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Practical technology for real field conditions.

We do not over-engineer. We choose technologies that work reliably in remote field environments, can be maintained by non-specialist teams, and improve over time as data accumulates.

Hardware layer.

Physical components designed for durability, low power, and remote deployment.

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HG-Standard-v1 Hive

Langstroth-compatible hive body. Hardwood construction. Sensor mounting point built into the base board. Designed for standardized stacking and transport.

In deployment
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Sensor Node (HG-SN-v1)

Low-power internal sensor. Measures temperature (±0.1°C), relative humidity (±2%), tamper (reed switch), and tilt (accelerometer). Solar-charged LiPo cell. Reports every 15 minutes.

In deploymentFirmware v1.2.1
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Site Gateway (HG-GW-v1)

LoRa receiver aggregating up to 100 sensor nodes. Cellular primary backhaul (4G). Starlink failover port. Solar-powered. Designed for outdoor mounting on site perimeter.

3 deployed

Software layer.

The platform stack, built for operations at scale.

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Cloud data pipeline

Gateway data arrives via cellular/satellite. Parsed, validated, and stored in time-series format. Anomaly rules applied in real-time. Alerts routed to the operations platform.

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Operations dashboard

Web-based multi-role platform. Operator and admin views. Mobile-responsive for field use. Works on 3G connections. No specialist hardware required.

→ Try the demo
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Traceability module

Full chain-of-custody from site to product lot. QR code generation for end-to-end traceability. Export-grade documentation built from operating data.

→ View traceability

Intelligence layer.

AI that is honest about what it can and cannot do at this stage of the dataset.

CapabilityPhaseStatusNotes
Threshold-based anomaly detectionPhase 1✅ ActiveRules-based, tunable thresholds
Device silence detectionPhase 1✅ ActiveConfigurable silence window
Tamper event groupingPhase 1✅ ActiveTime-window based grouping
Multi-sensor anomaly scoringPhase 2◷ In developmentRequires larger dataset
Predictive maintenance hintsPhase 2◷ In developmentPattern recognition in progress
Colony behavior modelsPhase 3○ PlannedRequires validated dataset
Disease risk scoringPhase 3○ PlannedAcademic collaboration required

We do not overclaim AI capability. Phase 1 is rules-based and works. Phase 2 and 3 require more data and more validation. We will be specific about what each model can and cannot do.

View AI intelligence panel