Restaurants, cafés & food operators
Turn sales, stock, recipes and labour data into decisions your managers can review and use.
Binarify helps restaurants and food businesses assess and implement demand forecasting, purchasing support, waste analysis, menu profitability, labour planning and multi-site reporting around existing systems.
Perumal founded and ran a restaurant ERP software business from 2012 to 2019. That operating context shapes a practical approach: inspect what the POS and back-office products already do, fix the data flow, and build only where a real gap remains.
30-minute discovery call · fixed scope before implementation
The food operations guide library
Each guide maps the inputs, controls, review points and measures. The workflows are proposed implementation approaches, not published client outcomes.
Managers plan sales, prep and staffing from disconnected reports and instinct.
Combine clean sales history with known calendar and operating factors, then show a forecast range and the assumptions a manager should review.
Measure Forecast error · bias · stockouts · overproduction
Read the guide →Counts, recipes, invoices and sales do not reconcile quickly enough to guide orders.
Create reviewed order suggestions from usable stock, demand, lead times and pack sizes while keeping supplier approval with the operator.
Measure Count variance · emergency buys · stockouts · purchasing time
Read the guide →Waste is recorded inconsistently, so teams cannot see why it occurs or where to act.
Capture reason, item, quantity, stage and location; identify recurring patterns and test one operational change at a time.
Measure Waste by weight and value · reason coverage · waste per cover
Read the guide →Popular items can look successful while recipe costs, modifiers and channel fees weaken contribution.
Join item sales to current recipe and channel costs, flag uncertain inputs, and prepare decisions for culinary and commercial review.
Measure Contribution per item · cost coverage · mix · override effects
Read the guide →Schedules miss demand by daypart or ignore role, availability and local rules.
Turn an approved demand plan into suggested role coverage, then let managers resolve constraints and publish the schedule.
Measure Forecast-versus-actual labour · understaffed periods · edits · overtime
Read the guide →Regional teams spend hours combining reports before they can investigate a variance.
Standardise definitions, reconcile location data and produce source-linked briefs that assign anomalies for review.
Measure Reporting effort · unresolved variances · data freshness · correction rate
Read the guide →Start with a baseline by location and period. Count avoidable handling effort, waste, stockouts, emergency purchasing and contribution effects without assuming every minute released becomes cash.
Read the restaurant AI ROI guide →Your software comes first
Restaurant platforms already cover substantial parts of the workflow. Toast describes invoice capture, recipe costing, inventory counts and actual-versus-theoretical reporting. Square documents inventory, ingredient costs, vendors and purchase orders. Availability varies by country, product and subscription.
We check whether the current system can already produce the required decision, whether inconsistent recipes or counts are the real constraint, and whether a supported integration can remove manual reconciliation. A custom layer comes after that assessment.
AI is useful where patterns, language or messy documents need interpretation. Stable calculations, approval thresholds, allergen records and food-safety controls should remain explicit and testable.
How we choose an implementation approach →A measurable first scope
A useful pilot does more than produce a dashboard. It changes a repeatable decision and records whether the recommendation was accepted, adjusted or rejected.
Food safety, allergens, employment rules and supplier commitments stay with the authorised people and processes that govern them.
First engagement
From $2,500 USD · 1–2 weeks
Implementation sprints start at $15,000 USD. The diagnostic fee is credited against the sprint if you proceed. Scope and fixed price are agreed in writing.
What the diagnostic includes →View pricing and terms →Before implementation
Usually not. We first examine the features, integrations and reporting already available in your current products. Configuration, cleaner master data or a small connection may solve the problem. Custom software needs a defined gap and a credible business case.
No. A single busy venue, catering operation, café group, dark kitchen or multi-site food business may have enough repeated work to justify an assessment. The value depends on transaction volume, avoidable effort and margin impact rather than location count alone.
Our default design prepares a recommendation with its inputs and exceptions for an authorised person to review. Approval limits, supplier terms, food-safety requirements and pricing authority remain explicit. Automation can be expanded only after the workflow is reliable.
That depends on the workflow. A forecasting pilot might need item or category sales, trading hours, promotions and known closures. Inventory work may also need recipes, counts, invoices, lead times and waste records. We minimise the fields and period before data is shared.
AI output is not treated as a food-safety release or verified allergen statement. Those processes use approved source records, qualified owners, traceable changes and the applicable rules for each market. We define boundaries before implementation.
The AI Impact Diagnostic starts at $2,500 USD and takes one to two weeks. Implementation sprints start at $15,000 USD, with scope and fixed price agreed in writing. The diagnostic fee is credited against the sprint if you proceed.
Bring one workflow, its frequency and the systems involved. No customer or employee records are needed for the first call.
Read about Perumal's restaurant software experience →