AI in Hospitality

Better demand insight. Better decisions.
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AI in Hospitality
Trusted by leading organisations

How we support Hospitality

Hospitality performance depends on thousands of daily decisions. How much to produce. When to open and close. How to price. Where to deploy resources. What work can realistically be completed. These decisions are often made in isolation, using different assumptions across teams.

SolvedBy.Ai connects demand forecasting to pricing, opening hours, inventory, food production, labour, task planning, and budgets. Plans adjust as conditions change, giving leaders clearer visibility into what is happening, where pressure is building, and what needs to change before performance is affected.

AI Solutions for Hospitality

SolvedBy.Ai predicts demand at the level hospitality requires by site, outlet, service, day and hour. Forecasts reflect real trading behaviour, including seasonality, bookings, covers, events, and local conditions.

This gives hospitality teams early visibility into changes in arrivals, outlet demand, and visitor volumes, supporting better decisions on pricing, capacity, inventory, and operational readiness.
Labour demand forecasting translates expected demand into required labour by role and time period. It shows how labour needs rise and fall as demand changes, rather than relying on fixed assumptions.

For hospitality, this supports more accurate planning across housekeeping, front of house, kitchens, bars, and guest services, reducing unnecessary cost while protecting service when demand increases.
Staff scheduling converts labour demand into workable schedules that reflect availability, roles, and operating rules. Schedules are built to match expected demand, not repeated from previous weeks.

In hospitality environments where conditions change frequently, this reduces schedule churn, improves stability for teams, and limits last-minute changes that create cost and operational strain.
Inventory optimisation sets stock and production levels based on expected demand and uncertainty. It identifies risk early, allowing teams to adjust before waste or shortages occur.

In hospitality, this improves food and beverage ordering, consumables planning, and production by outlet, helping reduce waste while maintaining availability during peak periods.
Task scheduling plans what work should be done, when, and by whom, based on demand and capacity. Tasks are prioritised and sequenced to reflect how work is actually completed.

For hospitality teams, this improves execution across housekeeping, venue preparation, cleaning routines, and service support, ensuring critical work is completed when demand is highest.
Resource allocation supports decisions on where to deploy limited resources such as capital, space, equipment, and budget. It evaluates options using demand forecasts and expected return.

Hospitality leaders use this to decide where to invest, scale back, or reallocate across sites and outlets, improving returns without expanding the estate unnecessarily.
Price optimisation supports pricing and promotion decisions based on expected demand and margin impact. Prices adjust in response to changing conditions rather than reacting late through blanket discounting.

In hospitality, this helps protect revenue and margin during softer periods and supports stronger pricing decisions when demand increases.
Opening hours optimisation evaluates when venues should operate based on expected demand and financial impact. It identifies which hours contribute value and which create unnecessary cost.

This allows hospitality operators to adjust trading hours by site or outlet while maintaining availability when demand exists.
Budget forecasting builds budgets based on expected demand rather than fixed assumptions. Forecasts adjust as conditions change, giving finance and operations teams a clearer view of risk.

For hospitality organisations, this reduces variance, improves control, and limits late-period corrections.
(Best suited to larger, asset-heavy hospitality operations)
Predictive maintenance identifies early failure risk in critical equipment that affects guests, revenue, or safety.

In hospitality, this applies to systems such as HVAC, refrigeration, lifts, and venue-critical equipment where unplanned downtime has a direct impact on service and reputation.

Case Studies

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The Outcomes We Deliver

Hospitality organisations work with SolvedBy.AI to achieve:

Labour and operating costs aligned to real demand

Costs adjust as demand changes, reducing overspend and unnecessary pressure.

Profit is protected when demand softens

Pricing, opening hours, inventory, and capacity decisions change early enough to protect Gross Operating Profit (GOP).

Stronger control over demand and margin

Better decisions on pricing, promotions, and channel strategy to support direct bookings and reduce Online Travel Agencies (OTA) dependency.

Connected decisions across the operation

Revenue, operations, and finance plan from the same data through API-led integration.

Lower operational risk and better compliance

Earlier visibility of operational stress, maintenance risk, and cost anomalies.

Why SolvedBy.Ai

We use different models for different decisions

Demand does not behave the same across venues, time periods, or decisions. At SolvedBy.Ai we select and tune models based on how your hospitality business operates and how demand actually behaves.

Models update on time periods that matter to your business

SolvedBy.Ai updates forecasts and recommendations at the time intervals that reflect how your business actually operates. Models can run by minutes, half an hour, an hour, a day, a week, or longer planning horizons, depending on the decision being made.

Outputs are explainable

SolvedBy.Ai shows the reasons behind each forecast and recommendation, so teams can see why a decision is being suggested and what information it is based on.

Probabilistic scenario modelling

SolvedBy.Ai produces best-case, expected, and worst-case outcomes based on predicted demand. This shows the range of likely results so teams can plan for upside, downside, and the most likely outcome before decisions are set.

Technology Agnostic - API-first

SolvedBy.Ai delivers forecasts and recommendations through APIs, so they can flow into your existing systems and reports without replacing the tools you already use.

