AI Tools for Restaurants: What They Do and How to Choose

Which AI tool a restaurant should buy depends on which line of its P&L leaks the most, because no single product does every job. Voice tools answer the phone and take orders. Forecasting tools set schedules and prep. Back-office tools watch food cost. Marketing tools bring guests back. A newer group of agents works revenue channels such as catering sales and delivery platforms. This page is a category overview, not a ranking: for each job it explains what the AI does, what to look for, and which vendors sell it.

The decision it helps you make is which category to shop in first, and what to ask once you're there. It is part of our guide to AI for restaurants, which maps each use to the P&L line it moves.

How the examples were chosen

• What's included: for each category, a few vendors that sell a product built for restaurants and describe that capability on their own website. The lists aren't complete, and a vendor's absence says nothing about its quality.
• What we checked: each description below is the vendor's own claim, read on its site and dated October 2026. We haven't tested these products ourselves, so none of this is a tested finding, and no product is ranked above another.
• Our interest: Kutlerri.ai builds AI agents for restaurants. Our own agents are marked as ours, with their status (live, in beta or coming soon), in the table below.

Adoption is still early, which is a reason to buy carefully. In the National Restaurant Association's State of the Restaurant Industry 2026 report, as covered by Restaurant Dive, 26% of operators said they use AI-related tools. Marketing was the top use, and only 6% of restaurants use AI for customer orders.

AI tools for restaurants at a glance

Phone answering and ordering

Phone AI is the most visible use case and the easiest to test: call your own number and listen. It pays where calls go unanswered at peak or after hours, and only by the orders it adds that would otherwise be lost.

What to look for:

• POS integration. Orders should land in your POS and kitchen display without anyone retyping them.
• Menu accuracy. Modifiers, sold-out items and hours should come from your live menu, not a copy.
• A clean handoff. Regulars, complaints and complex requests should reach a person quickly.
• What it handles. Takeout orders, reservations, catering inquiries and general questions are different jobs. Ask each vendor which ones it does and test those.

Examples, as of October 2026, in each vendor's own words:

• Loman sells AI phone answering built for restaurants and says it offloads "routine calls and order taking".
• Slang AI focuses on phone answering and reservation management and says it switches between 97 languages.
• SoundHound AI sells voice AI for restaurant ordering, including drive-thru, and quotes White Castle and Jersey Mike's on its restaurant page.
• Square's AI voice ordering answers calls to your Square business number and takes orders, for Square Plus, Square Premium and Square Messages Plus subscribers.
• Popmenu includes AI phone answering in its marketing platform.

Kutlerri's Inbound Voice Assistant answers only a restaurant's catering line, not its takeout line. How phone ordering works, how to test it and how to check whether it pays are in voice AI for restaurants.

Catering sales and order management

Catering is the use case most AI lists skip, and the orders are large. Say your average catering order is $400 and your average takeout ticket is $40: in this example one catering order brings in the sales of ten tickets. The products in this category differ mainly in how much of the selling they do, and how much your team still does.

What to look for:

• Who does the outreach? Some products capture and manage inquiries; some add a prospect database and email campaigns your team runs; a managed service does the outreach for you. Ask exactly which tasks stay with your staff.
• Every channel. Can buyers reach you by phone, email, text and web form, and does every inquiry land in one place?
• Quotes you control. The tool drafts; you approve the price before it goes out.
• Customer access. Can you see and export each buyer's contact details and order history, what marketing permission do you have, and what does the agreement allow if you stop using it?

Examples, as of October 2026, in each vendor's own words:

• Toast Catering & Events covers BEOs (banquet event orders), quotes and invoices, and its help center describes lead forms for your website that convert to catering orders, plus leads you enter by hand.
• Caterease is catering and event management software that accepts online orders and inquiries and includes an AI assistant called Cai for finding events, clients and reports.
• CaterZen describes "a robust customer and prospect database", tracking of emails, calls, meetings and quotes, and "a built-in email marketing module" for nurturing clients toward repeat orders.

On the pages we reviewed, none of the three describes building a list of nearby businesses and contacting them on your behalf: with each, someone on your team runs the outreach. Our comparison of catering marketplaces, catering software and AI sales agents sets out that difference, with costs.

Kutlerri's Catering Sales Agent, which is live, takes that outreach on as a managed service: it finds catering-fit businesses within 30 miles of each location, contacts them by email, calls and texts, answers inquiries by voice, email, text and web form (a website chatbot is coming soon), and drafts quotes and invoices that the operator approves, with Kutlerri's own sales team behind it. Kutlerri charges a percentage of the catering orders it generates rather than a subscription, and rates are quoted individually for each restaurant.

Delivery-platform sales and promo spend

Delivery apps reward restaurants that rank well, show good photos and keep ratings up, and they make it easy to spend on promotions that mostly discount orders regulars would have placed anyway.

What to look for:

• Incrementality. Does the tool separate promo orders from new guests from promo orders by regulars?
• Root causes. Bad reviews usually trace back to the kitchen or packaging. Look for tools that find the cause, not just the score.
• Every platform in one view, by location.

Example, as of October 2026: Loop AI describes itself as "the AI workforce for restaurants", with finance, marketing and operations agents, and its customer stories cover third-party delivery reconciliation.

Kutlerri has two agents here, both in beta: the 3P Sales Agent for ranking, ratings, reviews, menus and bundles, and the 3P Marketing Spend Optimization Agent, which cuts delivery promos and ads that don't turn into orders.

