THE MENU
A bestseller.
Or a reason to return?
Compare order volume with observed repeat visits and same-dish reorders. Put your next menu review on firmer ground.
Explore menu patterns A CLEARER PICTURE OF YOUR RESTAURANT
Know what sells.
See who returns.
Your restaurant has a story in every service. Connect your menu, regulars and revenue to see the patterns worth acting on.
Local-first Your data Clearer decisions
THE BIGGER PICTURE
B
A regular. And a full table.9 visits · 13 invited guest covers
FRMenu intelligenceDEMO
LOOK BEYOND THE BEST SELLER
Worth coming back for.
Observed return within 30 daysReturn rate
More than a sales ranking.
Every plate has a bigger story.
Illustrative sample data · Not restaurant results
BUILT FOR THE PLACES WE CALL LOCALSan Luis Obispo | Paso Robles | Central Coast
01 / SEE THE WHOLE STORY
A busy dining room.
A lot of unanswered questions.
Your POS tells you what sold. Frame connects the next chapters: who came back, what they ordered next, and the company they brought.
A bestseller.
THE REGULARS
One familiar face.
A much bigger table.
For enrolled guests, connect visit history, preferences and confirmed invitations. Understand a regular's wider contribution.
Meet the guest viewTHE TIMING
Same restaurant.
A different rhythm.
Explore meal periods, weekdays and party sizes. Find out how the patterns change from a quiet lunch to a full Friday night.
Find the rhythmLESS GUESSWORK. MORE CONTEXT.
Your restaurant,
with the dots connected.
Menus, regulars, revenue and recorded service timing.
One place to see how the pieces fit.
FRAME RESTAURANT INTELLIGENCE Local-first
Actual application interface · Synthetic demonstration dataTry the interactive sample
Menu & revenue Enrolled guest history Consented seating Food observation review
02 / FROM SERVICE TO INSIGHT
Start with what you know.
Build from there.
No mystery numbers. Sales records, guest check-ins and reviewed observations each have a clear role.
Bring your records.
Start with your menu and sales exports. Connect guest histories through affirmative enrollment and check-ins.
YOUR MENU + YOUR SALESAdd another perspective.
Optional food-only camera regions suggest dishes. Your team reviews the suggestions; unclear matches stay unknown.
LOCAL VISION + HUMAN REVIEWMake your next move.
Explore return patterns, guest value and timing. Use the evidence to guide menu conversations, specials and service reviews.
PATTERNS + BETTER QUESTIONSGrounded in records, not assumptions. Prices and payments come from sales records. A dish's return pattern is an association—not proof that it caused a guest to come back.
THOUGHTFUL BY DESIGN
Your hospitality.
Your data. Your call.
Useful intelligence should fit your restaurant—not turn it into a black box.
Explore a focused pilotLocal-first, not cloud-dependent.
Run the analytics application on your hardware. Keep your private restaurant data separate from this public sample site.
Guest profiles by check-in.
Named seating uses affirmative check-ins, not face recognition or appearance dossiers.
Evidence you can question.
Review sample sizes, pending return windows and dish suggestions. Export your records and control access and retention.
A FEW GOOD QUESTIONS
Before we get started.
Do I need a camera to get started?
No. Start with menu and sales records, enrolled guest histories, and confirmed invitations. Camera-assisted food observations are an optional workflow, configured and evaluated against your menu and camera placement.
Will this work with my point-of-sale system?
The product supports documented sales imports and a generic integration contract. A connector for every POS brand is not bundled. We review your export format, table and seat identifiers, payment records and integration options before proposing a pilot.
How do you know a customer has returned?
Linked, enrolled guest records identify repeat visits on later dates. Named seating uses an affirmative check-in, not automatic face recognition. People who are not enrolled remain unlinked in customer analysis.
Can a dish really be credited with bringing someone back?
The dashboard shows observed associations, not proof of cause. It separates incomplete follow-up from completed return windows and displays sample sizes. A return can reflect service, convenience, price or many other factors.
What can the camera actually tell me?
A local classifier suggests dishes from configured food-only plate regions using your menu's reference images. Staff confirm, correct or reject the suggestions; uncertain matches stay unknown. Prices and payments come from sales records, not guesses made from video.
Where does the restaurant data live?
The analytics application is local-first and can run on your hardware. It includes staff access controls, exports and retention settings. The public website demo uses synthetic data and is separate from any private restaurant installation. Storage and backups must be protected as part of deployment.
YOUR NEXT GOOD DECISION STARTS HERE
Let's talk about
your restaurant.
Bring your menu, a sample sales export and the questions that keep coming up. We'll start with a demonstration and a conversation about fit.
San Luis Obispo | Paso Robles | Central CoastA clearer picture starts with a hello.
Tell us a little. We'll take it from there.