A partnership built on ROI

We partner with hospitality operators to deploy AI that anticipates covers, arrivals, and service demand by site and trading period, turning that insight into better rotas, food production schedule, smarter opening hours, more effective pricing, and calmer shifts.

Our pricing is simple: we ask for a 10:1 ROI. That means every £1 you invest delivers at least £10 back in measurable value.
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FAQ

SolvedBy.Ai predicts future demand and uses that information to guide decisions on pricing, opening hours, inventory, food production, labour, tasks, resources, and budgets. The focus is on making better decisions earlier, before results are affected.

Traditional forecasts rely heavily on historic averages and fixed assumptions. SolvedBy.Ai reflects how hospitality demand actually changes by site, outlet, service, day, and hour, and updates as conditions change.

No. SolvedBy.Ai supports decisions with better information. People remain responsible for decisions and execution.

SolvedBy.Ai uses existing business data such as bookings, sales, transactions, labour, and inventory, combined with relevant external demand drivers. No system replacement is required.

No. SolvedBy.Ai delivers forecasts and recommendations through APIs, so outputs feed into the systems and reports you already use.

SolvedBy.Ai is designed for hotels, resorts, hospitality groups, food and beverage operators, leisure venues, and multi-site hospitality estates where demand varies by site, outlet, and time of day.

It can be used by single sites, but the strongest value is seen in multi-site or multi-outlet operations where demand varies and decisions need to be consistent across locations.

It combines internal data such as bookings, covers, sales, transactions, labour, and inventory with external drivers like seasonality, events, and local conditions. Models are selected based on how demand actually behaves in each part of the business.

Accuracy depends on data quality and volatility, but forecasts are designed to improve over time as more data flows in. Importantly, SolvedBy.Ai shows a range of likely outcomes so teams can plan for uncertainty rather than relying on a single number.

No. It provides labour demand forecasts and scheduling recommendations that can be used by existing workforce and scheduling systems.

No. SolvedBy.Ai is technology-agnostic and API-first. Forecasts and recommendations are delivered into existing systems, reports, and workflows.

It supports decisions on pricing, promotions, opening hours, inventory levels, food production, labour planning, staff scheduling, task planning, resource allocation, and budgeting.

Costs reduce by aligning decisions to real demand. This limits overstaffing, excess inventory, food waste, unnecessary opening hours, overtime, and late corrective action.

By identifying demand changes early, teams can adjust pricing, hours, inventory, and costs sooner, reducing margin leakage when volumes drop.

Yes. Better demand visibility and pricing decisions support stronger control over availability and pricing, which helps improve direct performance and reduce unnecessary dependency on OTAs.

All sites plan from the same demand view and decision logic. This reduces variation caused by local assumptions and improves consistency without central micromanagement.

It produces best-case, expected, and worst-case outcomes so teams can plan for upside, downside, and the most likely scenario.

Yes. Outputs are explainable. SolvedBy.Ai shows the reasons behind forecasts and recommendations so teams understand what drove the result.

No. It provides insight and recommendations. Decisions remain with the business.

Finance teams use demand-led budgets and updated forecasts to reduce variance, improve control, and avoid late-period surprises.

Operations teams get clearer visibility into expected demand, workload, and pressure points, allowing them to plan realistically and reduce last-minute changes.

Leaders gain earlier visibility into risk, clearer explanations of outcomes, and more confidence that plans reflect reality across the estate.

Implementation typically starts with one or two use cases and expands. Because it integrates with existing systems, it does not require a full system replacement.

SolvedBy.Ai uses data you already have, such as bookings, sales, transactions, labour, inventory, and budgets, combined with relevant external demand drivers.

Models update on time periods that reflect how decisions are made, from short-term operational planning to longer-term budgeting and investment cycles.

Yes. It supports forecasting covers, planning food production, optimising inventory, scheduling labour, and aligning tasks to demand by outlet and service period.

Predictive maintenance is best suited to larger, asset-heavy hospitality operations where equipment failure directly affects guests, revenue, or safety.

Yes. By reducing waste, unnecessary operating hours, and inefficient resource use, SolvedBy.Ai supports more efficient and sustainable operations.

Success is measured through improved forecast accuracy, reduced cost leakage, better margin protection, fewer late surprises, and more consistent execution across sites.

SolvedBy.Ai is built specifically to connect demand insight to real operational and financial decisions under real constraints, rather than providing standalone analytics.

The first step is a review of how demand is currently forecast and how decisions are made across pricing, capacity, costs, and execution.

TL;DR

Hospitality performance is shaped by constantly changing demand, by site, outlet, service, day, and hour, yet most decisions on staffing, pricing, and opening hours are still made using static plans and averages.

SolvedBy.Ai uses AI to forecast real trading demand and connect it directly to rotas, capacity, food production, pricing, and operational plans, so teams can act earlier and trade more profitably.
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AI Solutions
AI Demand Forecasting AI Labour Demand Forecasting AI Staff Scheduling AI Opening Hours Optimisation AI Footfall and Visitor Forecasting AI Inventory Optimisation AI Predictive Maintenance AI Resource Optimisation AI Price Optimisation AI Budget Forecasting AI Shift Create AI Task Scheduler
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