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‑powered quality‑assurance (QA) platform that blends Side’s deep testing pedigree with Modl.ai’s cutting‑edge machine‑learning capabilities.
Modl.ai, a relatively new entrant to the gaming ecosystem, was founded in 2018 and secured $1.7 million in seed capital two years later. While Side brings decades of experience in delivering testing services across a range of industries, Modl.ai contributes a suite of AI tools that have, until now, required developers to hand over entire game builds or even source code for analysis. That approach, which relied on integration‑heavy plugins and SDKs, proved cumbersome and often created friction between developers and QA providers. According to Modl.ai’s founder, Christoffer Holmgard, the new system eliminates the need for any internal code access.
"We treat the product exactly as you would hand it to a QA tester—or eventually to the consumer," he explains. "The game runs on a device that mirrors the target hardware, our AI watches the screen, simulates key inputs, records everything that happens, and then passes that data to a second AI layer that flags potential bugs. That layer escalates uncertain findings to a human reviewer for final judgment." The first phase of the workflow is what Modl.ai calls "building game knowledge." Developers upload assets, design documents, screenshots, and other relevant material, then converse with the AI in plain language to teach it the nuances of their title. "All of this happens in natural language," Holmgard says.
"You can chat about gameplay mechanics, attach images, or feed in design specs, and the system gradually builds a contextual model of the game." Once the AI has a basic understanding, developers specify the testing objectives. These can range from traditional test cases—such as verifying UI elements or ensuring level loading times—to more exploratory scenarios that are better suited to AI‑driven analysis. Holmgard notes that human expertise is still essential at this stage to craft effective prompts and guide the AI toward the right actions. During a "run"—Modl.ai’s term for a testing session—the system captures a wealth of data: textual logs, video snippets that serve as evidence, and detailed telemetry.
This package is then handed to a human QA specialist, who reviews the findings, validates whether each flagged issue is truly a bug or an intended feature, and decides on the next steps for the development pipeline. One of the perennial challenges in game QA is distinguishing bugs from intentional design choices. Holmgard points out that continuous feedback from human testers helps the AI refine its judgment. "Prompt engineering, the pre‑built game knowledge, and iterative feedback all combine to tune the model over time," he says.
"When testers label an item as a bug, not a bug, or a feature, the AI learns from those annotations and becomes more accurate." Side sees this collaboration as a pathway to elevate its workforce. Chief Commercial Officer Martin McBride envisions QA staff evolving into AI engineers, thereby moving up the value chain. "Instead of a career that ends at senior tester, our people can transition into roles that command higher salaries and greater strategic impact," he explains.
"This shift also opens the possibility of bringing jobs back to regions where low‑cost testing has been outsourced, because the higher‑skill AI‑engineer positions are less price‑sensitive." McBride adds that AI will free testers from repetitive, low‑value tasks, allowing them to focus on strategic analysis and creative problem‑solving. "Smoke tests, regression checks, and other routine verifications consume a lot of time. By automating those, we let our team think more critically about gameplay balance, user experience, and other high‑impact areas," he says. This sentiment is echoed by Modl.ai’s Chief Product Officer Benedikte Mikkelsen, who notes that eliminating tedious, repeatable flows enables human testers to concentrate on assessing core gameplay and conducting innovative testing methods.
Both executives stress that AI is not a replacement for human QA talent but a complementary tool that amplifies human capabilities. McBride describes AI as a "sliding scale" where the human element is always present: "Our ethos is that there will always be a person in the loop.
The technology reduces error and monotony, raising the overall quality of the process." When asked about the types of games the solution currently supports, Side’s 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 3D open‑worlds or fighting games are still a ways off," he admits. "We’re targeting developers who are willing to pilot the system and understand that the journey will involve iterative improvement." 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 blending automation with expertise, the collaboration hopes to streamline testing workflows, enhance career prospects for QA professionals, and ultimately deliver more reliable, polished gaming experiences to consumers.