Maria Zhang launched a broader version of Palona AI on August 17, extending its restaurant phone agents into software that combines customer conversations, business systems and security-camera feeds to trigger operational work. Palona also announced that a Series A had brought its total funding to $20 million, including converted SAFEs.
The financing announcement leaves the size of the Series A unclear. Palona previously launched with a $10 million seed round in January 2025, and the new total includes earlier financing and converted SAFEs. Palona did not identify a lead investor or valuation.
The structure matters because Palona is making a larger product bet than the restaurant voice agents it initially sold. Zhang wants Palona to capture an unanswered call, understand that it represents a high-value catering inquiry, route the opportunity to a manager and eventually use live operational signals to help the restaurant fulfill the order. That would move Palona closer to the daily control system for a physical business, where mistakes affect kitchens, staff and waiting customers.
"Physical businesses need AI that can understand what is happening and act in real time," Zhang said in the announcement.
Zhang's return to restaurant software
Restaurants have followed Zhang through two startup cycles. She founded Alike, a mobile app that recommended restaurants and other places based on a user's existing preferences. Yahoo acquired Alike for an undisclosed amount in February 2013 and moved its five-person team into Yahoo's mobile group.
Zhang later held engineering and AI leadership roles at Google, Meta, LinkedIn, Yahoo and Tinder. When she started Proactive AI Lab in June 2024, the project behind Palona, she described a system of specialized agents and multimodal models designed to help businesses act on customer needs. Palona's initial 2025 launch focused on emotionally aware sales agents for consumer-facing businesses, with early deployments outside restaurants as well as at Pizza My Heart.
The current strategy is narrower by industry and wider by workflow. Restaurants give Palona a demanding test environment: calls arrive during service, menus change, orders need to reach a point-of-sale system accurately and operational problems require action within minutes. The data is fragmented across conversations, reservation systems, ordering software and camera feeds.
Zhang built Palona with Tim Howes, the co-creator of LDAP and a co-founder of LoudCloud, Opsware and Rockmelt, and Xue "Steve" Liu, a McGill University professor who previously served as vice president of R&D, chief scientist and co-director of the Samsung AI Center Montreal, and earlier led research and innovation as chief scientist at Tinder. Zhang and Howes first worked together at Yahoo after the Alike acquisition. She later recruited her former manager to become Palona's CTO, describing him in a September 2025 post as a longtime mentor.
That history gives Palona a founding team with experience spanning consumer personalization, AI infrastructure and real-time systems. Palona's challenge is converting that pedigree into reliable software for operators whose tolerance for invented menu items, lost orders or noisy alerts is close to zero.
From answering calls to watching the floor
Palona organizes the new offering into Revenue Expansion, Revenue Intelligence and Operations Excellence. Its Ordering Agent handles calls and messages, answers questions and sends orders to a restaurant's point-of-sale system. Its Catering Agent gathers details such as party size, date, dietary needs and budget before routing an opportunity to a manager.
Revenue Intelligence analyzes conversations for demand, stalled inquiries and conversion problems. Operations Intelligence connects to existing security cameras and is designed to flag issues involving food preparation, cleanliness, guest experience and staff compliance.
Palona calls the underlying loop "Capture -> Understand -> Act -> Learn." The important step is "Act." Restaurant software already produces dashboards and reports. Palona is trying to turn detected intent or an operational event into an assigned workflow while the order can still be won or the problem can still be fixed.
Palona says its Interaction Model represents how people, objects, locations and processes relate over time, using spatial, temporal and semantic context. The announcement provides no technical evaluation of that model. A separate, verifiable piece of Palona's intellectual property is U.S. Patent No. 12,481,517, issued in November 2025. The patent covers routing requests among specialized AI agents using factors including user intent, latency, cost, availability and historical performance. It does not by itself validate Palona's restaurant outcomes or the broader Interaction Model claim.
Palona says its software supports systems including Toast, Olo, Square, OpenTable, Resy and Yelp Reservations. Palona's public materials do not establish which integrations are active at each named restaurant operator.
The operating results need a larger denominator
Palona says a multi-brand production study spanning Cali BBQ, Rooted Hospitality and Giordano's recorded 481 orders over 194 location-days and identified 305 large-order and catering inquiries across seven restaurants. At Cali BBQ, the company says Father's Day revenue rose 20% year over year and Palona became the restaurant's highest-average-order-value channel after adding catering and large orders.
Those figures show the type of return Zhang is selling: recovered demand rather than labor reduction alone. An unanswered phone call has an immediate revenue value when the caller is trying to place a large order.
The announcement does not identify the Father's Day comparison periods, baseline revenue, control locations or attribution method. It also does not report how many of the 305 inquiries became paid orders. The 481-order study is production data supplied by Palona, without an independent audit. Palona has not published revenue, annual recurring revenue, pricing or a total customer count.
The customer wording also deserves precision. Palona says it works with Din Tai Fung, Mountain Mike's Pizza, Giordano's, Rooted Hospitality and Cali BBQ. The announcement does not describe the commercial scope of each relationship or distinguish paying deployments from studies and other operating partnerships.
Palona is moving beyond the voice-AI fight
Restaurant ordering is already a competitive market. SoundHound says its voice technology operates in more than 10,000 restaurant locations and covers phone, drive-thru, text, scan-to-order and in-car channels. ConverseNow sells phone ordering, drive-thru automation, text conversations and point-of-sale integrations.
Palona's answer is to expand the unit of value beyond a completed phone order. Zhang is combining ordering, catering qualification, conversation analysis and camera-based operations in one product family. If Palona can reliably connect those signals, it can sell against a larger operating budget and build deeper integrations than a standalone phone agent.
That expansion also raises the implementation burden. Camera analysis introduces privacy, accuracy and alert-quality questions. Restaurant groups will need proof that Palona can identify meaningful events without flooding managers with false alarms. Point-of-sale and reservation integrations must remain accurate across brands, locations and changing menus.
Palona's disclosed investor group includes Ardenwood Ventures, CrimsonOx, UpHonest Capital, Turbo, Llama Ventures, Neo, Fusion Fund, Defy and Maynard Webb.
The $20 million total gives Palona resources to deepen deployments and test whether its restaurant system can extend to other physical businesses. Restaurants remain the decisive proving ground. Zhang has already shown that Palona can answer calls and surface demand. The next stage requires demonstrating that its agents can coordinate work across software and the restaurant floor with enough accuracy that operators entrust Palona with a larger part of the business.