Full-Time

Robot Delivery Technician

Coco Robotics

Coco Robotics

1,001-5,000 employees

Fast, transparent zero-emission local delivery

Compensation Overview

$21 - $23/hr

Miami, FL, USA

In Person

Associate's

Category
AI & Machine Learning (1)
Required Skills
Robotics
Excel/Numbers/Sheets

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Requirements
  • Hands-on experience in robotics, electronics, bike shops, or similar environments.
  • At least 2 years of technical experience in diagnostics, repair, or maintenance.
  • Familiarity with mechanical and electrical systems.
  • Ability to read and interpret schematics and technical documentation.
  • Ability to lift 40 pounds.
Responsibilities
  • Prepare and inspect robots for each shift.
  • Diagnose, troubleshoot, and repair mechanical and electrical issues.
  • Collaborate with engineers to test new functionalities.
  • Deploy and support robot fleets across active markets.
  • Conduct routine inspections and log performance data.
  • Assemble, maintain, and repair robot hardware.
  • Diagnose mechanical, electrical, and software issues.
  • Track recurring issues and contribute to hardware improvements.
  • Ensure robots meet safety and operational standards before deployment.
  • Collaborate with cross-functional teams to optimize performance.
Desired Qualifications
  • An associate degree or equivalent technical experience in robotics or engineering.
  • Experience with semi-autonomous robotic systems.
  • Skill with diagnostic tools and performance tracking.
  • Comfort using Excel or Google Sheets for reporting.
  • Strong communication and problem-solving skills.

CocoDelivery.com delivers food from local restaurants to customers’ homes or workplaces. It works by charging a per-order delivery fee, with a transparent pricing model that has no markups or tips and is shared with partner restaurants to cover costs. The service emphasizes speed and temperature, aiming to deliver faster, hotter, and fresher meals, while operating with a zero-emissions footprint. It differentiates itself from competitors through clear, low per-order fees, a restaurant-friendly revenue split, and a sustainability focus. The overall goal is to help local restaurants reach more customers, reduce environmental impact, and provide convenient, affordable, and dependable delivery through high-volume orders.

Company Size

1,001-5,000

Company Stage

Late Stage VC

Total Funding

$121.5M

Headquarters

Santa Monica, California

Founded

2020

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Simplify Jobs

Simplify's Take

What believers are saying

  • August 19, 2026 Little Caesars rollout broadens enterprise demand across Los Angeles, Chicago, Miami.
  • April 30, 2026 Ralf Wenzel joined the board, strengthening expansion execution.
  • June 2025's $80 million round funds fleet growth and deeper platform partnerships.

What critics are saying

  • Chicago's March 2026 bus-shelter crashes fueled petitions and scrutiny before May 2027.
  • Coco still depends on remote operators, exposing labor costs and failure points.
  • Regulators and city councils can restrict sidewalk robots after one high-profile safety incident.

What makes Coco Robotics unique

  • Coco Robotics runs the largest urban robot delivery platform, founded in 2020.
  • Coco 2 targets rain, snow, steep streets, and tight sidewalks across cities.
  • Direct integrations with DoorDash, Uber Eats, and Wolt reduce restaurant workflow friction.

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Benefits

Company Equity

Growth & Insights and Company News

Headcount

6 month growth

0%

1 year growth

0%

2 year growth

8%
PR Newswire
Aug 19th, 2026
Little Caesars teams up with Coco Robotics to power fast autonomous pizza deliveries.

