the layer that makes one node readable across every vertical simultaneously.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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Unsere Partner<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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\"htgf-400\"<\/figure><\/div>
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Request Pitch Deck<\/h1>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Have questions? We\u2019re happy to help.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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