We design custom hardware, embedded software and AI systems for real-world applications—built local-first, with privacy, cost and long-term control considered from the beginning.
We combine electronics, embedded software, networking, local AI and cloud services into systems designed around one specific application, environment and privacy requirement.
Application-specific devices and complete systems, from PCB and firmware to gateway, backend and user interface.
Privacy is an architectural input, not a feature added after implementation. Sensitive data stays local whenever possible.
Run inference on-device or on-premise whenever practical, and use cloud AI selectively where it adds real value.
Adapt open models for a defined workflow, vocabulary, tool set or application instead of relying on a generic assistant.
Representative product directions rather than rigid packages. Each implementation can be adapted to your hardware, deployment environment, privacy level and budget.
Recorders, voice interfaces, offline speech systems, event-triggered audio capture and private transcription.
Private cameras, local detection, low-latency streaming, event recording and optional cloud relay only when required.
Doors, presence, alarms, secure wireless links, local decision logic and privacy-conscious remote notification.
Soil sensing, irrigation control, weather-aware watering, low-power wireless nodes and simple local dashboards.
BLE, motion sensing, local gateways and alert logic for assets that should stay within a defined environment.
GNSS-enabled tracking, low-power reporting, movement-aware sampling and hybrid local/cloud data paths.
Custom sensing, connectivity, control and intelligence for applications that do not fit an off-the-shelf product. We can take responsibility for the complete system instead of only one layer.
The design principle: keep sensitive data and routine inference local; use external AI only for tasks where the additional capability justifies the privacy and recurring-cost tradeoff.
A smaller well-adapted model can be more useful, more predictable and much cheaper to run than a large generic model.
We can prepare datasets, fine-tune open LLMs and optimize them around application-specific commands, terminology, workflows and structured outputs.
user:
"Start watering zone 3 for 8 minutes."
model:
{
"intent": "START_IRRIGATION",
"zone": 3,
"duration_min": 8
}
execution:
✓ schema validated
✓ policy checked
✓ local controller invoked
✓ no cloud request requiredWe turn product goals into measurable engineering requirements before choosing technology.
We prove power, RF, latency, model performance or architecture early—before polishing the easy parts.
Hardware, firmware, application and infrastructure evolve together instead of becoming isolated workstreams.
Logging, recovery, updates, test points and maintainability are designed in rather than added afterwards.
ViaCat Technology develops custom connected and intelligent systems across electronics, embedded software, Linux, networking and local AI.
Our strongest fit is a project where privacy matters, off-the-shelf products are not enough, or hardware and AI need to be designed as one system.
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What the system should do, where it will run, expected volume, power/connectivity limits and any privacy requirements.
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