Side, a seasoned services provider formerly known as PTW, has entered into a six‑month memorandum of understanding (MOU) with Denmark‑based artificial‑intelligence specialist Modl.ai. The agreement sets the stage for a joint effort to build an AI‑augmented quality‑assurance (QA) platform that blends Side’s deep testing expertise 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 funding two years later.
While the startup has already experimented with AI‑driven QA tools, earlier versions required developers to ship full builds or even share source code via plugins and SDKs. That approach created considerable friction, as developers were reluctant to expose internal assets and the integration process grew cumbersome over time, according to founder Christoffer Holmgard. The new solution, Holmgard explains, eliminates the need for any internal access. "We treat the product exactly as you would hand it to a QA tester or eventually to a consumer," he says.
"You install it on a device that is identical—or at least very similar—to the target hardware. Our system then runs the game, watches the screen, simulates key actions, records everything that happens, and passes that data to a second AI layer that flags potential bugs.
That layer escalates the findings to a human reviewer who decides whether any action is required." The first phase of the workflow is what Modl.ai calls building "game knowledge." Developers upload assets, design documents, screenshots, or even short video clips and converse with the AI in natural language. The system gradually constructs an understanding of the game's mechanics, visual style, and narrative context. "All of this happens through a chat‑like interface," Holmgard notes. "You can ask the AI about a particular level, feed it images, or provide design specs, and it assimilates that information into a coherent model of the game." Once the AI has a solid grasp of the title, developers define the testing objectives.
These can range from conventional test cases—such as verifying UI elements or checking collision detection—to more exploratory scenarios that are specifically crafted to leverage the AI’s strengths. "Here you need human expertise to phrase the prompts correctly and guide the AI toward the right actions," Holmgard adds. "The quality of the prompts directly influences the relevance of the generated tests." During a test run, the system captures a wealth of data: textual logs, video snippets that serve as evidence, and comprehensive telemetry. This package is then handed over to a human QA specialist.
The specialist reviews the findings, confirms whether each flagged issue is truly a defect or an intended feature, and decides the next steps in the production pipeline. "Distinguishing a bug from a feature can be subtle," Holmgard says. "Feedback from human testers helps the AI learn those nuances over time, refining its judgment with each iteration." Side sees this collaboration as a way to elevate its workforce. Chief Commercial Officer Martin McBride envisions QA staff transitioning into AI‑engineer roles, thereby moving up the value chain.
"Instead of a career path that ends at senior tester, our people can become AI engineers, earning higher salaries and opening new career trajectories," he explains. "This also gives us the chance to bring jobs back to regions where they have disappeared because of low‑cost labor pressures. When the work becomes higher‑value, it can be located in higher‑cost markets again." McBride also stresses that AI is intended to make QA careers more rewarding, not to replace humans. Repetitive, low‑level tasks—such as smoke testing each new build—are prime candidates for automation.
By offloading those chores, testers can focus on strategic analysis, creative testing, and deeper gameplay evaluation. "The tool reduces the burden of mundane tests, allowing our people to think more strategically and grow professionally," McBride says.
Benedikte Mikkelsen, Modl.ai’s Chief Product Officer, echoes this sentiment: "Many current tests are extremely tedious, requiring a human to repeat the same flow over and over. With AI handling those routines, testers can concentrate on higher‑order activities like assessing game feel or devising novel test scenarios. That’s the real value proposition of AI in QA." Both executives agree that AI will never fully replace QA professionals.
The price of manual testing in certain low‑cost regions remains so low that a complete AI takeover is economically unrealistic. Instead, the partnership aims to provide tools that augment human workers, extending their careers and enhancing productivity. "There will always be a human in the loop—that’s our ethos," McBride asserts. "AI helps us cut down errors and repetitive effort, raising the overall quality of the process." Regarding the types of games the system can handle today, Side’s Chief Operating Officer Oliver Deslandes is candid: the technology currently excels with simpler titles—puzzle games, card games, and other experiences with repeatable mechanics.
Fast‑paced, complex 3D open‑world or fighting games remain a longer‑term goal. "We’re focusing on games that are not too rapid, where the AI can reliably observe and interact," Deslandes explains. "Clients willing to pilot this technology with us will help shape its evolution, and as the AI matures, we’ll expand to more demanding genres." In summary, the Side‑Modl.ai partnership aims to create a hybrid QA ecosystem where AI handles the grunt work, human experts provide strategic insight, and both parties benefit from a more efficient, higher‑value workflow.
The six‑month MOU will serve as a proving ground for this vision, with the potential to reshape how quality assurance is performed across the gaming industry.