sparkRequest a pilot

Make restaurants think in real time.

Spark turns cameras, POS, sensors, and store activity into a live decision layer for restaurants and physical stores.

Today

See where service breaks down.

Next

Dispatch the right action to the right person in real time.

Tomorrow

Route the same decisions to robots.

Live floor
3 events

Table 7 has waited 4 min without service

Ping Server A
Maria · ServerDispatched · 12s ago

Entrance queue increased to 12 customers

Move Host B to front
Jordan · HostPending · 45s ago

Zone C under-covered for 8 min

Redeploy Server D
Alex · ManagerAcknowledged · 1m ago

The problem

Online businesses optimize every second. Restaurants still run on intuition.

E-commerce teams know when customers drop off, which experiments work, and where revenue is leaking.

Restaurants have cameras, POS systems, and staff schedules, but these systems do not think together. Managers still walk the floor manually, review reports after the shift, and miss problems while they are happening.

Spark brings the e-commerce decision loop into the physical world.

The product

A real-time operating layer for the store floor.

Spark connects the signals already inside your store and turns them into operational decisions.

Catch service breakdowns

Detect unattended tables, long dwell times, queue spikes, and under-covered zones.

Find revenue leaks

See which time slots, staff patterns, and service moments hurt conversion or customer experience.

Route the next action

Send the right task to the right server, manager, or future robot while the issue is still happening.

Starting with restaurants

Built for physical operations.

Restaurants are the first vertical because every shift is full of high-frequency decisions.

A customer waits too long.

A queue forms at the entrance.

Staff cluster in the wrong zone.

A refund request needs approval.

A regular customer walks in.

These are not dashboard problems. They are real-time routing problems.

Live now

Live in 32 chain restaurant locations.

Spark is deployed across 32 Bahe Li Chaoshan Beef Hotpot locations in China.

Operators use Spark to analyze real restaurant floor data across shifts, service moments, and store performance.

The next product layer turns that analysis into real-time action.

Vision

The spatial brain for physical stores and robots.

Physical stores are becoming AI-native. First, software helps managers understand what is happening. Then it routes work to staff in real time. Eventually, the same decision layer can route work to robots.

The worker changes. The brain stays the same.

Bring real-time decisions to your stores.

We are taking pilot conversations with regional and mid-market restaurant chains running 10 to 50 locations.