Model downloads

Models, built for the edge.

Visual positioning for GNSS-denied navigation, packaged to run on the hardware a real vehicle carries. Every release ships as one versioned, checksummed bundle: the training checkpoint, exports for CPU runtimes, a compiled build for the Hailo-8 accelerator, and the evidence that the deployed model behaves like the one we evaluated.

Visual positioning for GNSS-denied navigation
Runs on Hailo-8 NPU, ARM, and x86
INT8-vs-fp32 evidence in every release
Versioned, checksummed, documented

What ships in every release.

One directory per release: the training checkpoint (PyTorch), ONNX exports for CPU inference on ARM and x86, a compiled Hailo-8 binary for the NPU, a model card describing intended use and limits, and machine-readable verification reports — with a SHA-256 checksum for every file.

Deployment parity is measured, not assumed: each exported build is verified against the reference implementation on real flight imagery, and the report ships in the bundle.
Quantised builds come with the accuracy evidence: the INT8-vs-fp32 comparison is published per release, so you can see the cost of the speed-up before you deploy it.
Full provenance per release: a semantic version, the exact source checkpoint, per-file checksums, and a model card covering evaluation scope and known limits.

Current release.

Visual navigation model

Our production visual-positioning model for when satellite navigation is jammed, spoofed, or unavailable. It fixes position by referencing live camera frames against imagery of the operating area, on the vehicle, offline.

Version: semantic version, assigned on release
Formats: PyTorch checkpoint (.pt) · ONNX · Hailo-8 HEF
Target hardware: Hailo-8 NPU · ARM64 · x86-64 CPU
Model card: included in the bundle, and available on request before purchase.

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Aerial object detection

Finds vehicles from an aerial platform and puts the cue on them, on the vehicle or in the cloud. Built for degraded footage — compression, interference, cheap optics — rather than clean stock imagery.

Sizes: a small model for edge hardware, a larger one for workstation and server
Formats: PyTorch checkpoint (.pt) · ONNX · Hailo-8 HEF
Target hardware: Hailo-8 NPU · ARM64 · x86-64 CPU · hosted API
Model card: included in the bundle, covering the conditions it is valid in and the ones it is not

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Evaluate it

Request an evaluation build.

Tell us your platform, runtime, and operating area, and we'll deliver the appropriate release as a time-limited download link — no account needed. Builds tuned to your camera, altitude band, and terrain are available under contract.

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