Side, a seasoned 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 quality‑assurance (QA) platform that leverages AI while keeping human expertise at its core. Modl.ai, a relatively new player in the gaming sector, was founded in 2018 and secured $1.7 million in seed financing two years later.
Side, by contrast, has a long history of delivering services across multiple industries. Martin McBride, Side’s chief commercial officer, says the partnership combines the strongest assets of each company into a single, differentiated offering. “One of the holy‑grail experiences for the games industry today is using AI to augment QA services,” he explains. “No one has cracked a truly effective solution yet, and we believe we are on the cusp of doing so.” Earlier AI‑driven QA tools, including earlier versions from Modl.ai, required developers to hand over full builds or even source code so the system could run tests.
That approach proved cumbersome and, as Modl.ai founder Christoffer Holmgard notes, “became difficult over time.” The new solution eliminates the need for deep integration. Instead, developers provide the product exactly as they would to a human tester or, eventually, to a consumer.
The AI runs the game on a comparable device, watches the screen, simulates key inputs, and records every observable event. A second AI layer then reviews the generated data, flags potential defects, and escalates items that merit human judgment. The workflow begins with what Modl.ai calls “building game knowledge.” Developers upload assets—artwork, design documents, even video clips—and converse with the AI using natural‑language prompts. Holmgard describes the process as a dialogue: “We just chat with the system about our game, but we also feed it images and design docs, so it builds a contextual understanding.” Once the AI has a baseline grasp of the title, developers specify the testing objectives.
These can range from traditional test cases to novel scenarios that exploit the AI’s strengths. Human insight remains essential at this stage. “You need expertise to shape the prompts and language so the AI does the right thing,” Holmgard says.
After the AI executes the defined sessions—referred to as “runs”—it compiles bug reports that include textual descriptions, short video snippets (the “evidence”), and full log data. These reports are handed to seasoned QA specialists who review, validate, and decide on the appropriate next steps for the production pipeline.
One of the trickier challenges for any automated system is distinguishing a genuine bug from an intended feature. Holmgard emphasizes that feedback loops from human testers help the AI learn these nuances. “Prompting, pre‑built game knowledge, and ongoing tester feedback all teach the system what counts as a defect and what does not,” he explains.
Over time, the AI becomes attuned to the particular design philosophy of each game. Side envisions a broader shift in the QA workforce. By giving testers the tools to automate repetitive checks, they can transition into roles that resemble AI engineering. McBride says this shift “moves our people up the value chain,” opening higher‑paying career paths and potentially repatriating jobs that have migrated to low‑cost regions.
"When repetitive, low‑skill tasks are automated, testers can focus on strategic analysis, creative testing, and gameplay evaluation," he adds. Benedikte Mikkelsen, Modl.ai’s chief product officer, echoes this sentiment: “There are very tedious tests that don’t need a human to repeat over and over. Those testers can instead assess gameplay or conduct more inventive testing, which is the real value proposition of AI.” Both executives stress that AI is not a replacement for human QA workers but a complement. McBride notes that price pressures in certain markets make it impossible to eliminate human testers entirely.
However, by equipping staff with AI‑driven tools, Side can retain talent longer, enhance job satisfaction, and reduce error rates caused by fatigue or monotony. Side’s philosophy treats AI as a “sliding scale” where human involvement never disappears. “There will always be a human in the loop—that’s our ethos,” McBride affirms. The AI handles the bulk of repetitive validation, freeing humans to intervene on complex, ambiguous issues and to provide the critical feedback that refines the system.
Regarding the types of games the platform currently supports, Oliver Deslandes, Side’s chief operating officer, is candid: the solution is best suited for simpler titles—puzzle games, card games, or other experiences with repeatable mechanics. Fast‑paced, 3‑D open‑world or fighting games remain out of scope for now.
“We’re targeting clients willing to embark on this journey with us, even if they have modest expectations at the start,” Deslandes says. He adds that pilot projects will reveal how the technology evolves and which genres can be tackled next.
In summary, the Side‑Modl.ai partnership aims to blend AI efficiency with human judgment to reshape game QA. By automating routine checks, providing richer bug documentation, and fostering new career trajectories for testers, the collaboration hopes to deliver faster, cheaper, and higher‑quality testing while preserving the nuanced decision‑making that only experienced humans can provide. The six‑month MOU will serve as a proving ground for this vision, with the potential to expand into broader markets and more complex game types as the technology matures.