Two engines. Zero latency trade-offs.
Edge AI detects threats in 47ms. Cloud VLM comprehends everything else. Neither waits for the other.
47ms
Edge
360°
Audio
380ms
Cloud
On-device. On-time. Every time.
The edge model runs entirely on-device. No server round-trip. No connectivity dependency. Threats detected before your next heartbeat.
47ms
Edge-to-audio latency
12MB
Quantized, optimized
180mW
All-day operation
Comprehension without compromise.
The cloud model sees what cameras capture and understands what it means. Faces, text, context, relationships.
Scene Narration
Describes environments in natural language. 'Busy café, 12 people, exit on your left.'
Face Recognition
Identifies known contacts. Announces them spatially before they speak.
Text & Sign Reading
Every sign, menu, label — read aloud from the direction it exists.
"Outdoor café terrace. Four empty tables. Friend Marcus seated at far table, waving. Menu board reads: Today's special — mushroom risotto, £12."
Measured. Reproducible. Real.
Latency Comparison (ms)
47ms p50
Camera-to-audio, on-device
380ms p50
Full scene comprehension
94.2% mAP
COCO benchmark, quantized
±15°
Sound placement precision
<8%
12-hour continuous operation
OTA, <30s
No user intervention
Ship spatial intelligence in 50 lines.
The Vajview SDK handles detection, classification, and audio rendering. You focus on the experience.
TypeScript · React Native · Swift · Kotlin
import { Vajview, Priority } from '@vajview/sdk'
const vj = Vajview.create({
edge: { model: 'detect-v3', maxLatency: 50 },
cloud: { model: 'vlm-v2', mode: 'navigation' },
audio: { renderer: 'binaural-hrtf' }
})
vj.onDetection((event) => {
if (event.priority === Priority.CRITICAL) {
// Edge-processed: 47ms to spatial audio
vj.audio.alert(event.bearing, event.distance)
}
})
vj.start()Built for builders.
Whether you're integrating Vajview into hardware or building on our API — the architecture is ready.