Side, a long‑standing services provider formerly known as PTW, has entered into a six‑month memorandum of understanding with Denmark‑based artificial‑intelligence specialist Modl.ai. The agreement paves the way for a joint effort to create an AI‑driven quality‑assurance (QA) platform that blends Side’s deep industry experience with Modl.ai’s cutting‑edge machine‑learning capabilities. Modl.ai, a relatively new player in the gaming sector, was founded in 2018 and secured $1.7 million in seed financing two years later. Its chief commercial officer, Martin McBride of Side, describes the partnership as a marriage of complementary strengths: “The MOU effectively brings the best of what Side has and the best of what Modl.ai has together in a unique solution.
One of the crown‑jewel, holy‑grail experiences for the games industry right now has been using AI technology to better augment QA services. No one's really found a great solution for that. We think we have.” Earlier attempts at AI‑enabled QA, including earlier versions of Modl.ai’s own tools, required developers to hand over complete game builds or even source code so that the AI could run tests internally.
This "integration‑based" approach, which relied on plugins and SDKs, proved cumbersome and created friction for development teams. As Modl.ai founder Christoffer Holmgard explains, the new system eliminates the need for any internal access. “We take the product as you would give it to a QA tester, as you would eventually give it to the consumer,” he says.
“You put it on a very similar or even the same device. Then our solution plays the game by watching the screen, simulating key processes, generating a data set of everything that happens, and then hands it over to a second AI system that analyses it, flags bugs, and escalates them to a human for review.” The workflow begins with what Modl.ai calls "building game knowledge." Developers upload assets, design documents, screenshots, and other relevant materials, then converse with the AI in plain language to teach it the fundamentals of the title. "All of this is in natural language," Holmgard notes.
"We just chat with the system about our game, but we're also adding in images, or we might upload our game design documents and so on." Once the AI has a baseline understanding, developers specify the testing objectives. These can range from traditional test cases—such as verifying UI elements or checking level loading times—to more exploratory scenarios that are particularly suited to AI‑driven analysis. Holmgard emphasizes the need for human expertise at this stage: "This is where you need some human expertise to adapt the prompting and the language to the AI agent to make it do the right things." During a test run, the system records every interaction, captures video snippets as evidence, and logs detailed telemetry.
After the session, it compiles a bug report that includes textual descriptions, video clips, and raw log data. This package is then passed to a human QA specialist for validation.
"We get all the texts, and we get some video snippets that we call evidence along with all the log data and everything," Holmgard explains. "A human expert reviews it and decides what to do with it for the rest of our production." One of the most challenging aspects of automated testing is distinguishing a genuine bug from an intentional feature. The AI learns this nuance through a feedback loop: testers label each report as a bug, not a bug, or a feature, providing reasons for their decisions. Over time, this iterative feedback refines the model’s ability to make accurate judgments.
"Some of it comes from the prompting. Some of it comes from that game knowledge that you've built up around the game ahead of time," Holmgard says. "And then a good part of it also comes from feedback over time from the human testers.
Over time, the system gets attuned." Side sees the partnership as an opportunity to upskill its workforce. Rather than remaining in low‑margin testing roles, QA staff can transition into AI‑engineering positions, overseeing prompt design, data interpretation, and model training. McBride believes this shift can revitalize jobs that have migrated away from certain regions due to cost pressures. "One of the cool parts about programs like this is that we get to move our people up the value chain," he states.
"Instead of just doing testing and having a career at Side as a tester, they can become an AI engineer. It allows our people to earn more, opens new career paths, and potentially brings jobs back to countries where they have historically disappeared." The AI tool also promises to make QA careers more fulfilling by automating repetitive, monotonous tasks. McBride points out that every new build requires smoke tests, regression checks, and countless verification steps that can bog down testers and limit strategic thinking.
"By knocking these out and automating them, testers can focus on analysis, creative problem‑solving, and higher‑order tasks that help them grow," he explains. Benedikte Mikkelsen, Modl.ai’s chief product officer, echoes this sentiment: "There are some very tedious tests that testers are performing right now. You don't really need a human doing the same flow over and over again.
That person could be doing something much more valuable, like assessing the gameplay itself or doing more creative kinds of testing. That, I think, is a value proposition of using AI." Both leaders stress that AI will not replace human QA workers but will augment them, moving people up the value chain. McBride notes that testing costs remain low in some regions, making a full AI takeover impractical. Instead, providing advanced tools empowers staff to extend their careers and deliver higher‑quality outcomes.
"There's always going to be an opportunity for people to do a lot of the testing work because the price point of testing right now is so low in certain countries that it's very hard to augment it completely away," he says. "But by giving our people tool sets like this, I'm allowing them to further their career, have a longer career, and keep them for longer." Side’s philosophy frames AI as a "sliding scale" where human oversight is non‑negotiable. "There will always be a human in the loop—that's sort of our ethos," McBride affirms.
"This tool lets our people take the best of what AI can offer, reduce the burden, and also reduce mistakes. A lot of this work is tedious and prone to human error.
You take that out of the equation, and everything ratchets up a notch and becomes better." When asked about the types of games the solution currently supports, COO Oliver Deslandes admits the technology is best suited for simpler titles—puzzle games, card games, and other experiences with repeatable mechanics—rather than fast‑paced 3D open‑world or fighting games. "We have to focus on titles that are more appropriate at this stage," he says.
"Our aim is to work with clients willing to embark on this journey, even if they have demanding expectations for results and cost savings. The reality is that it's a journey, but if you are at the table now with us and maybe doing some pilots, you will see where this tech goes."