Side, a veteran 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 sets the stage for a joint effort to build an AI‑enhanced 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 been delivering testing services for many years, Modl.ai brings a fresh perspective on how AI can be harnessed to streamline and improve the QA process. "The MOU essentially fuses the strongest assets of both companies into a single, differentiated offering," explains Martin McBride, Side’s chief commercial officer. "For the games industry, one of the long‑standing holy‑grail goals has been to use AI to augment QA in a meaningful way. Nobody has cracked that fully yet, and we believe we are on the brink of doing so." Earlier AI‑driven QA tools, including earlier versions from Modl.ai, required developers to ship entire builds or even share source code with the testing vendor.
Those solutions relied on deep integration via plugins and SDKs, which created considerable friction and, as co‑founder Christoffer Holmgard notes, "became difficult over time." The new approach 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," Holmgard says. "The game runs on a device that mirrors the target hardware, our system observes the screen, simulates key inputs, records every interaction, and then passes the resulting data set to a second AI layer that flags potential bugs. That layer surfaces its findings to a human reviewer who decides what action, if any, 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 then converse with the AI in natural language to teach it the specifics of their title.
"All of this happens through plain conversation," Holmgard explains. "You can paste images, attach PDFs, or simply describe mechanics, and the AI constructs an internal model of the game." Once the AI has a baseline understanding, developers specify the testing scope. This can range from traditional test cases—such as verifying menu navigation or level loading—to novel scenarios that are especially suited to AI‑driven exploration. "Here human expertise is still crucial," Holmgard adds.
"You need to craft prompts and guide the AI so it performs the right actions and focuses on the right areas." During a test run, the system captures textual logs, short video snippets (the "evidence"), and comprehensive telemetry. These artifacts are compiled into a bug report that is handed to a senior QA specialist.
The specialist reviews the findings, confirms whether each item is truly a defect or an intended feature, and then routes the report back into the development pipeline. Holmgard points out that distinguishing bugs from intentional design choices can be subtle, and human feedback is essential for teaching the AI those nuances.
"Prompt engineering, pre‑built game knowledge, and ongoing tester feedback all combine to fine‑tune the model over time," he says. Side envisions this technology reshaping career paths within QA.
Rather than remaining in purely repetitive testing roles, staff can evolve into "AI engineers" who design prompts, interpret AI outputs, and oversee the integration of machine‑learning insights into the testing workflow. McBride believes this shift will elevate salaries, open new professional trajectories, and even bring jobs back to regions where low‑cost testing labor has previously migrated away. "When we move people up the value chain, we can re‑locate them to markets where they were once lost," he notes.
According to McBride, the AI tool also makes the day‑to‑day work of QA testers more rewarding. By automating routine smoke tests and other monotonous checks, testers are freed to engage in higher‑order analysis, strategic thinking, and creative exploration of gameplay.
"The technology lifts the burden of repetitive tasks, allowing our people to focus on the aspects of testing that truly add value," he says. Benedikte Mikkelsen, Modl.ai’s chief product officer, echoes this sentiment: "Many current tests are mind‑numbing loops that a human doesn’t need to repeat. With AI handling those, a tester can concentrate on assessing game feel, balance, or innovative testing approaches—this is the real value proposition." Both leaders stress that AI will never replace QA professionals outright. The price point for low‑cost testing in certain regions remains so low that a complete AI takeover is not yet feasible.
Instead, the technology acts as an augmentation, giving testers better tools and longer, more fulfilling careers. "There will always be a human in the loop—that’s our ethos," McBride affirms.
"The AI reduces tedious work and human error, raising the overall quality of the process." When asked about the types of games the solution currently supports, COO Oliver Deslandes admits the system is best suited for simpler titles—puzzle games, card games, or other experiences with repeatable mechanics and modest graphical demands. Fast‑paced, 3D open‑world or fighting games remain a future target as the technology matures.
"We’re focusing on projects that fit the current capabilities, and we’re looking for partners willing to embark on this journey with us," Deslandes says. "It’s a collaborative pilot phase, and as we gather data and improve the models, the range of applicable games will expand." 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 critical judgment and domain expertise that machines lack. This collaborative model promises faster turnaround times, higher accuracy, and a more satisfying career path for QA professionals, all while keeping a human eye on every decision. The six‑month MOU will serve as a proving ground for this vision, with the hope that successful pilots will pave the way for broader adoption across the gaming industry.