India’s role is central to our billion-dollar R&D plan: Toast CEO Aman Narang

When Aman Narang began Toast in 2011, he and his partners had no intention of shaking up the $160 billion restaurant payments market. The founders had a simple goal—to let diners pay through their phones. However, after 12 years and a $30-billion IPO, Toast has a lot more on its menu. 

Today, its platform powers everything from kitchens to convenience stores, as it strives towards becoming the backbone of in-person commerce.

Initially launched as a consumer-facing restaurant app, the Boston-based firm pivoted from simply processing customer payments to providing comprehensive restaurant point-of-sale (POS) solutions. 

Toast exemplifies vertical SaaS, embedding payments, lending, payroll, and more. With $1.5 billion in annual recurring revenue (ARR), the Boston-based firm derives 80% of its income from fintech offerings alone.

In an interview with YourStory, Narang shares how AI is disrupting the vertical SaaS industry, outlines Toast’s AI strategy, and weighs in on how India is central to the company’s billion-dollar R&D plan.

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Edited excerpts from the interview:

YourStory: You started Toast in 2011. How has technology changed over the past decade? 

Aman Narang: Toast originally began as a way to start a company with my co-founders, Steve and Jon Grimm. We met while working at Endeca, an ecommerce firm, which was acquired by Oracle by the end of 2011. They were some of the best people I'd ever worked with. When starting a company, you want to find people who complement your skills and values.

We landed in this restaurant business totally by chance.

In the early days, we were just tinkering. One of our first experiments was letting people use their phones to pay—something like the QR code ordering you now see at tables. What we realised was restaurants were one of the few categories where the transition to cloud hadn't happened. Many of them were still using point-of-sale systems from the ’90s—or even the ’80s—with physical servers running in the basement. Most of their technology was disjointed. 

That’s when we decided to build a vertically integrated platform designed for restaurants. It started with helping restaurants move to the cloud, but the vision quickly expanded into an all-in-one system where every application works together. 

Today, our platform spans five key areas: commerce, which includes the point-of-sale, reporting, and kitchen management; fintech, covering payments, lending, and related tools; guest services like online ordering, loyalty, and CRM; employee management with payroll and scheduling; and accounting and back-office operations.

Over the past few years, we’ve expanded our business. For the first decade, our focus was primarily on small and mid-sized restaurants in the US. In the last three to four years, we’ve grown into the enterprise segment and expanded internationally—now operating in the UK, Canada, and Ireland, with more countries on the horizon. We’ve also taken a major step by branching out beyond the restaurant industry for the first time. Now, we power food and beverage retail, which includes grocery stores, convenience stores, and gas stations. 

Our vision is to become the go-to platform for in-person commerce—much like how people think of Shopify when they think of e-commerce. That’s how we see Toast evolving over the next decade and beyond.

YS: How are you leveraging AI to help your customers? 

AN: When it comes to AI, one of our biggest strengths is the dataset across restaurants in the US. Toast processes nearly $160 billion in gross payment volume in 2024, representing a meaningful share of the U.S. restaurant economy. That scale gives us access to rich data sets across employee behavior, guest preferences, supplier networks, inventory, menus, and more.

The opportunity now is to leverage this data to truly help the restaurant community. 

Imagine a server walking up to a table and already knowing what the customer is likely to love on the menu and why. They know the guest’s favourite drink, dietary preferences like being vegan or having a peanut allergy. If the customer is a regular, the server might drop off your regular dish—something that costs the restaurant nothing but adds a personal touch. Even something as simple as greeting them by name and acknowledging their presence is something tech can enable. 

This is the kind of hyper-personalised experience that AI can unlock. We believe it can drive higher cheque sizes and encourage more repeat visits from guests. That’s an example of where we think AI can play a big role.

YS: How widely are your customers adapting to your AI offerings? What kind of traction are you seeing with such tools so far?

AN: One of the biggest shifts we’ve seen is how our restaurant partners are using our generative AI marketing tools. We're also seeing strong adoption of our benchmarking tools—because most restaurants don’t have access to data to guide their decisions. 

We recently launched a product called Sous Chef, which we think of as your intelligent back-of-house assistant.

Looking ahead, we see major opportunities in voice AI and video. There are already startups building AI-powered phone systems, and we believe there's huge potential in automating and enhancing various workflows across the board. That said, if you look at most business applications today, especially in terms of AI-driven productivity, it’s still early days. When we ask operators where AI has been game-changing so far, the most common answer is customer support. 

We're actively learning, and figuring out which applications of AI will truly stick and drive impact for our customers.

YS: What markets do you consider primary as of now?

AN: For the first decade, we were focused exclusively on the US market. In 2021, we expanded internationally—launching in the UK, Canada, and Ireland—and we have a roadmap for entering several more countries. 

India, in particular, is a key part of our long-term vision. While we haven't launched our products here, we have a significant presence through our team in India, which plays a critical role across R&D, product innovation, customer support, finance, and back-office operations. 

YS: How do you ensure that privacy and data protection remain central to your AI strategy, given the volume of customer and restaurant data you’re working with? 

AN: We have a strong legal and data privacy function within the company. When we launched in the EU, for example, we had to build that capability from the ground up—ensuring customers can opt out, understand what data is being collected, and have visibility into how their data is stored, archived, or deleted over time. We follow all regulations and compliance standards across the regions we operate in.

Our data strategy is centered around helping our restaurant partners and their guests. 

For internal productivity—like support or developer tools—we leverage best-in-class third-party solutions rather than trying to build everything ourselves. We focus our build efforts where it truly matters: within the restaurant ecosystem. We have a dedicated data platform team working on foundational challenges like data warehousing, accessibility, and connectivity—because making data usable at scale is a hard but essential problem.

YS: Could you outline the company’s key financial targets and growth priorities?

AN: We focus on maximising impact rather than chasing specific targets. Since getting our first customer in the summer of 2013, it’s been less than 12 years—and today, we serve over 134,000 customers. 

Part of the reason we’ve expanded into new products, geographies, verticals, and customer segments is because we see a much broader opportunity for Toast. Our vision—ambitious as it may be—is to become the platform that anchors local commerce. It’s a far bigger mission than where we started, but one that aligns with the sheer scale of the global commerce market. We're not opportunity constrained. 

YS: With AI causing such disruption across the industry, what internal changes or adaptations have you made as a company to stay ahead?

AN: A big part of our business has actually been outcome-based from day one. While we do offer traditional SaaS modules, a big portion of our revenue comes from payments—where we monetise based on platform usage. Similarly, our lending and payroll businesses are both tied to how actively customers use the platform. Even our Gen AI and marketing tools are outcome-oriented, to help restaurants drive specific results. 

As we continue evolving with AI and data-driven offerings, we see usage-based pricing becoming even more important—especially in price-sensitive markets like restaurants and digital commerce. The more you can tie your pricing to outcomes, the more likely you are to monetise it best.