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 binds the two companies to collaborate on building a next‑generation, AI‑enhanced quality‑assurance (QA) platform for the gaming industry. Modl.ai, a relatively new entrant to the games market, was founded in 2018 and secured $1.7 million in seed funding two years later.
Side, on the other hand, brings decades of experience in delivering testing and support services across multiple sectors. "The MOU essentially fuses the strongest assets of Side and Modl.ai into a single, differentiated offering," explains Martin McBride, Side’s chief commercial officer. "For the games sector, the holy‑grail has been an AI‑driven approach that genuinely augments QA. Nobody has cracked it yet – we believe we have a viable path forward." Historically, AI‑enabled QA tools required developers to hand over full game builds or even source code so that the AI could analyse the product.
Modl.ai’s earlier solution relied on an integration model involving a plugin and software development kit (SDK), which proved cumbersome and created friction for developers. "It became difficult to scale," admits founder Christoffer Holmgard. The new system, however, eliminates the need for any internal access. "We treat the game exactly as you would hand it to a human tester or eventually to a consumer," Holmgard says.
"You load it onto a comparable device, our AI runs the game by watching the screen, simulating key inputs, and generating a comprehensive data set of everything that happens. A second AI layer then reviews that data, flags potential bugs, and escalates them to a human for validation." The first phase of the workflow is what Modl.ai calls "building game knowledge." Developers upload assets—such as art, level designs, or design documents—and converse with the AI in natural language. "We simply chat with the system about our game, supplementing the dialogue with images or design docs," Holmgard explains.
This conversational approach helps the AI construct a contextual understanding of the title, which later informs test generation. Once the AI has a baseline understanding, developers specify the testing objectives. These can range from traditional test cases to novel scenarios that are better suited to AI interpretation.
"Human expertise is still required to craft the right prompts and guide the AI agent toward the desired outcomes," Holmgard notes. The AI then executes the defined sessions—referred to as "runs"—and produces bug reports enriched with textual descriptions, video snippets (the "evidence"), and full log data. These reports are handed to seasoned QA specialists who review the findings and decide on the appropriate course of action for the production pipeline. A key challenge for any automated system is distinguishing a genuine defect from an intended feature.
Holmgard points out that continuous feedback from human testers refines the AI’s judgment. "Prompt engineering, the pre‑built game knowledge, and iterative human feedback all combine to tune the system over time," he says.
Side envisions a future where QA personnel evolve into AI engineers, shifting the skill set up the value chain. "Instead of a linear career from junior tester to senior tester, our staff can transition into roles that involve designing prompts, interpreting AI outputs, and improving the underlying models," McBride explains. This shift not only promises higher salaries but also creates new career pathways that could bring jobs back to regions where low‑cost testing labor has previously migrated away.
The AI tool also aims to make QA work more rewarding by automating repetitive, low‑value tasks. "Every new build triggers smoke tests, regression checks, and countless verification steps that can bog down testers," McBride observes.
"By offloading these routine activities to the AI, our people can focus on strategic analysis, gameplay evaluation, and creative testing, leading to a more fulfilling career trajectory." Benedikte Mikkelsen, Modl.ai’s chief product officer, echoes this sentiment: "Many current tests are monotonous and can be executed by a machine without sacrificing quality. This frees human testers to concentrate on higher‑order tasks like assessing game feel or devising innovative test scenarios, which is the real value proposition of AI in QA." Both leaders stress that AI is not a replacement for human QA but a catalyst for upskilling.
McBride notes that the economics of testing in certain low‑cost regions make a full AI takeover impractical at present. "By equipping our staff with these tools, we extend their careers, raise their earning potential, and retain talent longer," he says. He further describes Side’s philosophy as a "sliding scale" of AI involvement: "There will always be a human in the loop—that’s our ethos. The AI reduces tedious work and human error, allowing the overall process to operate at a higher level of quality." When asked about the types of games the solution currently supports, COO 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‑world or fighting games are still a ways off. We’re focusing on titles where the AI can reliably interpret screen output and generate meaningful test data," he explains.
Deslandes adds that early adopters will likely be partners willing to pilot the system and help shape its evolution, acknowledging that the journey is iterative and collaborative. In summary, the Side‑Modl.ai partnership aims to blend human expertise with cutting‑edge AI to streamline game QA, create new professional pathways, and ultimately deliver higher‑quality gaming experiences. The six‑month MOU marks the first step toward a future where AI handles the grunt work while humans steer strategy, creativity, and nuanced decision‑making throughout the testing lifecycle.