Marketing and first-party sales

Marketing is where operators already use AI most. The useful question is not "can it write an email" but "does it tie each campaign to orders".

What to look for: campaign reporting linked to actual transactions, guest data you can export, and a clear answer on who does the work each week.

Examples, as of October 2026, in each vendor's own words:

• Toast IQ Grow "combines AI agents with a dedicated marketing expert" for Toast restaurants, and links campaigns to transactions.
• Popmenu calls itself "the AI marketing platform" and says its AI captures guest information, sends personalized messages and tracks return.
• Owner.com positions itself as "the AI platform restaurants use to grow first-party sales", with an AI-powered website, online ordering and a branded app.

Kutlerri's Online Sales Agent, for a restaurant's own website and app, is coming soon and isn't available yet.

Forecasting and scheduling

Forecasts drive two of your biggest controllable costs: the schedule and the prep list. A forecast that misses by a few covers a day shows up as overtime or waste.

What to look for: forecasts by hour and daypart, inputs beyond last year's sales (weather, local events), schedules built from the forecast, and a way to see accuracy after the fact, compared with a simple baseline such as same day last week.

Examples, as of October 2026, in each vendor's own words:

• 7shifts offers sales-driven labor forecasting and says it lets you "forecast sales and schedule smarter with AI".
• Lineup.ai sells AI-powered hourly, daily and weekly sales forecasts with automated scheduling, aimed at franchise and chain restaurants.
• Toast IQ answers forecasting and labor questions inside Toast.

Kutlerri's Prime Cost Optimization Agent, in beta, matches labor to demand; its Daily Prep & Waste Control Agent is coming soon. How restaurants use AI for demand forecasting explains what the models use and how to judge accuracy.

Inventory and food cost

Food cost moves every week with vendor prices, portions and waste, and most operators see it only when the period closes.

What to look for: automatic invoice capture, alerts on price increases, recipe costing tied to live prices, and theoretical versus actual food cost by item.

Examples, as of October 2026, in each vendor's own words:

• MarginEdge automates invoice processing and reports daily P&Ls and price changes in your most-used products. It describes this as automation rather than AI.
• Restaurant365 markets R365 AI for "AI-driven food cost monitoring, purchasing and inventory".
• Square says its Order Guide compares prices across your suppliers automatically.

The Prime Cost Optimization Agent, in beta, also covers this: menu pricing off real cost, vendor price alerts and recipe recommendations. To see where you stand first, run your numbers through the prime cost calculator.

Reviews and guest feedback

Reviews are a revenue problem dressed as a marketing one: a slow reply or an unfixed packaging issue costs repeat orders.

What to look for: one inbox across review sites and delivery apps, replies you can approve, and trends by location that point to a fixable cause.

Example, as of October 2026: Momos sells AI agents for guest experience and says it helps you "turn feedback into action" with insights by guest, location and channel.

Which POS vendor has the best AI?

None has the best AI in general, and the question usually matters less than it seems. If you already run one of these systems, start with its built-in AI: it already has your data, and it often costs little or nothing extra. Here is what the major POS vendors publicly offer, as of October 2026, from their own pages:

Judge any POS AI on four questions:

1. Does it act, or only answer? Toast says Toast IQ can make changes, but only with your confirmation.
2. Is it generally available or in beta? Square and SpotOn both label features as beta.
3. What's included, and what's an add-on? Built-in assistants and paid packages are often sold side by side.
4. What does it do with your data? Toast, for example, says your business data is not used for general model training. Ask every vendor the same question.

Switching POS for its AI alone rarely pays. A POS assistant answers questions about your own data; for phones, catering, delivery platforms and food cost, compare it with the specialist products above on the jobs you need done.

How to choose: compare the options on the same basis

The right first purchase is the one that adds the most contribution after its own costs, so put each problem in the same terms before you look at vendors. A dollar of cost saved reaches profit if sales hold. A dollar of added sales is worth only what's left after the food, labor, packaging and delivery it takes to serve. Never add the two into one total.

Worked example: Say a restaurant does $1,200,000 a year in sales. If prime cost runs 2 points over target and the restaurant brings it back without losing sales, that's $24,000 a year in expense savings. If it spends $8,000 a month on delivery promos and a third of that discounts orders regulars would have placed anyway, cutting that third saves $32,000 a year, as long as those regulars keep ordering at full price. If catering outreach adds 2 orders a week at $400 for 50 weeks, that's 100 orders and $40,000 in added sales; at $150 left per order after food, packaging, kitchen labor, delivery and card processing, it adds $15,000 in contribution. These are example inputs, not forecasts: use your own numbers.

In this example the promo cut adds the most and the catering orders the least, before any tool's cost. Subtract each option's yearly cost (subscription, per-use fees, setup, your team's hours, or a percentage of the orders a service brings in) and the order can change again. The AI for restaurants guide works through the same comparison for a larger restaurant.

Then ask every vendor the same questions:

1. Which number will it move, and how will we measure it? Agree the baseline before you start.
2. Who does the work after the login? A tool you have to run is different from a service that runs itself.
3. What data does it need? POS, invoices, delivery-platform access, phone line.
4. Is it live or in beta? Beta can be fine, if you know it.
5. How is it priced? Included with your POS, a subscription, a per-use fee or a share of the outcome.
6. What happens when it's wrong? Look for approvals on prices, quotes and schedule changes.

If phones are your biggest leak, start with a voice tool. If it's the schedule, a forecasting tool. If catering inquiries wait and nobody sells catering, start in the catering category, and decide how much of the outreach your own team will do.