Little Caesars teams up with Coco Robotics to power fast autonomous pizza deliveries. Aug 19, 2026, 09:00 ET Coco's robots power faster deliveries of Little Caesars HOT-N-READY(R) pizzas across locations in Los Angeles, Chicago, Miami and soon San Jose LOS ANGELES, Aug. 19, 2026 /PRNewswire/ - Coco Robotics, the leader in autonomous delivery, today announced a collaboration with Little Caesars, the third-largest pizza chain in the world, to bring autonomous robot deliveries to locations throughout Los Angeles, Chicago, and Miami, with Little Caesars deliveries coming soon to Coco's recently expanded operations in downtown San Jose. Coco's robots are currently serving participating Little Caesars locations, marking the beginning of a broader rollout to bring autonomous delivery to more Little Caesars guests. Orders placed through participating Little Caesars locations on DoorDash and Uber Eats may be fulfilled by Coco, providing a faster, environmentally friendly, and more efficient delivery experience. Coco integrates directly into both platforms' existing ordering systems, requiring no manual entry or extra steps for in-store teams. Orders move directly from the kitchen to the curb, where a Coco robot completes the final delivery to the customer. "This partnership is about delivering more value and convenience to our guests," said Trish Heusel, VP of Innovation at Little Caesars. "By integrating Coco's autonomous robots, we can deliver hot, delicious pizza in record time to more customers. With Coco, we're now able to make deliveries even more quickly. Automating deliveries also reduces congestion in our stores and helps get orders out faster during peak periods." "We're proud to partner with Little Caesars, an iconic brand known for its dedication to speed and value," said Melissa Fahs, VP, Enterprise at Coco Robotics. "By integrating our robots into Little Caesars operations, we're showing how autonomous deliveries can enhance the guest experience at scale, making ultra-fast, sustainable delivery a reality for millions of pizza lovers." About Coco Robotics Coco Robotics is the world's largest urban robot delivery platform, combining autonomous robots, real-world operations data, and advanced AI to power smarter, more efficient city logistics. Founded in 2020, Coco has completed over 500,000 zero-emission deliveries across the U.S. and Europe. The fleet continuously learns from millions of miles of real-world operations, giving Coco instant adaptability to new cities and environments. This data-driven intelligence allows Coco to expand rapidly while maintaining safe, reliable, and efficient operations. Coco's mission is to create more sustainable, reliable, and affordable last-mile logistics solutions in cities around the world. For more information, visit www.cocodelivery.com. About Little Caesars(R) Little Caesars, the Best Value in Pizza*, was founded by Mike and Marian Ilitch as a single, family-owned restaurant in 1959 and is headquartered in downtown Detroit, Michigan. It is the third-largest pizza chain in the world, with restaurants in each of the 50 U.S. states and 31 countries and territories. Known for its HOT-N-READY(R) pizza, Crazy Puffs(R), and famed Crazy Bread(R), Little Caesars uses quality ingredients, like fresh, never-frozen mozzarella and Muenster cheese and sauce made from fresh-packed, vine-ripened California crushed tomatoes. The brand is known for innovation and is home to the exclusive Pizza Portal(R) pickup, a heated, self-service mobile order pickup station. Little Caesars is also the Official Pizza Sponsor of the NFL. A high-growth company with over 65 years in the $150 billion worldwide pizza industry, Little Caesars continually looks for franchisee candidates to join the team in markets worldwide. In addition to providing the opportunity for entrepreneurial independence in a franchise system, Little Caesars offers a simple operating system, a reputation for taste and value, and strong brand awareness with one of the most recognized characters in the country, Little Caesar. Little Caesars is proud to be part of the Ilitch Companies family of businesses. *Limited to top 4 national pizza chains in the United States SOURCE Coco Robotics

Cyber Security Insiders
Jun 3rd, 2026
What can Pokémon teach us about securing agentic AI? You might be surprised.

