Revenue, orders, menu demand, preparation, ingredient requirement, waste-risk views and Forecast Chat within the agreed data scope.
Early-access pricing
Start with one outlet and one decision.
Openfluid Restaurant Forecasting is in early access. Pricing is scoped per restaurant based on outlet count, data sources and support needs once a usable data flow is established. Data preparation, custom integrations and implementation work are scoped separately.
Transparent subscription starting pointImplementation scoped separatelyNo long-term commitment implied by prototype
Early access
PricingCustomscoped per outlet
Final price depends on usage, connections, forecast grains and support. Taxes may apply.
Discuss fit →Product scope
What the starting subscription is intended to include.
Consolidated and outlet-level planning for the subscribed locations, subject to available history and consistent identifiers.
A recurring data and forecast update cadence agreed for early access; real-time ingestion is not assumed.
Product onboarding, forecast interpretation and issue triage within the early-access operating model.
Not included in the starting subscription: bespoke source-system development, historical data repair, on-site process redesign, automatic purchase-order execution, custom model research or contractual service levels.
What changes the scope
Implementation cost is driven by data conditions, not page count.
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Source access
A stable export is simpler than undocumented APIs, manual downloads or restricted aggregator access.
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Data quality
Duplicate items, changing outlet IDs, missing stockouts and inconsistent units require mapping and remediation.
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Planning grain
Outlet-day revenue is materially smaller than outlet-item-day demand plus ingredient requirements and waste.
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Refresh and operations
Daily batch ingestion differs from intraday updates, alerting, retries, historical restatement and support coverage.
Pilot structure
A pilot should earn the subscription.
Examples: tomorrow’s preparation quantity or next week’s ingredient requirement. Avoid measuring success through a vague “better forecasting” objective.
Compare Openfluid with the restaurant’s current method and simple seasonal baselines on the same historical periods.
Operators review recommendations without surrendering control. Overrides and reasons are captured.
Evaluate forecast error, action adoption, stockout exposure, potential excess and time saved, only where the data supports each measure.
FAQ
Pricing questions.
Is there a fixed price for every restaurant?
No. Pricing is an early-access starting subscription scoped per outlet. Final pricing depends on product usage, data sources, implementation and support requirements.
Is there a free trial?
The current prototype does not establish a universal free-trial policy. A limited data review or pilot may be more useful because forecast value depends on the restaurant’s own history.
Are integrations included?
Standard ingestion supported by the product may be included in future plans. Custom source work and unusual data remediation are scoped separately during early access.
Can a restaurant cancel?
Commercial terms, billing cadence and cancellation need to be stated in the final order form. This prototype page is not a binding offer.
Price the actual scope, not an imaginary implementation.
Share outlet count, source exports, planning horizon and the decision you want the team to make differently.