Nory | Re-defining hospitality with an intelligent system of action
We start with the problem that sparked it all: an industry built on human intuition, yet crippled by high turnover, volatile margins, and a lack of decision tools. From forecasting guest demand to automating staffing and purchasing, Nory began by solving simple inefficiencies, only to uncover a far bigger opportunity: to rebuild restaurant operations from the inside out.
We then explore how this vision evolved into an intelligent system that manages everything behind the scenes: supply chains, teams, payroll, and capital flows. With AI at its core, Nory’s “always-on brigade” of assistants turns data into action, helping operators make faster, smarter, and more profitable decisions. The conversation dives deep into the delicate balance between automation and empathy, and how applying AI in reality - and not just in theory - helps close the adoption gap.
Finally, we look ahead to Nory’s next chapter: scaling across the US with local teams of “pirates and romantics”, building density from New York outward, and aligning capital and culture to a long-term mission: creating systems that empower people, drive margins, and redefine how an entire industry operates.
This is a story about transforming chaos into clarity - one algorithm, one restaurant, and one belief in better operations at a time.
00:53 - Conor Sheridan: Background & Breaking into Hospitality
06:33 - Mad Egg & The Origins of Nory
12:23 - Building an OS: Proritizing Product Roadmap
16:28 - Nory Today & Shipping with AI
22:49 -The Product Deployment Gap
28:04 -Navigating Go-To-Market Complexities
35:20 - Challenges Ahead: Internationalization, Building a Culture, and Product Focus
40:00 - Nory’s US Expansion: Building a Local Team
45:43 - Nory’s Road to $60m in Funding & Choosing the Right Partner
Transcript (edited for clarity and readability)
Luis: Today we have with us Conor Sheridan, founder and CEO of Nory. Nory is an AI-native operating system for the restaurant industry. It has raised over $60 million to date, has around $5 million in annualized revenue, and close to 300 clients. And this is the Samaipata Podcast. Welcome back to another episode of the show. Conor, great to have you.
Conor: Great to be here, Luis. Thanks for having me.
Luis: Your background is really interesting, and it's one of the reasons why we fell in love with the opportunity when we first analyzed Nory: going from finance to the restaurant industry to building the operating system for restaurants. Tell us how that path evolved and the key learnings that brought you to where you are today.
Conor: Yeah, it’s an interesting journey looking back. You can only connect the dots from the future, right?
I started off in strategic consulting and then moved into quantitative finance, doing automated fund management for big asset-management firms in Ireland. I really enjoyed that. I built strong skills around detecting signal from noise, analytics, numbers… trying to predict pricing — which never really works out — but still building an informed view of the market.
I always loved hospitality. I worked in restaurants in high school and university. And when I was on my trading desk, I’d constantly have a screen open looking at franchise opportunities from the US or the UK, thinking: “Can I open something as a passive investment?” Something that would get me more excited than what I was doing at the time.
Ireland is a bit of a time warp — a small country on the edges of Europe — so commercially, there’s a great arbitrage opportunity. It’s like Business 101: where do you open a barbershop? In the town where there is none. Many people in Ireland have been very successful taking concepts that exist in the US, Europe or Asia and bringing them to Ireland years before they become popular.
I looked at a lot of restaurant opportunities. Instead of opening a franchise like Subway, which would’ve been the “normal” decision, I decided to build something new. It came down to control — creative and entrepreneurial control. You can open a franchise, but it wouldn’t feel like it was mine.
So I launched Mad Egg, Ireland’s first fried-chicken-sandwich restaurant — kind of like a bougie Chick-fil-A. We opened in 2018 with immediate product-market fit because nothing like it existed in the country. We opened our second restaurant four months later, a third after eleven months, and kept expanding.
Luis: And that’s when complexity begins, right?
Conor: Exactly. As you add people, locations, geographies… you lose oversight. Restaurants are incredibly fast-moving — customer experience, operational pace, margins. You start losing control quickly. Margins varied a lot. Coming from an industry where you’re given incredible tooling — analytics, dashboards, real-time metrics — none of it existed in restaurants.
