Side, a veteran services provider formerly known as PTW, has entered into a six‑month memorandum of understanding (MOU) with Denmark‑based artificial‑intelligence specialist Modl.ai. The agreement sets the stage for a joint effort to create a hybrid, AI‑driven quality‑assurance (QA) platform that blends automation with human oversight.
Modl.ai, a relatively new entrant to the gaming ecosystem, was founded in 2018 and secured $1.7 million in seed financing two years later. Side, by contrast, has decades of experience delivering outsourced services across a range of industries. Martin McBride, Side’s chief commercial officer, summed up the partnership: “The MOU brings together the best of Side’s service expertise and Modl.ai’s AI technology into a unique solution.
The industry’s holy‑grail has been an AI‑enhanced QA offering that truly augments human testers. We believe we have finally cracked that code.” Earlier attempts at AI‑enabled QA required developers to hand over complete game builds—or even source code—to the testing firm. Modl.ai’s original offering relied on an integration plug‑in and SDK, forcing developers to expose internal assets. This approach generated significant friction and, as co‑founder Christoffer Holmgard admits, “became difficult over time.” The new system eliminates the need for deep integration.
Holmgard explains, “We treat the product exactly as you would hand it to a QA tester or eventually to a consumer. You load the game onto a device that mirrors the target hardware, and our AI watches the screen, simulates key inputs, records everything that happens, and then hands the data to a second AI layer that flags potential bugs. That layer then escalates the findings to a human for validation.” The first phase of the workflow is what Modl.ai calls “building game knowledge.” Developers upload assets, design documents, screenshots, or any other relevant material and converse with the AI in plain language. “All interactions are natural‑language based,” Holmgard notes.
“You can chat about gameplay mechanics, feed the system images, or attach design specs, and the AI gradually builds an internal model of your game.” Once the AI has a baseline understanding, developers specify the testing objectives. These can range from classic test‑case scenarios to novel, AI‑friendly challenges. Holmgard stresses the importance of human expertise at this stage: “You need skilled testers to craft prompts that guide the AI correctly. The quality of the AI’s output depends heavily on how well you phrase the instructions.” During a test run—referred to by Modl.ai as a “session”—the system records textual logs, video snippets (the so‑called “evidence”), and comprehensive telemetry.
This bundle is then passed to a human QA specialist, who reviews the findings and decides the appropriate course of action for the development pipeline. One persistent difficulty for automated testing is distinguishing a genuine bug from an intentional feature.
Holmgard explains that continuous feedback from human testers helps the AI refine its judgment. “Prompt engineering, pre‑built game knowledge, and iterative feedback all teach the system to recognize when something is a design choice versus an error.
Over time the AI becomes attuned to the nuances of a particular title.” Side envisions this collaboration reshaping the career trajectory of QA personnel. Rather than remaining in repetitive testing roles, staff can evolve into AI engineers who design prompts, interpret AI outputs, and fine‑tune models. McBride elaborates, “Our people can move up the value chain—from junior tester to senior tester, and eventually to AI engineer.
That progression not only raises salaries but also opens new career paths and even allows us to bring jobs back to regions where low‑cost testing had previously migrated.” According to McBride, AI should free testers from monotonous chores, enabling them to focus on strategic analysis and creative problem‑solving. “Every new build triggers smoke tests and countless verification steps that bog down a tester’s workflow. By automating those repetitive tasks, we let our staff think more strategically and engage in higher‑level analysis, making their jobs more fulfilling.” Benedikte Mikkelsen, Modl.ai’s chief product officer, echoes this sentiment: “Many current tests are mind‑numbingly tedious. You don’t need a human to repeat the same flow thousands of times.
Instead, they can concentrate on assessing gameplay feel or performing exploratory testing—activities that truly add value.” Both leaders stress that AI will never replace human QA workers; rather, it will augment them. McBride points out that testing costs remain low in certain regions, making a full AI takeover impractical. “Providing our teams with these tools extends their careers, elevates their skill sets, and keeps them engaged longer,” he says. “Our philosophy is a sliding scale—AI assists, but a human is always in the loop.” Side’s chief operating officer Oliver Deslandes adds a note of realism about the current scope of the technology.
At present, the AI works best with simpler titles—puzzle games, card games, or other experiences with repeatable mechanics—rather than fast‑paced 3D open‑world adventures or fighting games. “We’re focusing on titles where the mechanics are predictable enough for the AI to learn quickly,” Deslandes explains. “Clients willing to pilot the technology with us will help shape its evolution and eventually expand its applicability.” In summary, the Side‑Modl.ai partnership aims to deliver an AI‑enhanced QA platform that respects the need for human judgment while automating the most labor‑intensive aspects of testing.
By combining Side’s deep service expertise with Modl.ai’s cutting‑edge AI, the collaboration aspires to create a more efficient, cost‑effective, and satisfying QA process for game developers worldwide.