Working on real camera events Patent pending

Heliarch: your restaurant, live, on your coffee table.

Sit in your living room, pull up any store you run, and set a table-size 3-D model of it in front of you. Every person in the building appears as a faceless avatar in the area where they are, live. Every station shows green, yellow, or red. Rewind the last 7 days. Ask why something went wrong, and get the answer from what actually happened.

A table-size 3-D restaurant model floating beside a bookshelf in a living room, seen through Apple Vision Pro
Apple Vision Pro simulator. Native app in development; demo store with simulated activity.
Why it exists

A district manager can't stand in twelve kitchens at once, and twelve grids of camera feeds don't tell you much either. Heliarch turns those feeds into one thing you can read in a glance: the store itself, alive, from above.

How it works

From a ceiling camera to a figure on your table, in seconds.

The heavy lifting happens on a QSR Vision box inside the store. What leaves the store is a stream of anonymous events, not video.

  1. 1 · Cameras

    What's already there

    The store's existing security cameras are the input. No special hardware on the people.

    In the store
  2. 2 · Vision box

    People become dots

    On-site AI finds each person and places them on the floor plan. Roles come from the station they're working, not from who they are.

    In the store
  3. 3 · Events

    Anonymous, timestamped

    Positions, queues, waits, and station timing, with anonymous IDs (on pilot boxes they change at least every 5 minutes). No faces, no names, no video.

    Leaves the store
  4. 4 · Store state

    One record of truth

    Each zone is scored against your targets. The same record feeds the live view, the replay, and every answer.

    Secure cloud
  5. 5 · Your device

    The 3-D store

    Your headset or browser draws the store and its avatars. It never receives camera video.

    Wherever you are
What you see

The whole restaurant, inside and out.

Dining room, front counter, kitchen stations, drive-thru lane, and the lot, all as one model. Zoom from the whole building down to a single station.

In motion

Walk around the store.

Demo · simulated
Crew walk-around. The whole store from above while the lunch crew works. Demo store, simulated activity.
Demo · simulated
Kitchen close-up. Fry and grill on target; status cards float over each station. Simulated.
Demo · simulated
Drive-thru line. Cars in the lane, menu board, and window as one model. Simulated.
Demo · simulated
Exterior orbit. The lot, the lane, and the building, so you know where you are. Simulated.
Demo · simulated3-D front counter with faceless guest avatars in line and the front line status card
Front counter. Guests in line; front line on target. Simulated.
Demo · simulated3-D dining room with guest avatars at tables and booths
Dining room. Guests seated at tables and booths. Simulated.
Demo · simulated3-D drive-thru canopy and pickup window with a car at the window
Drive-thru window. Under the canopy at the pickup window. Simulated.
Demo · simulatedCompany view of 250 demo stores grouped by region, worst first
250 stores, worst first. Company to region to district to store. Demo data.
Demo · simulated3-D store with a heat map of historical bottlenecks across the floor
Heat map. Where the store has bottlenecked over time. Simulated.
Vision Pro simulatorApple Vision Pro simulator: the 3-D restaurant on a stand in a living room next to a glass control panel
Vision Pro premium look. Simulator, in development; demo data.

Unless marked otherwise, media in this section is the demo store with simulated activity in a desktop browser, October 7–8, 2026. Today's look is stylized; photo-real models built from scans of each actual store are next on the roadmap.

Real bench data
Real events from our test kitchen's cameras, Oct 7, 2026: 27 minutes sped up about 23×.
Proof, not a mock-up

Real waits turned the pickup zone red, then yellow, then red again.

On October 8, 2026 we ran the whole chain on real events from our camera test bench: cameras → Vision box → cloud → 3-D model. When a real customer waited too long at pickup, the zone turned red on screen in about 2.3 seconds (median, end to end).

The live store-status service that every 3-D view reads from went into production the same day.

Real bench data3-D store from real events: pickup zone critical with a 2:41 average wait, front line normal
Pickup at 2:41 average wait against target: critical. Front line: normal.
Real bench data3-D store beside a zone check report comparing the twin zones with the Vision box zones on the test bench
Zone check. The 3-D model’s zones checked against what the test-bench Vision box reports, so nothing shows green by mistake.
Real bench data3-D store from real events: pickup zone on watch at a 1:50 average wait, with people at pickup
Pickup on watch. Real waits easing from red to yellow (1:50 average).
Real bench data3-D store fed by the production store-status service, all zones within target
Production, Oct 8. The live store-status service feeding the 3-D store, on a quiet evening at the test bench.
7-day replay · ask why

Rewind the week. Find the moment. Know the cause.