We looked at market solutions and were underwhelmed. Many tools “did the job” but none made sense of the noise for a 25-year-old manager running a €2M restaurant. I used to get this level of insight on a trading desk, but in restaurants there were fires everywhere.
So I started building internal algorithms for Mad Egg — demand prediction, staffing computation, menu prep, ordering. Super basic at the start: macros, spreadsheets, simple UI bolted together. The real complexity wasn’t getting the answer — it was serving it up to the team in a way they could use.
When I talked to other restaurants — mom-and-pops with 4–5 locations, bigger groups with 100+ — nobody had solved it. Some had a person calling managers every day to make sure they used the right forecasting figures. Completely broken.
That’s when I realized the opportunity wasn’t just for small businesses like mine — large groups were operating inefficiently at massive scale.
So I applied to Dogpatch Labs, an accelerator in Ireland, got accepted, and started to build something real. This was mid-pandemic — restaurants were closed — but I believed it was the right moment. They needed help. Many restaurants leaned in, even pre-product, to do design partnerships.
I started hiring the first product, engineering, and design team members — some of whom are still here today. We began by building algorithms and piping them into other tools via open (and not-so-open) APIs. It worked extremely well. We proved we could drive margins and productivity in multi-million-euro restaurant groups.
But then we realized: these incumbents could block us strategically. They owned the account. They would keep us away. To scale, we needed to own the workflows, the data gravity, and the account gravity. That’s when we decided to build the full operating system — which required much more capital, time, and complexity — and that became Nory.
Luis: “Operating system” is a big phrase in tech and often overused. But Nory really is one, with a ton of features. How did you prioritize the product roadmap?
Conor: Coming from finance, I naturally think in P&L terms: sales, COGS, workforce, contribution margins, prime costs, overheads. Prime costs — which are 60–70% of turnover — were the area to own. If you get control of that, you get a healthy business. If you don’t, you fail.
So we worked backwards:
– Guest journey & revenue management
– COGS (menu, supply chain, inventory)
– Workforce (labor, hiring, retention, engagement)
Everything had to tie back to improving the P&L. If a product or feature couldn’t be tied to improving profitability, we didn’t build it.
Luis: But customer ROI and Nory’s ROI aren’t always the same. How did you balance that tension?
Conor: We always start with delivering insane value — 10x outcomes, measurable improvements. Then you can package and price in many ways: usage, transactions, SaaS, percentage of P&L. If you tie value to the P&L, you can price appropriately.
We don’t want to be just a SaaS line on a P&L. We want to drive value across prime costs and overheads — which is why we expanded into back-office products like payroll, procurement automation, and now lending.
Luis: What does Nory do today? What can it do for clients?
Conor: Nory is a back-of-house operating system. We manage everything from the front of house (via POS integrations, kiosks, payments) through to head-office workflows.
We manage:
- COGS: supplier engagement, inventory, recipe management
- People: hiring, onboarding, performance, engagement, staffing, HR, payroll
- Operations: food prep, ordering, financial flows
- Capital: lending, using predictive P&L and workflow data
Clients can get capital quickly because we know their margins, risk, and payback windows.
Luis: And what about AI? It seems core to Nory.
Conor: Since day one. Our initial pitch was “AI restaurant manager,” but pre-ChatGPT we had to suppress it because the industry is very people-oriented. But our ethos was always: build omniscient AI assistants managing sub-assistants across workflows.
Initially we used deep-learning and ML models — black-box outputs that still drove massive value. But with generative AI, we’ve unlocked explainability and user-orchestration. Managers can now engage with predictive models, scenario analysis, and proactive insights. We’re also building a “brigade of autonomous assistants” that handle supply chain, HR, staff-churn signals, and more.
Luis: And clients now understand this isn’t Skynet?