What can Pokémon teach Cybersecurity Insiders about securing agentic AI? You might be surprised. At first glance, Pokémon and cybersecurity have nothing in common. One is a nostalgic game about catching digital creatures, the other a high stakes battle over autonomous AI systems. But the story of Pokémon GO shows something more important for agentic AI security: the most powerful systems are often built on data whose value only becomes clear years later, while the risk builds quietly in the background. When millions of players captured Pokémon, they unknowingly generated one of the most detailed spatial datasets ever created, including billions of geotagged images, movement signals, and environmental data. That foundation now powers Niantic Spatial, enabling real-world robotics and navigation in environments where GPS alone fails. A game became infrastructure. Agentic AI is now repeating that pattern inside the enterprise, only faster, more distributed, and harder to control. How Pokémon Helps Pizza Delivery Drivers Navigate The game Pokémon GO provides delivery robots with a centimetre-accurate view of the world thanks to AI and augmented reality (AR). This unusual example demonstrates that AI's paths are difficult to predict and the value of a dataset may only become apparent decades later. Understanding and carefully controlling the data is crucial, throughout its lifetime. It's rare to get detailed insights into an AI-driven project with reliable figures. But the two companies Niantic Spatial and Coco Robotics offer a glimpse behind the scenes. The startup Coco Robotics is working on delivery robots that will deliver pizza, amongst other things, in several cities in the US and Europe. And Niantic Spatial, the AI spin-off of Niantic, creator of the Pokémon GO app, provides precise visual data that Coco's robots use for orientation in urban jungles from Helsinki to Los Angeles, because GPS alone isn't sufficient. This virtual orientation system is AI-driven and has analysed data from Pokémon GO's massive dataset. For those less familiar with the app's functionality and popularity, consider this: within 60 days of its release in July 2016, 500 million people installed it and roamed the world's major cities in search of digital Pokémon. In the process, they shared billions of images of urban landmarks and their surroundings from every imaginable angle, including precise location data. In 2024, eight years after its launch, the game still boasted over 100 million players. Niantic Spatial utilises this vast repository of crowdsourced data from hundreds of millions of players to calculate a digital world model. A staggering thirty billion images were analysed using AI for this purpose, all of which followed typical smartphone image formats, and every image was linked to precise location coordinates, camera orientation, and device movement data. The data is therefore highly standardised and, in a sense, structured. It was all fed into Google's BigQuery and BigTable for analysis and long-term storage which, over time, was used to create the centimetre-accurate 3D map that Niantic Spatial and Coco Robotics are benefitting from today. Hidden Infrastructure from Scale What this use of Pokémon GO demonstrates is a pattern that is becoming foundational to agentic AI security: large volumes of low-value interaction data can evolve into long-lived, strategic infrastructure over time. No individual player thought they were contributing to robotics-grade spatial intelligence. Yet collectively, they built something far more durable than a game economy: a continuously updated digital twin of the physical world. That is the key lesson for enterprise AI. Agentic systems do not just consume data, they generate it at scale, across every workflow, decision, and API call. Over time, this creates hidden infrastructure such as logs, embeddings, prompts, tool outputs, and behavioural traces that may later become mission-critical assets or become liabilities in the form of emerging risk. The problem is that organisations rarely treat this early stage "low value" data as strategic. By the time its importance is understood, it is already deeply embedded across systems, and those liabilities have already become systemic risk. AI is Collapsing Cyber Timelines Another shift is accelerating this risk. Developments in frontier AI capabilities are shrinking the gap between vulnerability discovery and exploitation, turning cyber risk into a continuous pressure rather than a periodic event. In earlier software eras, defenders had time to patch, isolate, and respond. In agentic environments, models can interpret systems and chain tools to automate exploitation workflows. That compression of time changes the security model: detection, response, and recovery must now happen almost simultaneously. When combined with highly distributed AI agents operating across cloud services, SaaS platforms, and internal APIs, the attack surface expands rapidly in both speed and complexity. What used to be a "breach window" is becoming a permanent exposure state. Agentic AI Expands the Attack Surface Today's agentic AI systems are not passive tools. They act as privileged digital actors across enterprise platforms, reading emails, executing workflows, calling APIs, and interacting with other agents. That creates identity sprawl at scale. Every agent effectively becomes a new identity with permissions, context, and autonomy. Unlike human users, these identities operate continuously, at machine speed, and often across multiple systems simultaneously. This introduces new failure modes: * Over-permissioned agents accessing sensitive data * Orchestration chains that escalate privileges unintentionally * Cross-system automation loops that propagate errors Taken together, these failure modes show that resilience is shifting from reacting to incidents to continuous readiness and clean recovery, with the requirement to be owned at the executive board level. This requires three connected capabilities: * Resilience for identity systems. Agent identities must be centrally governed, continuously monitored, and kept within least privilege constraints. Without this, autonomous systems accumulate unchecked authority across the enterprise. * Protection and anomaly detection. As agentic systems operate at scale with data sources across on-premises, hybrid, and cloud environments, the data must be continuously validated and protected against corruption or manipulation. * Cyber recovery must extend to AI systems themselves. Organisations need the ability to restore clean versions of both data and autonomous agents, including a known-good operational state, often referred to as a Minimum Viable Company (MVC), to ensure continuity after compromise. Without this, autonomous systems amplify risk faster than traditional recovery models can respond. The Real Lesson from Pokémon Pokémon GO is not just a consumer tech success story. It shows how modern AI infrastructure is quietly built from mass participation and long-term data accumulation, with unexpected reuse over time. What begins as entertainment becomes infrastructure. What looks like noise becomes training data. And what feels optional becomes foundational. Agentic AI is following the same trajectory, but in enterprise systems - where the stakes are far higher and exposure is growing beyond organisations' ability to keep pace.

