Autonomous systems, drones, and defense robotics

UAS, counter-UAS, emergency response, and robotic fleets operating in connected or austere environments.

Test AI perception, firmware, RF/C2, supply chain, autonomy boundaries, mission data, and Digital Twin state with safety and authorization gates.

Sector problems

What this environment has to get right

Fleets operate in connected and austere environments where a cloud-only console cannot see the vehicle or the link.
Firmware, command links, and supply chain have to be reviewed without assuming the vehicle can be taken offline.
Perception and autonomy models need test evidence before a mission, not a vendor claim.
Flight, radio transmission, and actuation have safety consequences and cannot be left to an unattended agent.

Regulations and frameworks

How AI SOAR supports the evidence, not the determination

Mappings help you collect and organize evidence. An assessor, examiner, auditor, or authorizing official still decides whether the obligation is met. The platform does not certify an organization or file a regulatory notice.

Framework	What it asks for	How the platform helps
NIST AI RMFOfficial source ↗	Govern, map, measure, and manage risk for AI used in perception, planning, and autonomy.	Benchmarks, adversarial tests, human review, and mission traces produce the measurement record for each model or agent.
NIST SP 800-82Official source ↗	Treat vehicles, ground stations, and robot cells as operational technology, not only as IT assets.	OT-safe discovery and a digital twin keep active testing behind an approval gate.
FAA Part 107 and Remote IDOfficial source ↗	Civil and public-safety UAS operations follow FAA registration, remote identification, and operating rules.	UAS reviews check firmware, remote identification, geofences, and command links. The default is evidence-only.
CMMC and DISA STIGs Official source ↗	Defense robotics and UAS programs protect covered information and harden supporting systems.	CMMC evidence workflows and STIG checks apply to the ground systems and data in scope. Flight and radio actions need a separate authorization.

Typical workflows

Illustrative missions, with a person still in control

These workflows show how documented capabilities apply. They are not customer case studies, and they do not describe a guaranteed outcome.

Evidence-only fleet review

Problem: A public-safety or defense fleet needs a current view of firmware, remote identification, geofences, and command links.
What the platform does: UAS workflows collect that evidence without transmitting or flying. Supply-chain checks cover components.
Human approval: Any flight, radio transmission, or other high-impact action needs a separate safety review and human approval.
Evidence: A UAS assurance report mapped to the rules that apply to that fleet.

Test a perception model before a mission

Problem: A program must show that an autonomy or perception model resists manipulation and stays inside policy.
What the platform does: Adversarial tests, benchmarks, and a mission trace run before the model is cleared. Low-confidence results go to human review.
Human approval: Reviewers decide contested results. The model is not cleared by the test harness alone.
Evidence: Scores, traces, and adversarial results in an evidence package.

Simulate response on a digital twin

Problem: Operators want to know the blast radius of a response action before they touch a live vehicle or cell.
What the platform does: A digital twin replays the proposed action against the recorded state.
Human approval: Applying the action to live equipment waits for the named operator.
Evidence: Simulation notes attached to the change or incident record.

Agent roles and workflows

UAS security · RF and wireless assessment · AI adversarial testing · mission assurance · Digital Twin · CNO operations

Select the installed agents and test their models, tools, permissions, and connectors before authorizing the mission. The available catalog depends on your deployment and release.

Agent verification and testing →

Requirements in context

CMMC · DISA STIG · NIST AI RMF · NIST SP 800-82 · mission-specific controls

Set applicability for your assets, jurisdictions, and system boundaries. Connect control owners, current policies, technical tests, exceptions, and review decisions.

Explore regulatory evidence workflows →

A practical route from scope to evidence

01
Scope and connect
Define the customer profile, authorized assets, and responsible owners. UAS, counter-UAS, emergency response, and robotic fleets operating in connected or austere environments.
02
Test and investigate
Use UAS security, RF and wireless assessment, AI adversarial testing workflows with approved credentials and mission limits. Preserve source evidence and failures alongside findings.
03
Remediate and verify
Assign corrective work, obtain approvals, capture changes, and retest. Export the evidence, exceptions, and status history for business owners and assessors.

Questions for this sector

Answers you can take to a scoping call

Are UAS assessments evidence-only?+

Yes, by default. Flight, radio transmission, and actuation require a separate authorization, a safety review, and human approval.

Can perception and autonomy models be tested before use?+

Yes. Benchmarks, adversarial testing, human review, and mission traces produce a package for the program or authorizing official. The platform does not grant airworthiness or flight approval.

Does this cover public-safety drones as well as defense robotics?+

Yes. The same evidence model covers emergency-response UAS and defense or industrial robotics, with the framework set chosen for that mission.

One connected product suite

AI Firewall AI HealthCheck AI SOAR Deployment options

Related industries

Government, defense, and national security Manufacturing, robotics, and industrial operations SLED and public safety

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