Conor: (laughs) Yes, for sure. In the last 18 months the industry has done a 180. The macro environment — costs, inflation — has pushed people to adopt AI much faster. There’s still healthy skepticism, but that’s good. Keeps us honest. There’s a lot of fake “AI marketing” out there.
Luis: We were talking about the AI deployment gap and deployment-oriented delivery models…
Conor: Exactly. We serve SMBs and enterprise — same core problems, different complexity. You need co-creation with big enterprise clients to land algorithms effectively. So we forward-deploy data scientists: they analyze the business, identify leakage, predict outcomes, and show a roadmap to value. Then they land the models and iterate.
Deployment needs to be fast but accurate. You don’t want “deployment purgatory” — nor rollout failure requiring rollback.
Luis: How do you manage multi-location deployments?
Conor: Start with a small sample (10–15), prove outcomes with different complexity layers, then scale to 10% of the estate, then full rollout. Workforce modules sometimes require “big bang” deployment.
Luis: You also serve SMBs and large enterprise — two very different ICPs. How do you navigate go-to-market complexity?
Conor: We think in a funnel bow-tie: demand gen → selection → closing → onboarding → expansion → retention.
We run two motions:
- SMB / Mid-market:
– High-velocity inbound
– 14–21 day sales cycles
– Rapid deployment and time-to-value - Enterprise:
– Outbound, referrals, events
– Longer cycles
– Solutions engineers, forward-deployed DS, custom integrations
– A “plug-and-play” team for ecosystem integration
The core value proposition is the same, but execution changes.
Luis: The multi-ICP model creates retention challenges too, especially when moving upmarket. How do you retain smaller clients?
Conor: We keep empathy for the operator at the center. 60% of our team has restaurant experience. We never forget we’re building for the GM “in the fire.” That helps ensure SMB needs are naturally met.
Most problems we solve — prime costs, margin leakage — aren’t exclusive to enterprises. So many features benefit both. But yes, there’s always a tension. Prioritization debates happen every cycle.
Luis: What are the biggest challenges ahead for Nory?
Conor: So many.
Two years ago, you led our seed. We just closed a Series B.
Back then we focused on SMB/mid-market UK. Now we serve the largest chains in the UK and Ireland, and have entered the US.
AI has disrupted everything.
We’ve gone from 18 people to around 75 in a year.
We’re launching into the US — our kingmaker market. A year ago, our London office was one desk in a co-working space. Now it’s 45 people. We’ll repeat that in the US. Huge challenge, but energizing.
Focus is also big: broad product, multiple geos, many segments. With new funding, everyone wants to go fast. Sequencing becomes essential.
And hiring — growing 100% YoY creates cultural and productivity challenges. Avoiding “big-company meeting culture” is important. We need to stay nimble.
Luis: And when you’re building the US team, what profiles do you look for?
Conor: Three constants:
- High ambition.
People who could work anywhere but choose Nory because we swing big. - High agency.
“Barrels, not ammunition.” Owners who can run with problems. - Deep empathy for the industry.
If you don’t care about operators, you won’t build great tools for them.
These map directly to our company values.
Luis: And what does the initial team structure look like?
Conor: It’s a GTM motion:
– Enterprise AEs
– State/city leads
– Partnerships (critical — our first $1M ARR came mainly from POS partners)
– Chief of staff (“Pepe para todo”!)
Local, New-York–based team, in person at the beginning.
Luis: Let’s touch on fundraising. You’ve raised over $60M. What do you look for in investors?
Conor: It’s a partnership. You’re promising an outcome. You need alignment on ambition and IRR expectations. That’s why we partnered with Samaipata, Accel, and Kinnevik — all aligned on building something huge.
Then:
– Who can help you reach your next milestones?
– Who has taken companies from A → B successfully?
– What do founders say about them?
– And the human element: can you call them when things go wrong?
As for capital deployment: now it’s about dominating core markets, breaking the US, and reinforcing our position as the leading AI-native player.
Luis: Conor, thank you — super interesting. Thanks for joining us.
Conor: Thanks so much for having me. Appreciate it.
