Daniel Lereya, Monday.com’s Chief Product and Technology Officer (CPTO) knows the company operates in a “crowded market” – but having been with the Tel Aviv-founded company since it was still called Dapulse in 2016, he clearly believes in its ability to offer something different.
On a call with The Stack Lereya is keen to emphasise the fast-growing software provider’s approach to commodifying AI technology to support its ambitious expansions across CRM, product development, and IT ticketing platforms – joining us after the company announced full-year revenues that tipped it over the $1 billion ARR mark for the first time.
The company’s product development has been aggressive, bringing it close to a field of heavyweight rivals like Salesforce and ServiceNow – and Lereya is happy to directly compare platforms. (Monday.com describes itself as “multi-product platform that runs all core aspects of work.”)
Last month, for example, it took its “monday service” (yes, replete with trendy lowercase branding) out of beta mode and officially launched the “one-stop-shop for service operations, designed to centralize and streamline workflows across IT, business, and service teams…”
A “totally customisable” platform
In 2022 meanwhile it launched a “monday CRM” and Lereya claims that just a year from its launch, the solution was already competing with market leaders by offering something “fundamentally different”.
To be “very simplistic” he says, on one side of the market there are smaller solutions only suitable for SMEs, and on the other side you have “some of the biggest platforms in the world” that are complex to deploy.
Referencing Salesforce and ServiceNow, Lereya says: “On paper, you can do anything, but in practice… If you want to change something in your sales process, you need an army of system implementers, and you need a lot of money in order to do that many times” (e.g. across different units.)
Monday.com’s co-CEO Roy Mann says CRM is “becoming more significant in terms of the contribution” to ARR but it’s early days – the company's platform still sits outside of the top 10 CRM products by market share.
Despite this, Lereya claims Monday.com's low-code system where “almost everyone in the account is a builder," will win out: “This [adaptability] is an inherent advantage, and this is the reason that I think we win. Although we don’t have all the features yet… we will be winning deals [over] CRMs that have been built for years” he tells The Stack.
(The company has been pushing upstream from its mid-market comfort zone in search of larger enterprise deals and in 2024 grew its largest customer to 80,000 seats. It names over 245,000 customers and last year grew its headcount 35% to 2,500 staff, with more recruitment pending.)
Providing resilience for a multi-product platform
The 2022 CRM launch and the release of the Monday Service IT ticketing system in 2024 later highlights Monday.com's growth ambitions.
In a post-Crowdstrike outage world, can customers at enterprise scale feel comfortable hosting more and more of their operations with one provider, The Stack asks? Lereya responds: “There's no single company in the world that can say we're going to have a 100% uptime.”
But the CPTO says a “state of mind” focussed on resilience is big for his team as the company scales: “It’s a challenge … but it’s a good challenge to have, and we invest a lot in it” [scaling resilient infrastructure] he says.
“If you look at our investment map and what we’re doing with our engineering and product teams. [It’s clear that] a lot of work and a lot of resources are being dedicated to invest in the future.”
A passionate development team
In fact, smart investment into Monday.com’s development teams is one of the reasons behind swift uptake of its AI-augmented products Lereya claims. (More on that below.) When first pulling people from its engineering teams to create an AI “force”, he focussed on talent and passion; some had “experience in it, but [most] learned on the go.”
However, when looking to expand, it took time to find AI experts able to translate their knowledge into developing a useful product, he says.
“The challenge of bringing talent in was to find people that are really passionate about providing business value to customers – because many of the specialists in AI [out there], are very distant from the end user.”
Monday.com spun up a “core team” working on “actually cracking the hard technology” before encouraging others to use the tech for new innovations through events like its AI hackathon. Lereya says: “Our internal lingo for that is ‘core versus playground’. So the core team should build the [technology’s] core, and then it should build a playground in which other people can leverage this core without getting in depth.”
Knowing where to invest, and how to monetise
While it’s all well and good curating a top engineering team and having them build your AI infrastructure, knowing how to deploy that technology, and monetise it, across platforms is another challenge.
Lereya tells The Stack this was something Monday.com learned when it tried to get ahead of AI, launching AI assistants early but seeing little adoption by users. A new approach was needed with a focus on AI augmentation that really "makes our product better” and improve KPIs.
“It’s a crazy zoo out there in terms of monetisation…” says Lereya “so we needed to come back to the basics and we said ‘we really want two main things’. One: we want to tie AI monetisation to real value. Two: we only want to get paid for it if our customers find value,” he says.
Simplifying AI to encourage experimentation
The result of this rethink was the creation of “AI blocks” – simplified modular AI augmentation tools for users which, as Lereya puts it, “you can take with no-code, you don't need any technical expertise, and with just one click you can actually integrate AI into your existing workflows.”
These blocks can take many forms, with the example given by Lereya one called "extract" that can be used by companies looking to pull data from documents and spreadsheets – with Monday.com extending free credits for customers to deploy these for a certain number of hours.
Lereya says: “We have a very large hold with mid market companies and I think that for them, AI is totally exciting, because suddenly they can be competitive with larger organisations as it's not necessarily about people.
“And in that sense, we didn't want a pricing mechanism that was [corresponding] to seats. We didn't want to be upset if someone used AI in order to be more efficient in his organisation.”
In this vein, all Monday.com users are given an initial 500 AI action credits per month with their contract, a number Lereya describes as the “tipping point” for experimentation, with users having to buy any credits after that: “We saw that after 500 actions, it means that people are no longer experimenting, they are now actually integrating it into their core flow.”
Keeping AI safe
With deeper AI integration comes an increased risk of technology errors, something businesses have quickly been learning when AI models write bad code or give employees access to confidential information.
Lereya says that existing frameworks and guardrails designed to follow user outlined permissions could be adapted: “The same rules that we have for data residency within regions, we follow with AI. In terms of encryption, we do the same with AI, both in transit and in rest.
“So I feel in that sense the risks are not materially different from things that were mentioned a few years ago about the cloud,” he responds.
Technically, Monday.com’s AI “primarily” relies under the hood on Microsoft Azure’s AI model, though Lereya also highlights integrations with Open AI’s ChatGPT, Mistral and Tropic providing “advanced users” a choice on the model which best fits their needs. And he’s bullish on the future: “Over time we expect AI to solve each and every one of the tickets, and only escalate to a human when it needs to, not vice versa.”
Users will also have a way to bypass the technology: “We make sure that the one who drops the ticket will know that this is an AI,” Lereya says.
“We give them the path to say, ‘listen, this is not what I asked for.’ We give power to the people in support to have a quality assurance for the AI, as I think in many products these things are left neglected.”
