Edge AI, Embedded and Evolving

Reliova is building practical, embedded AI solutions that run directly on real devices—close to data, with no cloud required.
We focus on optimizing lightweight AI models for resource-constrained platforms with rich I/O, local databases, and sensor integration.
Our current work includes early-stage demos, hardware-aware model tuning, and exploring industrial use cases where embedded intelligence makes a difference.

Partner with us on edge AI pilots

Edge AI software stack integrating real-world industrial systems with local sensor data and intelligent processing, without cloud dependency" 💬 Caption (optional): "Local-first Edge AI: Where embedded intelligence meets real-world operations" 📝 Description: This image visualizes Reliova’s embedded AI software stack in action — featuring real-time data processing, local sensor integration, and optimized model execution across field devices, robotics, and factory floors. It highlights the company’s practical, no-cloud-needed approach to intelligent edge computing in industrial applications. Edge AI software stack integrating real-world industrial systems with local sensor data and intelligent processing, without cloud dependency

What’s in Our Embedded AI Stack

01.

Model Conversion & Optimization

▪ INT8 / INT4 quantization for edge inference
▪ GGUF, ONNX, RKNN model conversions
▪ Aligned to target platforms like Rockchip RK3588, Snapdragon, and industrial PCs

We focus on adapting models to run efficiently on constrained hardware, including vision, audio, and control workloads.

02.

Edge Deployment with Sensor I/O

▪ Access real-time inputs from cameras, microphones, GPIO, USB, RS485, and more
▪ Run models locally in tight feedback loops — no cloud dependency
▪ Designed for factory floors, kiosks, robotics, and field devices

We’re exploring high-value use cases where sensor data drives real-time AI decisions. kiosks, robots

03.

Local Data + Feedback Loop

▪ Store outputs using SQLite or DuckDB — lightweight, fast, and local
▪ Use real-world data to fine-tune models or update edge behavior
▪ Enable simple RAG-like context loops without cloud or backend infrastructure

This lets us close the loop between data, inference, and local context — even in offline environments.

Designed for Real-World Edge Intelligence

01.

Smart Kiosks

▪ Voice + vision assistants powered by compact LLMs
▪ Runs offline with local logic and data storage

02.

Industrial Monitoring & Inspection

▪ Real-time camera + sensor integration with optimized CV models
▪ Logs events, triggers alerts, or enables basic automation

03.

Field Assistants or Tools

▪ Wearable or mobile devices running lightweight LLMs
▪ Local memory, data logging, and offline reasoning for guidance tasks

Why Choose Reliova’s Embedded AI Stack?

▪ Full stack focus: hardware + runtime + model + local data
▪ Designed for sensor-rich, edge-deployed boards
▪ Tuned for low power, real-time response
▪ Adaptive AI through local feedback loops
▪ Developer-friendly SDKs and engineering insights
▪ No cloud required — built for offline intelligence

Let’s Build Embedded AI That Works Offline

Whether you’re experimenting with Deepseek on a kiosk or adapting a vision model for ARM-based boards, Reliova is building embedded AI stacks that are practical, flexible, and ready for real-world prototyping.

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