SpectralSense delivers calibrated spectral data APIs, embedded SDKs, and real-time material intelligence — built for developers and researchers who build with light.
SpectralSense exposes ColorSense's hardware and perceptual compute stack through clean APIs. Plug calibrated light sensing into your product, pipeline, or research workflow without building the physics from scratch.
Every result includes dominant color, luminance, fiber indicators, NIR reflectance, and confidence — structured data your systems can act on immediately.
POST a scan trigger, get back a structured result with color name, hex, luminance, NIR reflectance, and fiber classification — all in one round trip. No raw ADC wrangling. No signal processing. Just data.
WebSocket streaming available for live ambient monitoring, color hold detection, and continuous scan loops.
Any workflow where material identity, color accuracy, or surface properties need to be known — without human judgment in the loop.
Verify dye lot consistency, detect off-color garments, and flag fiber anomalies on the production line — automatically, at speed.
Power the next generation of assistive color tools. SpectralSense is the sensor stack behind CUE — the voice-guided color assistant for low-vision users.
Automate inventory color tagging, match customer items to catalog SKUs, and reduce return rates from color mismatch.
Integrate calibrated spectral measurements into research pipelines. Reproducible, timestamped, structured — no custom hardware drivers required.
Add material-aware sensing to robotic pick-and-place, agricultural sorting, or autonomous inspection systems where RGB cameras fall short.
Continuously monitor ambient light, surface conditions, and material states in smart building, retail, or industrial IoT deployments.
SpectralSense is one layer of the ColorSense perceptual computing stack — infrastructure for machines that need to understand the physical world through light, sound, and touch.
SpectralSense is in private developer preview. Tell us what you're building.