Autonomous Robotics
We build the autonomy and deployment layer that turns robot hardware into working business outcomes — for last-mile delivery and industrial inspection.
Hardware is a commodity. The value lives in what runs on top of it.
request access →Navigation, SLAM, mission planning, and multi-robot fleet control — production-grade, hardware-agnostic, deployable across platforms.
Domain-tuned detection and anomaly recognition — not generic models. Trained on rare incident data from real deployments, improving with every mission.
End-to-end deployment for specific use cases — delivery, inspection, monitoring. Integrated into client IT landscapes, not bolted on top.
We take responsibility for the result — not just the uptime. On-site engineers, 24/7 coverage, contractual accountability for mission outcomes.
Actuators, batteries, base locomotion. Cost declining rapidly — number of $1B+ robotics companies grew from 2 to 11 between 2020 and 2025. We consume this layer, we do not build it.
VLA/RL architecture, world understanding. Already served by well-funded players (Skild AI, NVIDIA GR00T, Google DeepMind). Becoming a utility.
Autopilot, mission scheduling, remote control, edge runtime. Our primary build zone — 18–24 month window before the landscape hardens.
← We build hereThe end outcome for the client. Working scenario with vendor SLA accountability, enterprise integrations, on-prem deployment.
← We own thisThe only autonomous format combining door-to-door access, contactless handoff, and twice the speed of a wheeled rover. Navigates residential buildings, elevators, and entry points rovers cannot reach — at half the cost of a human courier by 2030.
Continuous inspection across oil & gas, metallurgy, chemical and coal facilities. Replaces static cameras and costly human rounds. Detects equipment anomalies, safety violations, and incidents in environments inaccessible or dangerous for people.
Industrial operations in oil & gas and metallurgy are governed by strict safety standards and hazardous-zone certifications impossible to acquire without deep local presence, operational history, and integration into local enterprise IT ecosystems that global players cannot replicate quickly.
Industrial AI cannot be sourced off-the-shelf. Safety gear detection in extreme conditions, smoke-obscured anomaly recognition — proprietary datasets that compound with each deployment.
Enterprise security buyers require a local legal entity, native-language support, and engineers who show up on-site. We are designed for this from day one — not retrofitted onto a remote product.
Not locked to a single hardware OEM. Hardware-agnostic architecture accelerates go-to-market and avoids the scaling constraints of full-stack ownership. Clients get vendor resilience and lower capital expenditure — we get faster deployment cycles and better unit economics.
Autonomy stack, navigation, and fleet control layer in development. E-grocery and industrial monitoring MVPs underway. Pilot negotiations active for residential last-mile delivery and data center inspection. Active investment round.
E-grocery delivery in premium residential segments. Industrial monitoring pilot at oil & gas facility. 3–5 enterprise clients. First contract renewals. Repeatable deployment process formalized.
Broader residential and medical deployment. Industrial coverage expanded. 80% of missions without human operator. Fleet density drives data flywheel compounding. 10–15 enterprise clients.
Full series production. Domain AI models at defensible depth. Operational moat established through deployment density and accumulated proprietary data. Series A or strategic minority investor.
Strategic partnerships in key global markets. Platform licensing to tier-1 robotics operators. Technology and operational IP positioned for joint ventures at scale.
End-to-end experience scaling autonomous vehicle and robot fleets to commercial operation. Product architecture across multiple embodiments and real-world deployments.
RL research and engineering for legged robots. Training pipelines, simulation environments, and deployment of learned policies to physical hardware at scale.
Deep learning from frontier AI labs and large-scale production systems. Industrial inspection, anomaly detection, and safety-critical visual inference.
Full-stack sensor fusion and localization for autonomous platforms. Proven across large-scale multi-modal autonomous vehicle fleets in production.
Deep tech strategy, corporate development, and financial modeling. Track record structuring complex enterprise B2B deals in regulated industries.
Integrating autonomous systems into enterprise IT: process control, ERP, access management, and video analytics. Deep knowledge of industrial stacks and procurement cycles.