Side, a seasoned 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 venture that will integrate Modl.ai’s AI capabilities into Side’s quality‑assurance (QA) processes, creating a hybrid system that blends machine efficiency with human expertise. 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 the company has already experimented with AI‑driven QA tools, earlier versions required developers to hand over entire game builds or even source code. Those “integration‑based” solutions, which relied on plugins and SDKs, proved cumbersome and often created friction with development teams, as noted by Modl.ai founder Christoffer Holmgard. The newly announced platform eliminates the need for deep internal access.
Holmgard explains that the system treats the game exactly as a human tester would receive it—delivered on a device that mirrors the end‑user’s hardware. The AI then runs the game, watches the screen, simulates inputs, and records every interaction. A second AI layer analyses the generated data, flags potential defects, and escalates them to a human reviewer for final validation. The first phase of the workflow is called “building game knowledge.” Developers upload assets, design documents, screenshots, and other relevant material, and then converse with the AI using natural‑language prompts.
This dialogue helps the system form a contextual understanding of the title, its mechanics, and its intended experience. Once this knowledge base is established, developers specify the testing scope—ranging from traditional test cases to novel scenarios that are particularly suited to AI‑driven exploration. Holmgard stresses that human input remains essential during the prompting stage.
“You need expertise to shape the language and guide the AI toward the right actions,” he says. After the AI executes the defined sessions—referred to as “runs”—it produces comprehensive bug reports. These reports include textual descriptions, short video clips as evidence, and full log files. The output is then handed to a seasoned QA specialist, who reviews the findings, decides which issues merit further action, and feeds feedback back into the system.
One of the most challenging aspects for an automated tester is distinguishing a genuine bug from an intentional feature. Holmgard notes that continuous feedback from human testers refines the AI’s judgment over time. As the system receives confirmations—“this is a bug,” “this is not a bug,” or “this is a design choice”—its predictive models become increasingly attuned to the nuances of game design. Side sees this collaboration as a pathway 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 linear career that ends at senior tester, our people can become AI engineers, earn higher salaries, and open new career trajectories,” he explains.
This shift could also reverse the off‑shoring trend that has seen many low‑cost testing jobs disappear from certain regions; by adding AI‑centric responsibilities, Side hopes to repatriate talent to markets where testing costs have historically been prohibitive. McBride adds that AI will free testers from repetitive, monotonous tasks, allowing them to focus on strategic analysis and creative problem‑solving. “The tool handles smoke tests and routine verifications, so our staff can think more strategically and grow professionally,” he says.
Benedikte Mikkelsen, Modl.ai’s Chief Product Officer, echoes this sentiment, noting that many current tests are tedious and could be automated, letting humans concentrate on gameplay assessment and innovative testing approaches. Both executives are clear that AI is not a replacement for human QA but a complementary asset.
McBride describes AI as a “sliding scale” where a human remains in the loop at every stage. This philosophy underpins Side’s ethos: leveraging AI to reduce error‑prone, repetitive work while preserving the critical judgment that only experienced testers can provide. Regarding applicability, Side’s Chief Operating Officer Oliver Deslandes cautions that the technology is presently best suited for simpler titles—puzzle games, card games, and other experiences with repeatable mechanics. High‑speed, complex 3D open‑world or fighting games remain a longer‑term goal.
Deslandes emphasizes that early adopters should be willing to pilot the solution and accept that the technology will evolve alongside their feedback. In summary, the Side‑Modl.ai partnership aims to create a hybrid QA ecosystem where AI handles data‑intensive, repetitive testing while human experts provide direction, validation, and nuanced decision‑making. The six‑month MOU will serve as a proving ground for this approach, potentially reshaping how the gaming industry conducts quality assurance and redefining career pathways for QA professionals worldwide.