Side, a veteran services organization 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 build an AI‑powered 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 capital two years later.
While the company has already experimented with AI‑enabled QA tools, earlier versions required developers to ship entire game builds—or even share source code—so the system could run its tests. This “integration‑based” approach, which relied on plugins and SDKs, proved cumbersome and created friction for development teams, as noted by Modl.ai founder Christoffer Holmgard. The new solution, Holmgard explains, eliminates the need for any internal code access. "We treat the product exactly as you would hand it to a QA tester or ultimately to a consumer," he says.
"You install it on a device that is identical—or at least very similar—to the target platform. Our AI then plays the game, watches the screen, simulates key actions, and compiles a comprehensive data set of everything that occurs.
A second AI layer reviews that data, flags potential bugs, and escalates them to a human reviewer for final validation." The process 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 English (or any natural language) to teach it the fundamentals of the title. "We literally chat with the system about our game, feeding it images, design docs, and other context," Holmgard notes. This conversational approach helps the AI construct a mental model of the game’s mechanics, art style, and narrative flow.
Once the AI has a solid understanding, developers define the testing scope. This can range from conventional test cases—such as verifying that a menu opens correctly—to more exploratory scenarios that are specifically tailored to the strengths of the AI. "Human expertise is still crucial here," Holmgard emphasizes.
"We need to craft prompts and guide the AI so it performs the right actions and looks for the right outcomes." During a test run, the system records every interaction, capturing text logs, video snippets (referred to as "evidence"), and telemetry data. These artifacts are then handed to a human QA specialist, who reviews the findings, decides which issues merit further attention, and provides feedback to the AI. This feedback loop helps the system differentiate between genuine bugs and intentional features, a distinction that can be subtle in game development. "Over time, as testers label items as 'bug' or 'not a bug' and explain why, the AI becomes attuned to the nuances of our design philosophy," Holmgard says.
Side sees this collaboration as a catalyst for a broader shift in the QA workforce. Chief Commercial Officer Martin McBride envisions QA professionals evolving into AI engineers, moving up the value chain and gaining higher‑paid, more strategic roles.
"Instead of a career that ends at senior tester, our people can become AI engineers, which opens new career paths and potentially brings jobs back to regions that have lost them due to low‑cost labor pressures," he explains. By automating repetitive, low‑skill tasks—such as smoke testing each new build—human testers can focus on higher‑order analysis, creative testing, and gameplay assessment, leading to more fulfilling careers. Modl.ai’s Chief Product Officer Benedikte Mikkelsen echoes this sentiment, noting that many current QA tasks are monotonous and could be handled by machines.
"If you free testers from running the same flow over and over, they can spend their time on more valuable activities, like evaluating game feel or designing novel test scenarios," she says. Both sides stress that AI will not replace QA staff but will augment them. McBride points out that testing costs remain low in certain regions, making a full AI takeover impractical. However, by equipping testers with sophisticated tools, Side can extend their careers, improve retention, and elevate overall quality.
"Our ethos is a sliding scale of AI—there will always be a human in the loop," he states. "The technology reduces tedious work and human error, allowing us to raise the bar on quality. Regarding applicability, Side’s Chief Operating Officer Oliver Deslandes admits that the current iteration works best with simpler titles—puzzle games, card games, and other experiences with repeatable mechanics—rather than fast‑paced 3D open‑world or fighting games.
"We are targeting clients who are willing to join us on this journey, even if they have modest expectations at first," Deslandes says. "As the platform matures, we anticipate expanding to more complex genres." In summary, the Side‑Modl.ai partnership aims to create a hybrid QA ecosystem where AI handles high‑volume, repetitive testing while seasoned human experts provide strategic oversight and continuous training for the algorithms. The six‑month MOU will serve as a proving ground for this approach, with the ultimate goal of delivering faster, cheaper, and higher‑quality game releases while reshaping the career landscape for QA professionals worldwide.