Onshape
May 14th, 2026
The Cloud-Native Workflow Behind Coco's Next-Gen Delivery Robot.

The Cloud-Native Workflow Behind Coco's Next-Gen Delivery Robot. READ TIME: Quick Summary * Coco Robotics is developing the Coco 2, an urban delivery robot designed for reliable operation across varied weather conditions, terrain types, and city environments. * The team uses PTC's Onshape and Arena to maintain a single source of truth across design, manufacturing, and the supply chain. * Cloud-native CAD and PLM have improved BOM management, release processes, vendor communication, and overall iteration speed. Building a delivery robot is one thing. Building one that survives Chicago winters, navigates rain-slicked Los Angeles streets, climbs steep gradients, and keeps running reliably, consistently, and at scale is something else entirely. That's the challenge Los Angeles-based Coco Robotics is solving with its next-generation delivery robot, the Coco 2. At the core of the effort is a product development process powered by one truth: To build a reliable product, teams need reliable design tools. A Delivery Robot built to handle anything. The Coco 2 is Coco's latest urban delivery robot, designed to operate in the kind of environments that would stop most robots cold. It's larger in cargo capacity than its predecessor, built from tougher materials for better field performance, and faster. Swappable terrain-specific tires handle wet streets and snow. Powerful motors climb steep gradients. A zero-turn-radius capability lets it navigate tight sidewalks and crowded urban corridors. For rain, an air blade system uses directed airflow to clear water droplets from the robot's sensors so it can see clearly in any weather. On board is a solid-state LiDAR system for reliable object detection, improved cameras, better communications hardware, and an ambient light ring that signals the robot's status and intent to people around it. Quick-swappable batteries make energy replenishment fast and simple in the field. The Coco 2 is designed for a roughly two-mile delivery range and currently operates in cities including Los Angeles and Chicago with plans for rapid global expansion. How Coco balances speed, cost, and quality. For Abhi Bhakuni, lead mechanical engineer at Coco, the core engineering challenge is straightforward to describe and difficult to solve: Build a product reliable enough to operate most of the time, across thousands of units, in dozens of environments, all while keeping cost and manufacturability in check. "Reliability is really important," he said during a webinar panel. "We want these robots to be operating most of the time." That means every design decision carries weight. Material choices, geometry, and structural design all get evaluated not just for performance but for how it holds up in the field and how practical it is to produce at scale. Iteration is essential to get that balance right. But iteration only works if the process behind it is tight. Mistakes that reach manufacturing cost time, real money, and create downstream problems that ripple through the program. The faster a team moves, the more important it is that their data, their files, and their processes stay in sync. Onshape-Arena Connection: one source of truth, across teams. Coco has been using Onshape for nearly 3 years, with Abhi personally on the platform for close to a decade. The company's product development process runs through the tightly integrated Onshape-Arena Connection that keeps design data, BOM, and sourcing details aligned across the entire organization. The workflow is straightforward in concept and significant in practice. Modeling happens in Onshape. When a design reaches a release milestone, the Onshape-Arena integration captures that data in a single shared system. From that point, everyone, including designers, supply chain teams, external vendors, is referencing the same version of a model. There is no ambiguity about which version a manufacturer is working from. "The big difference with the Onshape and Arena integrate workflow is it's like everything is aligned and files stay current," Abhi said. "The release process is cleaner, more visible and... it's really improved communication with vendors. In Arena, we can have our sourcing details very clearly laid down so our supply chain teams can just reference those. There is no confusion." For a team scaling globally, there's no room for a vendor working from the wrong file. The team at Coco streamlined design workflows with Onshape and Arena. 