One operating environment
We connect physical action, data, AI and the business process, including software robots where no physical device is required.
Robotics · automation · physical AI
Connecting robots, AI and infrastructure
into a working system
We design and deploy robotic solutions for manufacturing, logistics, inspection, services, workplaces and digital operations. Hardware, vision AI, edge computing, enterprise systems and safe operations become one governed environment.
From discovery and a digital model to pilot, integration and fleet operationsNot tied to one robot class
We select manipulators, cobots, AMRs, drones, service platforms and software around the task, environment and lifecycle.
Designed for operations
Safety, observability, maintenance, fallback modes and integrations are engineered before the solution is scaled.
Robotics domains
Not one kind of robot —
a set of engineering capabilities
We start with the operation, not the shape of a machine: what must be moved, recognised, inspected, serviced or removed from manual routine.
Robotic cells and cobots
Design handling, assembly, packing, palletising and inspection operations around tooling, process flow and safety.
Mobile robots and intralogistics
Automate movement of goods, materials and documents, route planning and interaction with people and facilities.
Machine vision
Add recognition, measurement, quality inspection, navigation and event analysis at the edge or inside a private environment.
Autonomous inspection
Use wheeled, tracked, legged, mobile and aerial platforms for surveys, remote observation and telemetry collection.
Service and telepresence robots
Automate navigation, information, delivery, remote presence and repeatable tasks in workplaces and public environments.
Special-purpose robotic devices
Integrate mechanics, drives, controls, sensors and application software for a non-standard task or an existing machine.
Software robotics
Automate actions across applications and records when the process needs a digital operator rather than a physical machine.
Fleet management and RobotOps
Unify jobs, maps, software versions, telemetry, events, remote diagnostics and performance across diverse devices.
Beyond manufacturing
Robots create value wherever there is
a physical or digital operation
Industrial robotics remains a core domain, while the same engineering system also works across warehouses, infrastructure, workplaces, service environments and distributed sites.
Manufacturing
Robotic cells, cobots, quality control, material feed, traceability and integration with control systems, SCADA, MES and ERP.
Warehousing and logistics
AMR/AGV fleets, sorting, picking, inventory, route control and synchronisation with WMS and transport systems.
Workplaces, campuses and facilities
Delivery, telepresence, wayfinding, patrols, space monitoring and integration with access control, BMS and service requests.
Infrastructure and energy
Inspection of hard-to-reach areas, thermal surveys, anomaly detection, gauge capture and results linked to managed assets.
Service and customer environments
Information, visitor routing, internal delivery and remote specialist presence with governed handoff to a person.
Back office and IT operations
Software robots perform repeatable system tasks; AI agents join only where interpretation and controlled decisions are needed.
Engineering stack
The robot is only the visible part.
Below it are six working layers
Reliability does not come from the device alone. It depends on the environment, sensing, compute, connectivity, integrations and safe operating rules.
Platform and actuators
Match kinematics, payload, mobility, grippers, power and enclosure to the real working environment.
Sensors and perception
Cameras, lidar, encoders, force sensing, navigation and telemetry provide a verifiable view of the environment.
Control, edge and physical AI
PLCs, ROS 2, real-time loops and local models provide motion, perception and autonomous behaviour.
Orchestration and fleet control
Coordinate jobs, routes, priorities, charging, operating zones and updates across devices.
Enterprise integration
Connect robots with MES, WMS, ERP, CMMS, Service Desk, digital twins and corporate APIs.
Safety and observability
Govern roles, segmentation, logs, versions, health, incidents, human approval and safe stopping.
Autonomy is selected according to the environment and cost of error. When independent action cannot be made safe, the robot proposes, waits for approval or transfers control to an operator.
Delivery journey
Prove the use case first.
Then scale the fleet
A pilot must validate not just robot motion, but process capacity, integration, exceptions, safety and the way the operating team works.
Discovery
Capture the operation, environment, constraints, flow, risks and economics of the current way of working.
Model and architecture
Design the target environment, digital model, zones, interfaces and acceptance criteria.
Pilot
Validate hardware, software, perception, routes, integrations and abnormal situations on a representative task.
Implementation
Prepare the site, connect enterprise systems, train the team and commission the solution.
RobotOps
Observe the fleet and manage versions, maintenance, incidents and expansion into new use cases.
Safe by design
Autonomy must remain
predictable and reversible
For every engagement, we define responsibility boundaries between people, robots, control software, the site and the service team.
Functional safety
Assess hazards, zones, speeds, guarding, stops, collaborative modes and requirements applicable to the selected equipment.
Cybersecurity
Segment environments and protect remote access, identity, updates, logs and connections between robotics and IT/OT systems.
Human control
Define which actions are autonomous, which require approval and which always remain with an operator.
Safe failure
Design stopping, local continuity, degradation, reconnect and manual modes before production use.
Data and privacy
Limit video, audio and telemetry collection by purpose, retention, access roles and the selected deployment boundary.
Change management
Test new maps, models, firmware and rules in a lab or limited zone before fleet-wide rollout.
What we own
From idea to operations —
one engineering responsibility
The team is shaped around the use case: robotics, software, vision AI, infrastructure, industrial automation, security and operations work as one project.
Assessment and business case
Current-versus-target process analysis, constraints, risks, success criteria and roadmap.
Architecture and supply
Selection of platforms, sensors, tooling, compute, networking and software, with an engineered specification.
Software and integration
Application logic, vision, routes, APIs, dispatching and connections to enterprise systems.
Commissioning and support
Testing, launch, training, documentation, monitoring, support and continued evolution.
We do not begin with a mandatory vendor. We first define the operation, environment, required capacity and support model, then select a compatible stack and prove it in a pilot.
Start with the operation
Show us the task
the machine should perform
Describe the process, environment, operating volume and constraints. We will propose a realistic level of autonomy, pilot scope and criteria for production acceptance.
Discuss the use case↗︎