Built for operators who run on margins
We believe restaurant teams deserve the same closed-loop optimization tools that e-commerce and retail have had for years — without the jargon or the hype.
Our story
MenuMargin Optimizer was born from a simple frustration: restaurant operators make hundreds of pricing and assortment decisions every month, but most rely on gut feel, outdated spreadsheets, or revenue-only dashboards that ignore ingredient costs entirely.
We saw teams spending hours reconciling supplier invoices against POS reports, only to end up with stale numbers and no clear next step. Meanwhile, food cost volatility kept rising, delivery commissions ate into margins, and multi-location chains struggled to keep menus consistent across channels.
We built MenuMargin Optimizer to close that loop: ingest real cost and sales data, compute item-level contribution margin, rank the highest-impact actions, deploy changes to POS and delivery channels, and then measure whether the change actually worked — with controlled experiments, not assumptions.
The result is a proof-first workflow that turns messy menu and cost data into clear, deployable actions with transparent reasoning and measured results.
Our mission
Help every restaurant operator make faster, evidence-based menu and pricing decisions that raise contribution margin and reduce waste — with transparent reasoning, measured outcomes, and respect for operational reality.
What we stand for
Four attributes that shape every feature we build and every word we write.
We focus on actions that fit real restaurant operations — not theory. Every recommendation comes with estimated impact and operational feasibility, not just data.
Evidence-led, transparent about inputs, assumptions, and confidence. We show the drivers behind every recommendation and never hide uncertainty in footnotes.
We help you choose and ship changes with minimal friction. Tight flows from review to approve to deploy to monitor — fewer dashboards, more outcomes.
Plainspoken, realistic, and calibrated to the uncertainty of restaurant data. We say 'estimate' when we mean it and acknowledge constraints upfront.
Our design principles
- 1Lead with the decision, then show the math
- 2Make uncertainty explicit and usable
- 3One flow from insight to rollout
- 4Optimize for weekly cadence
- 5Respect the floor — acknowledge operational constraints
Ready to work with a team that respects operator reality?
We built this for people who make menu decisions under real constraints. Connect your data and see what evidence-based optimization looks like.