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‑powered 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 financing two years later. While Side has a long history of delivering testing services to game developers, Modl.ai brings a fresh perspective on how AI can augment, rather than replace, human QA work. "The MOU effectively brings the best of what Side has and the best of what Modl.ai has together in a unique solution," explains Martin McBride, Side’s chief commercial officer.
"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 AI‑driven QA tools, including Modl.ai’s own first‑generation offering, required developers to ship full builds or even share source code so the AI could analyse the game from the inside. That approach proved cumbersome and generated friction with development teams, as the founder Christoffer Holmgard notes.
The new system eliminates the need for any internal access. Instead, developers provide the finished product exactly as they would hand it to a human tester or eventually to a consumer.
The AI runs the game on a device that mirrors the target platform, watches the screen, simulates user inputs, records every on‑screen event, and then hands the resulting data set to a second AI layer that flags potential defects. Human reviewers then decide whether each flagged item warrants action.
The first phase of the workflow is what Modl.ai calls "building game knowledge." Developers upload assets—such as sprites, level designs, or design documents—and converse with the AI in plain language. "All of this is in natural language," Holmgard explains. "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 contextual understanding of the title, the development team defines the testing objectives. These can range from traditional test cases to novel scenarios specifically crafted to leverage the AI’s strengths.
Holmgard emphasizes that human expertise is still crucial at this stage: "You need some human expertise here to adapt the prompting and the language to the AI agent to make it do the right things." During a test run—referred to by Modl.ai as a "session"—the system captures a wealth of evidence: textual logs, short video clips that illustrate the issue, and comprehensive telemetry. This bundle is passed to a senior QA specialist who reviews the findings and determines the appropriate next steps for the production pipeline. One of the persistent challenges in automated testing is distinguishing a genuine bug from an intended feature. Holmgard says that ongoing feedback from human testers helps the AI refine its judgment.
"Some of it comes from the prompting, some from the game knowledge you built up ahead of time, and a good part comes from feedback over time from the human testers," he notes. "Over time, the system gets attuned." Side envisions a future where QA professionals evolve into AI engineers, shifting the skill set up the value chain. McBride believes this transition can revitalize job markets that have seen testing roles migrate to low‑cost regions.
"Instead of just doing testing and moving up to senior tester, they can become an AI engineer," he says. "It allows our people to get paid more, opens new career paths, and potentially brings jobs back to countries where they historically left." The company also argues that AI will make QA careers more fulfilling by automating repetitive, low‑value tasks. "One of the things this tool does very well right now is that it reduces the burden of repetitive tests," McBride explains.
"Smoke tests, verification steps, and countless routine checks can bog down a tester’s workflow. By knocking these out, testers can focus on strategic analysis, creative testing, and deeper gameplay evaluation." 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 is not a wholesale replacement for human QA staff. The price point for manual testing in certain regions remains low, making a complete automation impractical. However, by equipping testers with AI‑enhanced tools, Side aims to extend their careers and keep talent engaged longer.
"There's always going to be an opportunity for people to do a lot of the testing work here because the price point of testing right now is so low in certain countries that it's very hard to augment it completely away," McBride says. "But by giving our people tool sets like this, I'm allowing them to further their career." McBride describes Side’s AI philosophy as a "sliding scale" with a human always present in the loop.
"That's sort of our ethos," he affirms. "The tool lets us take the best of what AI can offer, reduce the burden, and also reduce mistakes. Human error is inevitable; removing that variable lets the whole process ratchet up a notch." When asked about the types of games the solution currently supports, COO Oliver Deslandes is candid: the technology works best with simpler titles—puzzle games, card games, and other experiences with repeatable mechanics—rather than fast‑paced 3D open‑world adventures or fighting games.
"We have to focus on titles that are more appropriate at this stage," he says. "Clients willing to join us on this journey will see where the tech goes, and we’ll iterate together." In summary, the Side‑Modl.ai partnership aims to create a hybrid QA ecosystem where AI handles the heavy lifting of data collection and initial bug detection, while seasoned human testers provide the nuanced judgment and strategic insight that only experience can deliver. By doing so, they hope to raise the overall quality of games, empower QA professionals with new technical skills, and ultimately reshape the economics of game testing on a global scale.