For decades, robotics lived in research labs and YouTube highlight reels - technically dazzling, commercially irrelevant. That’s finally changing.

The cost curves of sensors, edge compute, and mobility systems have collapsed. What once required a $100K Boston Dynamics rig can now be built for under $10K. NVIDIA Orin-class compute can run transformer-based perception locally. Connectivity is cheap and reliable.

The result: autonomy is going modular. Instead of monolithic humanoids, we’re seeing domain-specific intelligent machines - purpose-built robots that do one job extraordinarily well and pay for themselves fast. The winners will look less like science experiments and more like vertical SaaS with legs.

Why now

• Hardware deflation: LiDAR, depth, and radar stacks now cost hundreds, not tens of thousands.
• Edge intelligence: LLMs and vision-language models can run inference locally, no cloud latency.
• Labor shortages: Every field-based industry — from agriculture to facilities — faces 20–50% labor gaps.
• Connectivity & uptime: 5G, LoRa, and Starlink enable 24/7 fleet management and OTA updates.

Together, these shifts make commercial autonomy finally viable — not as a demo, but as a business.

Opportunity areas we’re excited about

• Commercial environment robotics – AI-enabled janitorial, inspection, and inventory robots for airports, hospitals, and warehouses. Real-time anomaly detection, floor mapping, and stockout alerts.
• Infrastructure & security drones – Specialized aerial systems that autonomously inspect power lines, solar farms, or perimeters, paired with analytics that flag risk and dispatch maintenance.
• Industrial task automation – Low-cost, reliable subsystems for repetitive field or facility tasks like delivery, sweeping, or basic maintenance.
• Vertical stacks – Full-stack platforms that integrate hardware, sensors, and software for specific industries (utilities, construction, manufacturing), monetized through robotics-as-a-service or software