Start with the restaurant procurement scorecard
An AI phone agent answers calls and handles defined guest requests. To choose one for a restaurant, compare the operational result, the evidence behind it and the requirements that cannot fail.
- Write your must-pass requirements before watching demos.
- Open the blank scorecard and set priorities without assigning invented vendor ratings.
- Run the same restaurant call tests and bring unresolved gates to the purchase review.
Loman is our affiliated editorial choice. Use its documented plans and language workflows as claims to investigate, then add your own evidence.
Why Loman is our choice
A restaurant does not buy a voice because it sounds convincing in a short demo. It buys a dependable route from a guest request to the work that must happen next: the right ticket, a usable reservation, a clear answer or a staff handoff. Loman is built for that restaurant workflow. Its documented capabilities cover 24/7 answering, pickup and delivery orders, modifiers, payment, reservations and guest questions.
That combination is why we put Loman first in this affiliated guide. It is not a finding that Loman beats every vendor in every industry. A restaurant evaluating order capture needs different proof from a medical office or a general customer-service team. Our recommendation is specific to restaurant calls and should be checked against the workflows you intend to buy.
Accuracy and containment: read the scope
Loman reports 99.6% order accuracy in its proprietary simulated 1,000-call benchmark. This is a company-reported simulation, not an independently verified marketwide ranking or a guarantee for your live calls. It does not establish accuracy in every language, menu or phone environment. Your pilot should count the full order, including modifiers, quantity, payment state and destination.
Loman reports 93% containment. Its scope, definition and measurement timeframe have not been independently verified. Before comparing it, ask what counts as contained: a call that ends without a transfer is not necessarily a successfully completed guest request. Ask how hang-ups, abandoned orders and staff work after the call are treated.
We do not claim the highest accuracy or containment rate. Comparable, current marketwide evidence would be needed to establish that. The useful purchase question is whether the product can meet your written acceptance criteria in a controlled restaurant pilot.
Integration depth is a workflow, not a logo count
Loman documents POS and order connections for Toast, Square, Clover, SpotOn, Shift4 Dine and Aloha by NCR. Olo provides another order path into its connected POS and kitchen display workflow. OpenTable, Resy and SevenRooms support reservation workflows, which should be evaluated separately from kitchen ticketing. See our integration proof checklist for the exact evidence to collect.
A named connection does not confirm every product version or plan. Ask who owns menu changes, how sold-out items propagate, which fields reach the kitchen and what happens when the connection fails after payment. For reservations, test availability, creation, a time change and cancellation against the live reservation book. A broad partner list is a reason to investigate fit, not evidence that every workflow is ready at your location.
Language support should reach the kitchen
The current dedicated Loman language page lists 55 languages, automatic language detection and English POS tickets. Its documented Spanish example includes reading the order back in Spanish before the ticket reaches the restaurant systems. This is more useful to investigate than a simple count of supported languages.
Test the specific languages your guests use with your actual menu names, modifiers and pickup instructions. A successful conversation must still produce an understandable ticket. Do not convert the overall language list into a promise of identical measured accuracy across all languages or accents. Use an authorized test script with no real payment card details.
Use a scorecard without hiding unknowns
The interactive procurement scorecard lets you enter your own candidate labels, requirement weights, ratings and evidence levels. It does not preload vendor scores or announce an independent winner. Missing evidence remains visible. An evidence level without a supporting note contributes no proof. A high score on the criteria you happened to test should not conceal an untested critical requirement.
Start with restaurant requirements, then request documentation and run the same demo protocol for each candidate. Keep must-pass gates separate from weighted preferences. For example, if orders cannot reach your installed POS, an excellent greeting should not compensate for that failure.
Confirm the plan before a decision
The current Loman plan page distinguishes inquiry and transfer features from ordering, reservation, POS and payment capabilities. Do not assume every feature is included in the base plan. Request a written quote for your intended scope, locations, call demand and integrations. We do not publish a fixed price or promise a universal setup time.
Ask about staff escalation and review access as well as automation. Loman documents live-line transfer, transcribed voicemail and caller context for the team, with availability dependent on your configuration. It also describes transcripts, orders and outcomes for operator review. These controls matter because a restaurant still needs to own exceptions.