Demo · simulatedReplay mode: a red line connects the overloaded sandwich station to the backed-up drive-thru; a 7-day timeline lists the day's red moments
Cause → effect. The line runs from where the problem started to where customers felt it. Demo store, simulated activity.
  • Seven days, zone by zone. Replay any part of the last week, zone by zone (people replay coming soon). The raw anonymous position data behind it is kept up to 30 days, then deleted automatically.
  • Day, hour, or 15-minute zoom, played at 1× to 60× speed.
  • “Worst moment” jumps straight to the reddest minute of the day.
  • Ask “why is this red?” by voice or tap. An AI assistant answers with what happened, since when, the likely upstream cause, and the order volume, all from the same events you can watch.
  • District view. All your stores at once, worst first. Step into any one of them.
“Why is the drive-thru lane red?”
What
8 cars against a 5-car target; 4:19 average against 3:00.
Since
12:09 PM, when the queue reached 6.
Likely cause
Sandwich assembly: 1:33 average build vs. 55 s target, 20 orders in a row over.
Volume
Orders up about 34% at noon.

Example from the lunch-rush demo scenario (simulated data).

Devices

One store model. Every screen you'd want it on.

Headset emulator · demo
Meta Quest 3S view (headset emulator capture): replaying cause → effect on the tabletop store.
Working today

Meta Quest 3S

Runs in the headset's web browser, nothing to install. Color passthrough puts the store on your real table; point and pinch with your hands.

In development

Apple Vision Pro

A native app with the premium look: the store on your table or floating in the room, the 7-day replay with people, and the district view.

Built · in testing

Ray-Ban Meta glasses

Voice-first and hands-free. Built on Meta's wearables toolkit and in internal testing.

Planned

Meta's display glasses & desktop

Meta's display glasses are a target platform. And no headset is required at all: the same experience runs in a regular desktop browser today.

Vision Pro simulatorRestaurant model resting on a stand in a living room, seen through Apple Vision Pro
Vision Pro, tabletop mode (simulator, demo data).
Vision Pro simulatorVision Pro 7-day replay: the restaurant model on a stand with a day picker and timeline panel beside it
Vision Pro, 7-day replay with people (simulator, demo data).
Headset emulator · demo
Meta Quest 3S tabletop (headset emulator capture). The demo store on your table, live.
Vision Pro simulator
Vision Pro: premium look and 7-day replay (simulator stills, in development; demo data).

Meta Quest, Ray-Ban Meta, and Apple Vision Pro are trademarks of their owners. QSR Inspector is not affiliated with or endorsed by Meta or Apple.

Our privacy promise

You see the floor, not the people.

Privacy isn't a setting we added later. It's how the system is built, and it's the first thing the app shows you.

No faces. No face recognition.

Everyone is a generic avatar, and nothing in the system tries to identify who a person is.

Roles, never names

An avatar is “grill” or “front counter” because of where they're working, never a name or employee ID.

Anonymous IDs that change (pilot boxes)

On pilot boxes (the release we're testing now, coming with the pilot), a person's anonymous ID changes at least every 5 minutes and whenever tracking is lost, so a figure can't be followed into a profile over days.

No video in the 3-D view

The headset or browser receives positions and events only, and never asks for your headset's cameras.

A 30-day limit

Raw anonymous position data is kept up to 30 days, then deleted automatically. Replay shows the last 7 days. Stores can also run in “heat only” mode with no figures at all.

Walter looks only when asked

Walter only looks at a picture when you ask him to: one photo or screenshot at a time, never video or audio, and nothing is kept running.

Vision Pro simulatorVision Pro first-run screen titled Our privacy promise: roles only, never names or employee IDs; people are generic avatars with no faces; this app never receives camera video; it never asks for your headset's cameras
The first screen you see on Vision Pro (simulator).
What's real today

Exactly where each piece stands.

As of October 8, 2026.

Working

Live 3-D store from real camera events

Proven end to end on our camera test bench; store-status service in production.

Working

Avatars, zones, 7-day replay, district view

Desktop browser and Meta Quest 3S; Vision Pro build in development.

Working

“Why is this red?”

Answers built from the store's events, working in the demo; connecting to live stores during the pilot.

Prototyped

Photo-real store from a phone scan

The scan-based look is prototyped; real store scans start with the pilot.

Next

Real restaurants

A first multi-store pilot with a multi-unit franchise operator is being planned.

Planned

Display glasses

Lighter, everyday glasses as those platforms reach the market.

Questions

Straight answers

Do I need a headset?

No. The same 3-D store, replay, and answers run in a regular desktop browser. A headset makes it feel like the store is on your table.

Does it need new cameras?

It starts with the cameras a store already has, through a QSR Vision box. More camera coverage means more of the floor shows up in 3-D; areas no camera can see show grey, never a fake “green”.

Can I see who someone is?

No. Everyone is a faceless, generic avatar labeled by role. There's no face recognition and no names or employee IDs in the 3-D view.

Does video go to the headset or the cloud?

The 3-D view never receives video, only anonymous positions and events produced by the Vision box in the store.

How realistic does it look?

Today it's a clean, stylized model with real store layouts. Photo-real models built from phone scans of each actual store are next on the roadmap.

Can I buy it today?

Heliarch is in pilot and not sold separately yet. QSR Vision is available now; see pricing. If you run multiple stores and want to be part of a pilot, talk to us.

Is it patented?

Patent pending: two U.S. provisional patent applications were filed in October 2026.

Want your stores on the table?

We're lining up pilot operators now. Tell us how many stores you run and what you'd want to see first.