4 things that work better with Onshape and Arena. The shift from a legacy file-based workflow to Onshape and Arena has changed how Coco's team works in four specific ways. * BOM management is cleaner and more current. Design data flows directly from Onshape into Arena without manual export, keeping the bill of materials aligned with the live design at every stage * The release process is more visible. Every release is captured in Arena with a clear record of what was approved, when, and by who. There's no chasing files or reconstructing decisions after the fact. * Vendor communication is more reliable. Sourcing details live in Arena alongside the design data, accessible to supply chain teams and external partners without requiring a separate handoff. Abhi notes this has meaningfully reduced confusion with overseas vendors who still work primarily from formal documentation. * The overall system stays current. Unlike file-based PDM environments, where assemblies break and syncing is manual, cloud-native design means the data is always up to date. "In the past, I would have to be careful about managing data and communicating that carefully," Abhi said. "Now I just share a link." A platform that keeps getting better. One of the less obvious advantages of building on Onshape is that the platform itself evolves on a consistent cadence - releasing updates every three weeks. For a team like Coco's, iterating on a product that operates in the field every day, that matters. New features, improved workflows, and capabilities shaped by real customer feedback arrive regularly, without requiring upgrades, migrations, or IT intervention. For Abhi, that consistency is part of what makes Onshape a reliable foundation for a fast-moving product development team. "The platform is constantly evolving," he said. "New features are coming in at a consistent cadence and it genuinely feels like it's shaped based on user feedback and real customer needs." Building a reliable product is hard enough. The last thing a team scaling globally needs is to outgrow their tools. The Onshape discovery program. Learn how qualified CAD professionals can get Onshape Professional for up to 6 months - at no cost! * * Case Study * Robotics How Fauna Robotics Is Leading Humanoid Robot Development with Cloud-Native CAD & PDM 03.30.2026 See how Onshape cloud-native CAD+PDM accelerated Fauna Robotics' humanoid robotics design development with real-time collaboration and open API tools. learn more * * Blog * Evaluating Onshape * Electronics * Integrations * PCB Studio How Onshape PCB Studio Pulls 3D Component Models Straight from Altium 365 05.21.2026 Learn how the Onshape Altium Connector, a cloud-to-cloud integration, brings supplier-sourced 3D components into your mechanical assembly automatically. learn more Michael LaFleche * * Blog * Evaluating Onshape * Collaboration * Data Management What's the Difference Between File-Based and Cloud CAD? 05.20.2026 Not all CAD is the same. Compare file-based, cloud-hybrid, and cloud-native CAD across collaboration, file management, performance, accessibility, design history, security, and cost. learn more The Onshape Team * * Blog * Customers & Case Studies * Arena PLM Connection The Cloud-Native Workflow Behind Coco's Next-Gen Delivery Robot 05.14.2026 How the Coco Robotics team uses PTC's Onshape and Arena to manage design data, streamline releases, and scale globally without sacrificing quality. learn more The Onshape Team

