Vercila Engine · SDK for evaluation

Real-time, on-device de-aging — as an engine you can embed.

Vercila is the neural core behind FaceReady: it eases the signs of age on a live face, frame by frame, entirely on the user's own device — on Windows and macOS. We license it as an embeddable SDK, with a native C-ABI and no cloud step in the pipeline.

Native C-ABINativeAOT · no JITWindows + macOSReal-time 1280×720No cloud inference
01

One job, done convincingly

Most face-effects SDKs are built for mobile AR decoration — masks, makeup try-on, novelty filters. Vercila is built for a narrower, harder job: making a real person look rested and naturally younger on a live feed, without turning them into someone else.

Specialised, not general

Purpose-built for live de-aging — an open lane the broad AR-filter SDKs don't lead on.

Desktop-first

Ships on Windows and macOS today, where the mobile-led competitors are weakest or absent.

On-device by design

Inference runs locally. There's no cloud processing step anywhere in the pipeline.

Identity-preserving

A residual approach keeps the subject's real skin and features — none of the plastic look of full-face regeneration.

Embeddable

A native C-ABI drops the engine into a host app or a virtual-camera pipeline, with no managed-runtime dependency.

The same core as FaceReady

Vercila already ships in a paid consumer product. The SDK is that proven engine, not a lab demo.

02

A correction, not a replacement

Vercila takes a video frame containing a face and returns the same frame with the signs of age eased back — under-eye shadow, the lines a lens over-sharpens, the flatness that reads as tired — while leaving features, expression and real skin texture intact. It computes a small correction and applies only that, so the result tracks motion exactly, because it is the original frame minus the camera's harshness.

Input
Live frame · RGB / NV12
On device
Vercila engine
Output
Corrected frame

De-age is the lead capability. The same engine exposes relight and warmth as independent parameters — use de-age alone, or combine them in one pass over the frame.

03

At a glance

Platforms
Windows (x64) · macOS (Apple Silicon)
Execution
On-device — the processor's neural engine
Integration
Native C-ABI — init / process / release
Runtime model
NativeAOT — no JIT, no managed runtime
Throughput
Real-time at standard call resolution (1280×720)
Pipeline output
RGB and NV12 frame formats
Capabilities
De-age (lead) · relight · warmth
Data handling
No cloud step — frames never leave the device
Why on-device is the point, not a feature

Run it locally, and an entire class of compliance risk simply isn't there.

Because inference runs on the user's machine, there's no server in the loop: nothing is uploaded, nothing is transmitted, nothing is retained. For any vendor shipping a face-processing capability into regulated, enterprise or privacy-sensitive environments, that removes a whole category of data-handling and compliance exposure. Even the broad face-AR leaders run their core engines on-device; "cloud," where it shows up in this market, is effect delivery, not processing. Vercila has no cloud-inference path by design.

Run it against your own footage.

Get the technical overview, or start an evaluation — an engine build for Windows and macOS, C-ABI integration docs, and a direct technical contact.