Auralis is Chaac’s passive optical drone-detection offer. Available cameras and edge machine learning at portable stations support detection, tracking and geolocation across multiple observation points, with CoT/ATAK information exchange. It complements other sensors. The reviewed product page supplies no measured range, accuracy or false-alarm envelope; DND’s separate SkyMesh sandbox participation is not treated as validation of the current Auralis configuration.
Technical detail
Core features
Available cameras, edge machine learning and portable observation stations
Collaborative tracking/geolocation with CoT/ATAK output
Passive optical detection
Edge AI
CoT / ATAK
Use & integration
Recorded applications
Airspace and infrastructure awareness as a complementary sensor
These describe the reviewed application scope, not confirmed deployments, released requirements or procurement eligibility.
Evidence of maturity
Current vendor offer; no inspected source proves independent Auralis performance or identity with the SkyMesh sandbox system.
Commercial availability
Supplier demonstration and tailored configuration; hardware, deployment and acceptance terms require agreement.
Integration and verification
Readiness
A technology readiness level is not established by the reviewed public sources.
Station-level machine learning can reduce dependence on centralized image processing and supply local track information; a buyer still needs measured network, latency and disconnected-operation limits.
This is a reviewed public-source assessment. It is not procurement eligibility, endorsement, customer interest, or classified demand.
Original sources 2 linked records
These records support this capability and its published Mission area and Defence need connections. A source count is not a count of independent confirmations.
Auralis CUAS uses available cameras, local edge machine learning and observations from multiple portable mast-mounted stations to detect, classify, track and estimate positions of small uncrewed aircraft without transmitting RF detection energy.
Supports: Capability · technical tags
Auralis distributes aircraft tracks through tactical/C2 interfaces including Cursor-on-Target and ATAK; it is offered as a passive optical sensing component complementing radar, RF and acoustic sensors. No effector, detection range, accuracy benchmark or environmental rating is specified.
Supports: Capability · technical tags
Auralis CUAS uses available cameras, local edge machine learning and observations from multiple portable mast-mounted stations to detect, classify, track and estimate positions of small uncrewed aircraft without transmitting RF detection energy.
Supports: Capability · capability type
Auralis CUAS uses available cameras, local edge machine learning and observations from multiple portable mast-mounted stations to detect, classify, track and estimate positions of small uncrewed aircraft without transmitting RF detection energy.
Supports: Capability · slug
Auralis CUAS uses available cameras, local edge machine learning and observations from multiple portable mast-mounted stations to detect, classify, track and estimate positions of small uncrewed aircraft without transmitting RF detection energy.
Supports: Capability · technicaldomainslugs
Auralis CUAS uses available cameras, local edge machine learning and observations from multiple portable mast-mounted stations to detect, classify, track and estimate positions of small uncrewed aircraft without transmitting RF detection energy.
Supports: Capability · core features
Auralis CUAS uses available cameras, local edge machine learning and observations from multiple portable mast-mounted stations to detect, classify, track and estimate positions of small uncrewed aircraft without transmitting RF detection energy.
Supports: Capability · defence applications
Auralis distributes aircraft tracks through tactical/C2 interfaces including Cursor-on-Target and ATAK; it is offered as a passive optical sensing component complementing radar, RF and acoustic sensors. No effector, detection range, accuracy benchmark or environmental rating is specified.
Supports: Capability · technicaldomainslugs
Auralis CUAS uses available cameras, local edge machine learning and observations from multiple portable mast-mounted stations to detect, classify, track and estimate positions of small uncrewed aircraft without transmitting RF detection energy.
Supports: Capability · name
Auralis CUAS uses available cameras, local edge machine learning and observations from multiple portable mast-mounted stations to detect, classify, track and estimate positions of small uncrewed aircraft without transmitting RF detection energy.
Supports: Capability · commercial availability
Auralis is offered through demonstration and tailored supplier engagement for defence, infrastructure, transport, correctional and temporary-site airspace awareness. Named buyers and accepted deployments are not identified on the product page.
Supports: Capability · summary
Auralis CUAS uses available cameras, local edge machine learning and observations from multiple portable mast-mounted stations to detect, classify, track and estimate positions of small uncrewed aircraft without transmitting RF detection energy.
Supports: Capability · core features
Auralis distributes aircraft tracks through tactical/C2 interfaces including Cursor-on-Target and ATAK; it is offered as a passive optical sensing component complementing radar, RF and acoustic sensors. No effector, detection range, accuracy benchmark or environmental rating is specified.
Supports: Capability · technical tags
Auralis CUAS uses available cameras, local edge machine learning and observations from multiple portable mast-mounted stations to detect, classify, track and estimate positions of small uncrewed aircraft without transmitting RF detection energy.
Supports: Capability · maturity
Auralis is offered through demonstration and tailored supplier engagement for defence, infrastructure, transport, correctional and temporary-site airspace awareness. Named buyers and accepted deployments are not identified on the product page.
Supports: Capability · summary
Auralis distributes aircraft tracks through tactical/C2 interfaces including Cursor-on-Target and ATAK; it is offered as a passive optical sensing component complementing radar, RF and acoustic sensors. No effector, detection range, accuracy benchmark or environmental rating is specified.
Supports: Mission area · Edge Data Processing
Auralis CUAS uses available cameras, local edge machine learning and observations from multiple portable mast-mounted stations to detect, classify, track and estimate positions of small uncrewed aircraft without transmitting RF detection energy.
Supports: Mission area · Edge Data Processing
Auralis CUAS uses available cameras, local edge machine learning and observations from multiple portable mast-mounted stations to detect, classify, track and estimate positions of small uncrewed aircraft without transmitting RF detection energy.
Supports: Mission area · Edge Data Processing
Auralis CUAS uses available cameras, local edge machine learning and observations from multiple portable mast-mounted stations to detect, classify, track and estimate positions of small uncrewed aircraft without transmitting RF detection energy.
Supports: Mission area · Edge Data Processing
Auralis CUAS uses available cameras, local edge machine learning and observations from multiple portable mast-mounted stations to detect, classify, track and estimate positions of small uncrewed aircraft without transmitting RF detection energy.
DND calls the sandbox system SkyMesh; the current Chaac page calls its optical product Auralis. No inspected source establishes a rename, identical configuration or transfer of the SkyMesh demonstration to Auralis.
Supports: Capability · maturity
DND calls the sandbox system SkyMesh; the current Chaac page calls its optical product Auralis. No inspected source establishes a rename, identical configuration or transfer of the SkyMesh demonstration to Auralis.
Public sources cited · Facts and assessments kept separate · Human review
