For chains running 5–200 locations
Most analytics tools tell you what already happened. Insights tells your operators what to do next — and routes any employee-affecting action through human approval before it ships.
For chains past the point where built-in POS reports stop being enough — and before the stage where you'd build your own data warehouse. Insights sits on top of the POS and stack you already run, and turns it into proposed moves the C-suite can approve in one place.
The decision loop
A rearview-mirror BI tool answers the question once. Insights closes the loop — explain, predict, recommend, approve, measure — so each next decision is informed by the last one and the model gets sharper on your specific business.
What moved the number, and why.
What happens if you change X — with confidence intervals.
The move with the best EBIT outcome — never executed without approval.
Named reviewer signs off. Required for any employee action — GDPR Article 22.
Was the prediction right? The model learns your business.
Rearview-mirror tools
Show the report. You read, decide, act, hope you measured the right thing. Next quarter, repeat. The tool never gets sharper on your business.
Self-driving navigation
Closes the loop in days, not quarters. Every recommendation is tracked against the forecast it was based on, so the system gets better at predicting your specific business.
What's different
Reporting tools draw the chart. Insights does the math, runs the simulation, drafts the move, and queues it for approval.
Capability 01
Five role-based agents (CFO, CMO, COO, CPO, CHRO) propose cost reductions and operational shifts in the language of the role. Every action a person feels — schedule, price, hours — is held in an approval queue. The CHRO Agent never executes; GDPR Article 22 requires a named reviewer, and we ship it that way by default.
Capability 02
Most "campaign performance" reports compare a before-period average to an after-period average and call the difference ROI. That's not how statistics works. Insights runs Welch's t-test against control and reports Cohen's d effect size — peer-reviewed math that tells you whether the lift is real and how big it actually is.
Example output
Capability 03
Stop forecasting from last year. Type in the EBIT you need this year, and Insights works the P&L backward — the daily revenue, the labor budget, the average check, the throughput per shift required to land it. You see the gap before the year starts, not in the December review.
Example calculation
Capability 04
Ask Insights questions the way you'd ask a senior analyst — "why is location 12 underperforming?", "what happens if we raise lunch combo 5% at the mall sites?". Get back a real answer, the data behind it, and a forecast with confidence interval. No SQL, no dashboard navigation, no waiting until Monday.
Example query
Five role-based agents
Agents share one canonical model, but answer in the vocabulary of the role asking. Permissions are per-agent. Actions are routed to whoever is allowed to approve them.
EBIT · margin · forecast
Finance vocabulary. Models price and mix scenarios; reconciles forecast vs actual at month/quarter close.
campaigns · ROAS · uplift
Runs campaign analysis with control groups, Welch's t-test, Cohen's d. Calls a campaign uplift real or noise — and stands behind the math.
service · throughput · waste
Compares service time, prep time, error rate, waste against the network median. Surfaces where ops drift opens up.
menu · mix · pricing
Menu engineering with margin and demand elasticity. Recommends mix shifts when input cost moves.
staffing · scheduling · retention
Recommends scheduling — never executes. Every employee-affecting action queues for human approval.
GDPR Art. 22 — human reviewer required.
Human in the loop
Insights does not autonomously change a guest's price, an employee's schedule, or anything that touches a person. Every recommendation lands in an approval queue with the data behind it, the predicted impact, and the alternatives.
For employee-affecting actions — schedules, hours, performance flags, retention measures — human approval is not a setting. It's required by GDPR Article 22 and we ship it that way by default. Operators have an AI trust deficit; "fully autonomous" is the wrong promise to make. We don't make it.
Approval queue
Example viewPricing · CMO Agent
Lift Friday lunch combo +5% across mall sites
Forecast: +€340/wk EBIT · n = 7 sites
Scheduling · CHRO Agent
GDPR Art. 22Reduce Tuesday opening shift by 1 staff at Location 04
Forecast: −€180/wk labor · service-time impact 0%
Menu mix · CPO Agent
Swap underperforming starter at 4 sites
Forecast: +€95/wk gross margin
Frictionless integration
Insights consumes a narrow slice of the data a chain typically warehouses — the events, prices, costs, shifts and forecasts that move EBIT. The rest can keep living wherever it lives. Two ways in: file uploads or a direct REST connector.
Path A
Drop the exports your finance and ops teams already pull weekly. Insights' pluggable importer maps your columns to the canonical model — no schema work, no ETL pipeline.
Path B
When the loop matters in real time, plug Insights into your POS over REST. Live in production today on R-Keeper; Toast, iiko, Square and Lightspeed on the roadmap.
No data warehouse required.
Lean ingestion, EU-resident, tenant-isolated. Source data stays where it lives.
How to get it
Insights is not sold as a standalone analytics product. It is the decision layer of the Fooodo platform — the same operating system that runs your QR menu, ordering and payments. Take Fooodo, and the data flows in automatically. The agents start working against the numbers your locations are already producing.
No percentage-of-revenue fee. No success tax. No bolt-on contract.
What you get on day one
Enterprise track available for 150+ locations · Custom POS · SSO · DPA
Frequently asked
BI tools end at the dashboard. Insights closes the loop: every recommendation it makes is tracked against the forecast, so the model gets sharper on your business. It also runs the marketing-ROI math (Welch / Cohen) and the reverse P&L workflow, and routes any employee-affecting action through GDPR Article 22-required human approval. Those are not features BI tools cover.
No. Insights uses a pluggable importer: drop CSV/Excel exports or wire a direct REST connector to your POS. The agents only consume the slice of data that moves EBIT — events, prices, costs, shifts, forecasts. No Snowflake required.
R-Keeper is live in production. Toast, iiko, Square and Lightspeed are scoped on the roadmap. Any other POS works via the CSV/Excel importer — full automation comes when the connector lands. Custom connectors are part of the Enterprise tier.
Two phases: ingestion (CSV importer or REST connector), then agent enablement once enough data has flowed to fit forecasts. Exact timeline is gated by POS connector availability and the cleanliness of historical data, and is scoped on the demo.
Two reasons. Legal: GDPR Article 22 requires human review of any decision that significantly affects an employee — schedules, hours, performance, retention. Auto-applying those is non-compliant in the EU. Operational: restaurant operators have an AI trust deficit for good reasons. A "fully autonomous" promise is the wrong one to make. AI proposes, people approve, the loop stays auditable.
EU region. Tenant-isolated. Your data fits your forecast models and improves your agents — never to train shared models other tenants use. Architecture and security details: /docs.
No. Insights is the decision layer of the Fooodo platform — bundled with the QR menu and ordering system at no separate cost. There is no percentage-of-revenue fee, no success tax, no bolt-on contract. If you run Fooodo, you get Insights.
See Insights against your numbers.
30-minute walkthrough with your CFO or COO. We'll model one decision in your data and run it through the full loop.