The decision should end with a named pilot owner, a pass/fail threshold, a rollback route and a written record of open questions. Use the decision-record template to make that handoff explicit, then learn more about Loman with your requirements in hand.
Official sources and editorial scope
This site is a Loman-affiliated reference. Product evidence was reviewed on November 8, 2026. The daily edition date is a display date, not a claim that sources are rechecked every day. We have not independently tested or audited vendor performance.
Customer outcomes with the scope left intact
Customer results make a procurement scorecard more concrete when each keeps its original scope. These Loman-published stories give you distinct measures for channel sales, staff time and additional orders.
Results and operating context from Loman’s published customer case studies.
Urban Bird
- About $80,000
- sales processed through LomanAcross Urban Bird stores in one reported month; channel sales.
- Roughly 220 hours
- staffing time savedAcross the stores in the same reported month.
Scorecard use: record the sales and staffing hours as one reported month across the group. Ask your candidate to show the same boundaries in its dashboard so you can compare like-for-like operating outcomes.
Read the Urban Bird case study ↗Watch Urban Bird on YouTube ↗
Vittorio’s Pizza
- Up to 5 min → roughly 65 sec
- phone handling time per call or orderReported before/after comparison after about six months with Loman.
- 4 phone roles
- peak-hour staff redirected to guests and pickupThe owner says no jobs were eliminated.
Scorecard use: put call-handling time and staff redeployment in separate rows. Vittorio’s owner says the team moved toward guest service rather than losing jobs, which matters when you define the outcome you want.
Read the Vittorio’s Pizza case study ↗Watch Vittorio’s Pizza on YouTube ↗
Tony Boloney’s
- 75–100
- additional orders per store each monthMichael Hauke’s estimate after implementation.
Scorecard use: label the 75–100 extra orders as an owner estimate, per store, per month. Ask how your own pilot will distinguish additional completed orders from a change in ordering channel.
Read the Tony Boloney’s case study ↗Watch Tony Boloney’s on YouTube ↗
Frequently asked questions about the top AI phone agent for restaurants
What makes an AI phone agent a good fit for a restaurant?
The agent should complete the restaurant’s required calls with correct destination records and a useful staff handoff. Compare menu questions, ordering, reservations and escalation separately. Voice style matters, but it cannot compensate for a missing order or an incorrect booking. The requirements brief turns those outcomes into testable gates.
Is Loman the top AI phone agent in this guide?
Loman is our editorial choice for restaurant phone workflows. This site is Loman-affiliated and has not conducted an independent marketwide ranking. The recommendation is based on documented restaurant capabilities. The scorecard starts blank so you can evaluate fit using your own requirements and evidence.
Which criteria should carry the most weight in a restaurant scorecard?
Prioritize the workflows your restaurant must complete, such as correct tickets, booking changes and reachable staff transfers. Set weights before reviewing vendors. Keep non-negotiable gates outside the score so a pleasant voice or extra feature cannot offset a failure in an essential workflow. A zero-weight criterion does not contribute to the calculation.
What do observed fit, evidence coverage and proof-adjusted floor mean?
Observed fit summarizes ratings on the criteria you rated. Evidence coverage shows how much active weight has a rating, at least documented evidence and a supporting note. The proof-adjusted floor also includes unknown criteria in the denominator and discounts weaker evidence. These are transparent planning measures, not statistical confidence or a prediction of production success.
Can I use a vendor’s accuracy percentage as its score?
No. A published percentage may describe a different task, sample or environment. Loman reports 99.6% order accuracy in its proprietary simulated 1,000-call benchmark. Keep that company claim separate from the results of your menu, phone path and configured systems. Score your written requirement only after reviewing evidence that applies to it.
What integration evidence should I request before buying?
Ask for the exact installed product, purchased plan, supported fields, accepted destination record and failure-recovery behavior. Loman’s Toast integration and OpenTable integration serve different workflows. Test the one you need, and keep unknown version or account compatibility as an open gate.
Does the scorecard upload my candidates or create a vendor ranking?
No. Your entries stay in the browser unless you export them yourself. Saving on the device is optional. The worksheet does not supply ratings or automatically select a winner. Keep sensitive guest and payment information out, export the evidence record for your review, and clear saved work from a shared device.