Metalenz Acquires PxE Imaging to Push Color and Depth Into Edge AI

Metalenz announced on November 11, 2026 that it had acquired PxE Imaging, an Israeli startup whose Holocoder technology captures color and depth with a single camera. The purchase price was not disclosed — a gap worth noting, since both companies are private and neither released revenue or unit figures for the deal itself.

The acquisition moves Metalenz beyond near-infrared sensing into visible imaging, while reusing a supply chain the company has already built. The combined platform layers color and depth onto the material and surface data Metalenz already captures, with target markets including consumer electronics, automotive systems, drones, robotics and machine vision.

What does the Holocoder actually do?

PxE co-founder and CEO Yoav Berlatzky invented the Holocoder, a pattern baked directly onto the image sensor. The optical layer exploits the wave nature of light to encode wavelength and depth information, so color and depth land in the same image.

PxE's own technology page describes the component as a transparent, static diffractive optical element that replaces the Bayer filter inside a compact camera module and produces a holographic image. A deterministic, real-time image signal processor and decoding stack then generate RGB, infrared and depth images — channels the company says arrive pre-fused for perception AI.

The efficiency claim is the number that matters. Metalenz says conventional Bayer filters absorb 60% of incoming light, while the Holocoder sorts light without absorption and delivers 2.5 times more light to a standard image sensor. That figure comes from the acquirer, not an independent benchmark. The same layer also encodes spatial geometries aligned with the visible image, a design meant to eliminate separate depth modules and computationally expensive sensor fusion.

PxE built the stack as an alternative to multi-sensor cameras and active illumination systems, aiming to cut the cost, size and power draw of 3D sensing. If the claims hold in volume production, the implications reach camera-module economics as much as image quality.

Why does decoding in hardware matter for edge AI?

The location of the decoding is the strategic point. Metalenz says decoding the additional information directly in hardware reduces downstream computation, letting AI models run more efficiently on devices rather than depending on heavy software reconstruction.

Rob Devlin, Metalenz's co-founder and CEO, framed the deal as a bet on supplying the AI stack from the sensor up. "Owning hardware that brings new information to sensors is the real moat for differentiated AI models," he said. That is a competitive assertion, not a shipped result; the moat holds only if the technology scales.

Can Metalenz manufacture it at scale?

Metalenz spun out of Harvard University in 2016 and reports shipping more than 300 million metasurface optics in consumer devices — roughly 30 million units per year on average since founding. Its foundry-compatible optics are manufactured at semiconductor scale and integrated directly onto CMOS image sensors.

The company's PolarEyes platform captures polarization data that lets vision systems distinguish materials by their physical properties. Polar ID, the first product built on that platform, delivers payment-grade face authentication for consumer devices, extending Metalenz's sensing hardware into a finished edge product.

For the acquired team, scale was the attraction. "Joining Metalenz gives us the manufacturing platform and commercial reach to bring this technology to everyday devices," Berlatzky said. His startup gets distribution; Metalenz gets a visible-sensing layer it did not have.

The deal pairs a visible-sensing technology with a manufacturing operation already proven at high-volume consumer scale. Whether the edge AI opportunity materializes now depends on converting PxE's reported light-capture and depth gains — 2.5 times the light, no separate depth module — into commercial products across every market the two companies are targeting.