Autonomous Operations

Autonomous systems: multi-device operations

AI agents coordinating drones, robots and industrial systems under governed workflows — with people in control of the decisions that matter.

Orchestration

How multi-device operations run

1

Task intake

A business event or schedule creates a task with a defined scope.

Workflow
2

Agent planning

An AI agent plans which devices do what, within its permissions.

Agent
3

Device execution

Drones, robots and systems carry out their parts through standard interfaces.

Devices
4

Human checkpoint

Safety-critical or unusual steps wait for human approval; anomalies escalate.

Oversight
5

Verified close-out

Results, evidence and decisions are written to the audit record.

Audit
Governance

Autonomy within limits

  1. 1

    Data provenance

    Where data came from, when, which version, and under what licence.

  2. 2

    Identity

    Which person, agent, model or device is acting — verified, not assumed.

  3. 3

    Permission

    What that identity is authorised to read, decide or execute.

  4. 4

    Audit

    A tamper-evident record of inputs, decisions, actions and outcomes.

Every data input, model call, agent decision and device action is checked against provenance, identity and permission, and written to an audit record.
Use Cases

Where it is used

  • Coordinated drone and ground-robot inspection
  • Warehouse fleets working with WMS
  • Site monitoring with automated escalation
  • Scheduled data capture feeding digital twins

Boundaries

  • Full autonomy is not applied where it is inappropriate or unsafe.
  • Autonomy levels are set per site and per task in agreement with the operator.

Robotics Identity & Audit

Related Ventures

Ventures building on this

Physical IntelligenceIn Development

AI Robotic Logistics Warehouse

A smart, robotics-driven fulfilment warehouse for cross-border small-goods e-commerce — WMS, OMS and TMS with AI vision quality checks and robotics-assisted picking.

Layer
Open Physical Intelligence Layer — Industrial Intelligence
Industry
Logistics & Warehousing, Cross-border Trade
Core capabilities
Robotics-assisted picking · AI vision quality checks · WMS / OMS / TMS · Fulfilment-as-a-Service

On DNY infrastructure: Combines the Physical Intelligence Layer with enterprise integration and agents; operational data is governed in the Trusted Data Space.

RoboticsComputer visionAI agents
View venture
FAQ

Autonomous Systems — common questions

What is Physical AI?

Physical AI is artificial intelligence that perceives the real world through sensors, reasons about it, and acts through machines such as drones, robots and industrial equipment.

What is the Open Physical Intelligence Layer?

It is DNY’s unified connection layer between trusted AI infrastructure and real devices. It links models, agents, data governance, identity, security and audit with drones, robots, edge devices and vision systems, while staying compatible with multiple model, cloud and hardware vendors.

Is DNY a drone company or a robotics company?

Neither on its own. Drones and robotics are directions within the Physical Intelligence Layer. Specific drone and robotics businesses, such as DNY Aerial Systems and DNY Robotic Systems, are separate ventures that reuse the group’s infrastructure.

How are physical AI actions kept safe and accountable?

Every device, model and agent is bound to an identity and a set of permissions. Key decisions and actions are logged for audit, humans stay in the loop where full autonomy is inappropriate, and anomalies escalate to people.

What is an AI agent?

An AI agent is software that uses an AI model to plan and carry out multi-step tasks — calling tools, systems or devices — rather than only answering a single prompt.

How does DNY govern AI agents?

Agents run under defined identities and permissions, with human oversight and escalation for decisions where full autonomy is inappropriate, and with their actions recorded for audit.

Next Step

Coordinate devices under one governed workflow