Side, a seasoned services provider formerly known as PTW, has entered into a six‑month memorandum of understanding (MOU) with Danish 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 the strengths of both organisations. 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 Side brings decades of experience in delivering testing and support services, Modl.ai contributes cutting‑edge machine‑learning expertise. "The MOU essentially fuses the best of Side’s service pedigree with Modl.ai’s AI know‑how into a truly differentiated solution," explains Martin McBride, Side’s chief commercial officer. "Creating a scalable AI‑enhanced QA offering has been a holy‑grail for the games industry, and we believe we have finally cracked it." Earlier AI‑driven QA tools, including Modl.ai’s own prior version, required developers to ship entire builds—or even source code—into a testing environment.
That approach relied on deep integration via plugins and SDKs, generating considerable friction and, as founder Christoffer Holmgard notes, becoming unsustainable over time. The new system eliminates the need for any internal access. "We treat the product exactly as you would hand it to a human tester or eventually to the consumer," Holmgard says. "You load it onto a comparable device, our AI watches the screen, simulates key inputs, records every observable event, and then hands the data to a second AI layer that flags potential bugs and escalates them for human review." The process begins with what Modl.ai calls "building game knowledge." Developers upload assets, design documents, screenshots, or even converse with the AI in plain language to teach the system the fundamentals of their title.
"All interactions are natural‑language based," Holmgard explains. "You can chat, paste images, feed design docs—everything helps the AI form a mental model of the game." Once the AI has a baseline understanding, developers specify the testing scope.
This can range from traditional test cases to novel scenarios that play to the strengths of the AI engine. Holmgard stresses that human expertise is still crucial at this stage: "Crafting effective prompts and guiding the AI’s language requires domain knowledge, so testers must shape the instructions to get the right outcomes." During a test run, the system captures textual logs, video snippets (referred to as "evidence"), and comprehensive telemetry. These artefacts are compiled into bug reports that are handed over to a human QA specialist for validation. "The specialist reviews the findings, decides which issues merit action, and feeds that feedback back into the AI," Holmgard says.
This feedback loop helps the AI distinguish between genuine defects and intentional features—a nuanced judgment that pure automation struggles with. Over time, the AI becomes attuned to the particular design philosophy of each studio, learning from repeated human annotations such as "this is a bug," "this is not a bug," or "this is a feature with a known rationale." The cumulative effect is a system that gradually reduces false positives and improves detection accuracy. Side envisions a broader transformation for its workforce. By upskilling QA staff into AI‑engineer roles, the company hopes to shift the value chain upward, offering higher‑paying, more strategic positions.
"Instead of a linear career path from junior tester to senior tester, we can now open routes to AI engineering," McBride notes. "That not only raises salaries but also creates opportunities to bring jobs back to regions that lost them due to low‑cost testing models." The AI tool also promises to make existing QA roles more fulfilling.
Repetitive smoke tests and routine verifications, which consume a large portion of a tester’s day, can be offloaded to the machine. "When the AI handles the boring, repetitive work, our people can focus on strategic analysis, gameplay assessment, and creative testing," McBride adds.
Benedikte Mikkelsen, Modl.ai’s chief product officer, echoes this sentiment: "Automating tedious flows frees humans to evaluate core gameplay and explore innovative test ideas, which is the real value proposition of AI in QA." Both leaders are clear that AI will not replace testers but will augment them. "Testing costs are still low in some regions, making a full AI takeover impractical," McBride says.
"Providing our staff with powerful tools lets them extend their careers, stay relevant, and move up the value chain, which in turn helps us retain talent longer." Side’s philosophy treats AI as a sliding scale rather than an all‑or‑nothing solution. "There will always be a human in the loop—that’s our ethos," McBride emphasizes. By combining AI efficiency with human judgment, the partnership aims to reduce errors, cut down on tedious work, and raise overall quality. When asked about the types of games the system can currently handle, COO Oliver Deslandes admits the technology is best suited for simpler titles—puzzle games, card games, and other experiences with repeatable mechanics.
Fast‑paced 3D open‑world or fighting games remain a future goal. "We’re focusing on projects that align with the AI’s present capabilities while we continue to refine the platform.
Early adopters willing to pilot the solution will help shape its evolution," Deslandes concludes. In summary, the Side‑Modl.ai collaboration seeks to create a hybrid QA workflow where AI handles bulk, repetitive testing and humans provide the critical insight and decision‑making that only experience can deliver.
The six‑month MOU will serve as a proving ground for this vision, potentially redefining how the gaming industry approaches quality assurance.