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AHOY, the deeptech infrastructure company delivering Physical AI, today announced the launch of the Perception Suite — the first sovereign deployable toolkit to unify perception, intelligence, and orchestration into a single, auditable action layer for real-world environments.
The suite consolidates AHOY’s vision, audio, and data intelligence capabilities into a single deployable stack that runs onchip, at the edge, onprem, and in fully airgapped environments, making it the only perception tooling in the world that operators, governments, and enterprises can deploy independently, on their own infrastructure, under their own sovereignty.
The announcement was made at Web Summit Rio, where AHOY participates as a Platinum Partner. It is accompanied by two additional strategic milestones: a research partnership with Mila — Quebec AI Institute (founded by Yoshua Bengio) to advance ondevice physical AI; and the establishment of Canada’s first Physical AI Lab, headquartered in Montreal, AHOY’s North American base of operations.
The Perception Suite: Architecture and Modules
The Perception Suite is AHOY’s answer to a structural gap in enterprise and sovereign AI deployment. Existing perception tooling either requires persistent cloud connectivity, produces outputs that cannot be independently audited, or arrives as fragmented point solutions that operators must assemble and maintain themselves. The Perception Suite closes all three gaps simultaneously.
The suite is composed of four integrated modules:
Vision SDK: Real-time computer vision executed at the edge and onchip, with no cloud dependency. Designed for environments where latency, data sovereignty, and continuous uptime are nonnegotiable. Audio: Multimodal audio intelligence and anomaly detection, enabling acoustic situational awareness across industrial, transport, and infrastructure environments. The Audio module now includes speech-to-speech capabilities that support Portuguese, and the overall audio stack has been adapted for Portuguese language use cases and testing workflows. Data Intelligence: Context-aware GraphRAG (GRAG) with deterministic outputs, grounding decisioning in structured, verifiable knowledge rather than probabilistic inference alone. GRAG is extended to incorporate AVML (audiovisual machine learning) signals and local geographic context so that alerts and recommendations are explicitly grounded in place-specific knowledge (e.g., site maps, local topology, regional asset registries). Orchestration: Permissioned decisioning at millisecond latency, enforcing Deterministic Permissioning across all actions the system recommends or initiates.
Photo credit: AHOY
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