Food On Demand
May 5th, 2026
Autonomous delivery reaches age of expansion.

Autonomous delivery reaches age of expansion. Scaling - that's the state of the autonomous delivery industry, no longer a futuristic vision for food ordering but one already soaring through the skies and navigating busy city sidewalks. That's the diagnosis CEOs Zach Rash of Coco Robotics and Keller Rinaudo Cliffton of Zipline made during the "Future of Delivery" address May 5 at the 2026 Food On Demand Conference in Dallas, where they discussed their companies' growth and sat down with FOD managing editor Bernadette Heier. During the "Future of Delivery" address at the 2026 Food On Demand Conference in Dallas, Zipline CEO Keller Rinaudo Cliffton said the company plans to expand service to Austin, Texas, and Phoenix by the end of the quarter, and another six major metro areas by the end of the year. The CEOs said autonomous delivery addresses the largest headaches on food delivery faced by both consumers and restaurants. After years of building technology and infrastructure capable of carrying out their AI-powered ambitions, the company leaders said their companies are ready and positioned to transform delivery and commerce as a whole. "There are about 5.5 billion instant deliveries happening in the U.S. every year via a 4,000-pound gas combustion vehicle driven by a human," Rinaudo Cliffton said during the address. "If you were to look at the buying behavior that we're observing in customers right now in Dallas, and expand that to the rest of the U.S., there would be 55 billion instant deliveries happening in the U.S." Rinaudo Cliffton reported a massive wave of consumer adoption of Zipline in the Dallas area, where the company spent much of 2025 scaling operations to serve 22 municipalities. Last month, the drone delivery platform launched operations in Houston, with Austin and Phoenix expected to join the list of service areas by the end of the quarter, and another six major metro areas to follow by the end of the year. Rash described Coco's key target service areas as dense cities, where food delivery congests streets already congested with traffic and strained for parking. The robotics company already serves seven cities with diverse climates, including Miami and Chicago, but expansion is set to reach dozens of cities between this year and next. "We've done over a million miles of deliveries in city environments around the world," Rash said, noting the brand has a quickly growing fleet of robots already numbering well into four figures. "Food On Demand work with almost 5,000 merchants at this point, that's across grocery chains, mom and pop restaurants and some of the largest enterprise brands in the world. While Zipline and Coco take different paths to deliver orders autonomously, both see severe weather as an opportunity rather than a roadblock to servicing consumers. "Everyone wants to get things delivered when it's miserable to walk outside, even if the place you're ordering from is actually quite close to you; it's a cold and miserable experience," Rash said. "There's this supply and demand mismatch that happens on the major delivery app today, and Coco aims to be the best partner for those sorts of conditions, which means we can get really good at solving a lot of hard engineering problems to deliver on a great experience." Coco Robotics CEO Zach Rash (right) looks at a delivery robot vision for the future of autonomous delivery with Food on Demand managing editor Bernadette Heier at the FOD Conference May 5 in Dallas. For Coco, navigating those conditions means robots capable of trudging through flooded areas and dense snow. For Zipline, weather resistance means drones that can fly through hail and heavy rain. "The challenge of building autonomous vehicles that operate reliably in the real world is that a lot of weird, extreme stuff happens in the real world," Rinaudo Cliffton said. Food On Demand actually ended up flying in hurricane-level winds a month ago." "This system is designed to handle all of this and ultimately operate 24/7/365, in a way that people can count on, day in and day out," he added. Beyond a willingness and capacity to deliver when human couriers prefer not to, both companies see a simple onboarding process with operators as crucial to expansion. "When you enroll to start having your deliveries fulfilled with Coco, the robot arrives, your staff just comes outside, lifts the lid, puts the order in, and it goes on its way," Rash said, noting an intentionally simple setup process with no costs for the operator. Rinaudo Cliffton said Zipline followed a similar emphasis on simplicity, noting that the approach makes integration a more obvious decision for operators. "None of the restaurant brands we work with want to do any kind of construction project or really want anything to do with drones, the FAA, or anything complex with technology," he said. "All they want is teleportation. They want a magical portal in the wall (where) you make food, pass it through the magical portal and it's immediately teleported directly in that moment." That magical portal Zipline uses is an in-house-designed product called "drop boxes," an order drop-off space that can be installed outside restaurants without requiring power or permitting. "We can deploy these drop boxes in just a few hours," Rinaudo Cliffton said... "Most of the new drop boxes that we're doing, especially with the Chipotle and a lot of other brands, we're now doing through-wall loading. So we actually attach the drop box directly to the wall, and then they can load the drop box without leaving the restaurant." Both CEOs said autonomous delivery methods have quickly gained traction among diverse demographics, with Rash recalling parents who insist on using Coco for delivery orders, and Rinaudo Cliffton mentioning the popularity of Zipline with nursing homes. As companies expand, the solutions they offer will become more evident and increasingly available. The coming year, the CEOs predicted, will be one of skyrocketing adoption for autonomous delivery. The 2026 Food on Demand Conference runs through Wednesday, May 7, at the Renaissance Addison Dallas Hotel. Keep up with Food On Demand! Demographic Information

PR Newswire
Apr 30th, 2026
Coco Robotics appoints ex-Foodpanda CEO Ralf Wenzel to board ahead of global expansion

Coco Robotics has appointed Ralf Wenzel to its board of directors as the company scales its autonomous delivery fleet globally. Wenzel brings two decades of experience in last-mile logistics, having founded Foodpanda and JOKR, and helped lead Delivery Hero through its 2017 IPO. He has built delivery operations across more than 40 countries and previously served as managing partner at SoftBank Group International. The appointment supports Coco's strategy of building an operationally experienced board as it expands into new cities and geographies. The company, founded in 2020, operates the world's largest urban robot delivery platform and has completed over 500,000 zero-emission deliveries across the US and Europe. Coco currently operates in major cities including Chicago, Miami, Los Angeles and Helsinki, partnering with platforms such as Uber Eats, DoorDash and Wolt.