Recent reports that the Trump administration is considering how to boost the robotics industry came at an opportune time for Tekcapital portfolio company Guident, which is currently preparing to list on the NASDAQ.
Following a major focus on building the United States’ AI capabilities, the US government is now engaging closely with robotic leaders and stoking interest in the sector ahead of any specific actions expected to be revealed next year.
Guident provides autonomous vehicle safety and robot monitoring solutions to the industry, a technology stack that can facilitate broader adoption.
As we all know, the bigger winners from the rise of AI so far have been the ‘picks and shovels’ companies, such as Nvidia, that provide GPUs, data centres, and the power source to facilitate the vast requirements of AI computing.
We could see a similar playbook for robotics and autonomous vehicles.
While much of the market’s attention has been on the latest LLM models, data centres, and how much the hyperscalers are spending on capex, the real-world application of AI in robotics has been quietly building a head of steam.
As mobile robots expand from warehouses into public spaces, the infrastructure enabling remote monitoring and control is emerging as the essential “picks and shovels” play in a market racing toward $124 billion by 2030.
Autonomous mobile robots are forecast to grow from $4.5 billion in 2025 to $9.3 billion by 2030, whilst delivery robots could quadruple from $0.8 billion to $3.2 billion over the same period. Annual shipments are expected to jump from 547,000 units in 2023 to 2.79 million by the decade’s end.
But regulators and insurers have imposed a reality check. California, Arizona, Florida, Michigan and Texas now require or encourage remote operator capabilities for autonomous vehicle deployments.
Florida-based teleoperation provider Guident has already deployed solutions that meet these requirements and is preparing to ramp up the rollout post its proposed NASDAQ IPO.
Guident’s investment case is straightforward: edge cases persist regardless of AI capability, public trust demands human intervention options, liability requires clear oversight protocols, and operational uptime depends on rapid remote resolution when robots encounter obstacles.
Many still fear the ‘Terminator’ scenario where robots act autonomously to harm humans. Guident’s capability to take control of autonomous vehicles and devices will help address these concerns.
Control rooms oversee full autonomy
Remote Monitoring and Control Centers (RMCCs) now function as mission control for distributed robot fleets, combining real-time video streams, sensor data and AI-assisted decision support. Guident’s platform exemplifies the emerging standard: redundant connectivity across terrestrial and satellite networks, distributed sensor fusion to detect risks across multiple vehicles, and human-in-the-loop capabilities allowing operators to provide guidance or assume direct control during anomalies.
The company demonstrated the model’s maturity in June 2025, achieving what it described as the first long-distance remote control of a full-size automated bus in operational transit. In November, Boca Raton launched a driverless shuttle route explicitly managed through Guident’s RMCC platform.
The possible application of robotics and, therefore, Guident’s RMCCs is enormous. Warehouse AMRs require remote intervention when aisles are blocked or unexpected obstacles are encountered.
Pavement delivery bots navigating pedestrian traffic need human assistance at complex crossings. Urban shuttles face construction zones and emergency vehicles. Industrial robots in mining, agriculture, and construction operate beyond reliable network coverage, demanding satellite-backed oversight. Healthcare robots in hospitals require strict protocol enforcement and emergency stop capabilities.
Security robots patrolling facilities with thermal cameras, LiDAR, and access control systems similarly connect to RMCCs, where operators can respond instantly to threats or safety incidents.
As more robots are released into our environment, the risk of accidents increases, underscoring the need for human intervention. Tesla still has human safety monitors in their Robotaxis in Austin. It’s expected these will be removed soon, but it’s very likely some form of human oversight will persist.
The infrastructure economics
RMCC providers operate on recurring revenue models, charging per robot, per mile or per operating hour. Once fleets build safety cases and regulatory approvals around specific platforms, switching costs rise sharply. As supervised robot populations grow, platforms accumulate edge-case data that improves AI assistance, creating competitive moats.
Guident positions its RMCC capability as the enabling infrastructure layer. This is the toolset allowing robots to operate safely whilst learning from human intervention. If robot revenues reach $124 billion by 2030 as forecast, even modest take rates for remote monitoring, connectivity and control software could generate substantial independent markets.
The companies solving these problems at scale won’t simply support robot deployment; they may define the standards that regulators and insurers expect, becoming the invisible operating system beneath autonomous operations worldwide.
