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Bring one decision and a small sample of the data behind it.

A useful first conversation is specific: what the team decides, when it decides, which outlet or item grain matters, and which records are available. Openfluid can then assess whether a forecast, operating rule or data change is required.

No generic demo requiredCSV or Excel is enough for discoveryData gaps stated before commitments
Useful context

What to share in the first review.

Decision

  • Who makes it
  • When it must be made
  • Forecast horizon and grain
  • What happens when the estimate is high or low
  • How the team makes the decision today

Data

  • Source system and export format
  • Available historical period
  • Outlet, item and ingredient identifiers
  • Known gaps such as stockouts or missing waste
  • One or two representative files with sensitive values removed where necessary
Good starting points

Example pilot questions.

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Revenue

What should each outlet expect to sell over the next seven days, and how does that compare with the current target?

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Preparation

How many portions of the top 20 items should each outlet prepare tomorrow?

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Inventory

Which ingredients need purchase or transfer before the next reliable supplier receipt?

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Waste

Which items repeatedly show excess preparation, and can actual outcomes be measured?

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Assessment path

What happens after you contact us.

Scope conversation

Agree one decision, user, horizon and expected output. We will not assume every module belongs in the first pilot.

Sample review

Profile the files for coverage, grain, identifiers, timestamp rules and material gaps. Sensitive fields not needed for forecasting can be excluded.

Feasibility note

Document what can be forecast now, what requires additional data and which baseline will be used for comparison.

Pilot proposal

Define implementation work, subscription, evaluation period, success measures, responsibilities and limitations.

FAQ

Contact questions.

Do I need to connect the POS before a discussion?

No. A representative export is usually more useful for discovery because it reveals the actual fields and history before integration work begins.

Can I remove customer information?

Yes. Restaurant demand forecasting generally does not require guest names or direct identifiers. Retain only fields required for the agreed decision.

Will Openfluid sign an NDA?

Confidentiality requirements can be discussed before non-public production data is shared. This prototype itself does not constitute an NDA.

What email should be used?

Email product@openfluid.ai directly, or use the form above. Both reach the same inbox.

Prefer email?

Send the decision, outlet count and available source exports to product@openfluid.ai.

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