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‑driven quality‑assurance (QA) platform that blends the strengths of each partner. Modl.ai, although a relatively new name in the gaming sector, was founded in 2018 and secured $1.7 million in seed financing two years later. Since then, the company has been experimenting with AI tools that can assist QA teams, but early versions required developers to hand over full game builds or even source code so the AI could analyse the product.
That approach proved cumbersome, creating friction for studios and limiting scalability, as Modl.ai’s founder Christoffer Holmgard acknowledges. The new solution, Holmgard explains, eliminates the need for any deep integration. "We treat the game exactly as you would hand it to a human tester or eventually to a consumer," he says. "You load it onto a device that mirrors the target hardware, and our system runs the game, watches the screen, simulates inputs, and records everything that happens.
A second AI then reviews that data, flags potential defects, and escalates the findings to a human reviewer for final validation." The first phase of the workflow is what Modl.ai calls building "game knowledge." Developers upload assets—artwork, design documents, level layouts—and converse with the AI using natural‑language prompts. The system ingests these inputs, creating a semantic model of the game’s mechanics, rules, and visual style. This model becomes the foundation for later testing activities. Once the AI has a basic understanding, developers define the testing objectives.
These can range from traditional test cases—such as verifying that a menu opens correctly—to more exploratory scenarios that are specifically crafted to leverage the AI’s pattern‑recognition abilities. Holmgard notes that human expertise is still essential at this stage to phrase prompts effectively and guide the AI toward the most relevant behaviours. During a "run"—Modl.ai’s term for a testing session—the platform executes the defined scenarios, captures video snippets, logs console output, and records telemetry data.
The AI then synthesises this information into a bug report that includes textual descriptions, visual evidence, and the raw logs that led to the detection. These reports are handed off to a human QA specialist, who reviews the findings, decides whether they constitute genuine defects, and determines the appropriate remediation steps. One of the persistent challenges in game QA is distinguishing a bug from an intentional feature.
Holmgard emphasizes that ongoing feedback from human testers helps the AI refine its judgment. "When testers label a finding as a bug, not a bug, or explain why it’s acceptable, the system learns those nuances over time and becomes better calibrated," he says.
Side sees the partnership as a way to elevate its workforce. Chief Commercial Officer Martin McBride explains that the AI tool can free testers from repetitive, low‑value tasks—such as smoke testing every new build—allowing them to focus on strategic analysis, creative testing, and ultimately, AI engineering.
"Instead of a career path that ends at senior tester, our people can evolve into AI engineers, command higher salaries, and even bring jobs back to regions where they have previously disappeared due to cost pressures," McBride states. The shift also promises a more satisfying professional experience. By automating the monotonous portions of QA, testers can engage in higher‑order problem solving, contribute to gameplay assessment, and develop skills that are transferable across the industry. Benedikte Mikkelsen, Modl.ai’s Chief Product Officer, adds that eliminating tedious repeatable flows lets humans apply their expertise to areas that truly require human intuition, such as evaluating game balance or crafting novel test scenarios.
Both companies stress that AI will not replace QA personnel but will act as an enabler that moves them up the value chain. McBride notes that in many low‑cost regions, testing rates are so low that fully automating the process is economically infeasible.
Providing AI‑augmented tools, however, lets those same workers remain relevant, extend their careers, and command better compensation. Side’s philosophy regarding AI is described as a "sliding scale"—a spectrum where automation increases but a human remains in the loop at all times. "That’s our ethos," McBride affirms.
"The tool reduces tedious work and human error, raising the overall quality of the output while still relying on expert judgment for the final decision." When asked about the types of games the platform can currently handle, Chief Operating Officer Oliver Deslandes is candid that the technology is best suited for simpler titles—puzzle games, card games, and other experiences with repeatable mechanics. Fast‑paced, graphically intensive 3D open‑world or fighting games are still a ways off. "We’re focusing on projects where the mechanics are predictable enough for the AI to learn effectively," Deslandes explains.
"Clients who are willing to pilot the technology with us will help shape its evolution, and as we gather more data, we’ll expand to more complex genres." In summary, the Side‑Modl.ai collaboration aims to create a hybrid QA ecosystem where AI handles bulk, repetitive testing while seasoned human analysts interpret results, provide feedback, and guide the system’s continuous improvement. The six‑month MOU will serve as a proving ground for this approach, with the ultimate goal of delivering faster, cheaper, and higher‑quality testing services to game developers worldwide, while simultaneously upskilling the QA workforce and preserving human oversight throughout the process.