Side, a seasoned services provider formerly known as PTW, has entered into a six‑month memorandum of understanding (MOU) with the Danish artificial‑intelligence startup Modl.ai. The partnership is designed to create a joint AI‑powered quality‑assurance (QA) platform that blends Side’s deep testing expertise with Modl.ai’s emerging AI technologies. Modl.ai, founded in 2018, raised $1.7 million in seed capital two years later and has been positioning itself as an innovator in the games‑testing arena. According to Martin McBride, Side’s chief commercial officer, the MOU “effectively brings together the best of what Side has and the best of what Modl.ai has into a unique solution.” He adds that the gaming industry has long been searching for a "holy‑grail" AI system that can genuinely augment QA services, and Side believes this collaboration may finally deliver that breakthrough.
Earlier AI‑driven QA tools, including Modl.ai’s first generation, required developers to ship full builds—or even source code—into a testing environment. Those solutions relied on integration plugins and SDKs, creating friction and scalability problems that the companies acknowledge were "difficult over time," says Modl.ai founder Christoffer Holmgard.
The new approach eliminates the need for any internal access to the game’s code base. Holmgard explains the workflow: "We take the product exactly as you would hand it to a QA tester or eventually to a consumer. You run it on a device that is identical or very similar to the target hardware. Our system then plays the game, watches the screen, simulates key inputs, records everything that happens, and passes that data to a second AI layer that flags bugs, escalates them to a human reviewer, and asks whether they merit action." The first phase of the process is what Modl.ai calls building "game knowledge." Developers upload assets, design documents, screenshots, and even converse with the AI in natural language to teach it the context and mechanics of their title.
Holmgard notes that this conversational training can include images and textual documentation, allowing the AI to develop a nuanced understanding of the game world. Once the AI has a baseline model, developers specify the test scenarios they want to run. These can range from traditional test cases—such as verifying UI elements or level loading—to novel, AI‑friendly challenges that exploit the system’s pattern‑recognition capabilities. "Human expertise is still required to craft the right prompts and guide the AI agent toward the intended actions," Holmgard emphasizes.
During a test run, the system generates comprehensive bug reports that include textual descriptions, short video clips (referred to as "evidence"), and full log data. These artifacts are handed over to a human QA specialist for review.
The specialist decides the appropriate response, prioritizes the findings, and integrates them into the broader production pipeline. One of the persistent challenges in automated testing is distinguishing a genuine bug from an intentional feature. Holmgard points out that feedback loops from human testers are crucial for teaching the AI these subtleties. "Prompt engineering, pre‑built game knowledge, and ongoing human feedback all combine to fine‑tune the model over time," he says.
As testers label findings as "bug," "not a bug," or "expected behavior," the AI gradually learns to make more accurate judgments. Side envisions a future where QA personnel evolve into AI engineers. By equipping testers with sophisticated AI tools, the company hopes to shift their roles up the value chain, offering higher‑paying, more strategic positions.
McBride explains, "Instead of a linear career that ends at senior tester, our staff can become AI engineers, which opens new career paths, higher salaries, and the possibility of bringing jobs back to regions where low‑cost testing has been outsourced." According to McBride, AI also promises a more fulfilling work experience for QA staff. Repetitive smoke tests and routine verifications consume a large portion of a tester’s day, leaving little room for creative problem‑solving.
By automating those mundane tasks, testers can focus on strategic analysis, gameplay assessment, and higher‑level quality decisions. "The tool reduces the burden of repetitive tests, allowing our people to think more strategically and grow their careers," he notes. Benedikte Mikkelsen, Modl.ai’s chief product officer, echoes this sentiment: "Many current tests are tedious and involve the same flow over and over. An AI can handle those, freeing humans to evaluate gameplay, explore edge cases, and conduct more inventive testing.
That’s the core value proposition of AI in QA." Both leaders stress that AI will not replace human QA workers but will augment them. McBride warns that testing costs remain low in certain regions, making a complete AI takeover impractical for now.
However, by providing advanced toolsets, Side can retain talent longer, upskill its workforce, and improve overall testing quality. The partnership also reflects Side’s broader philosophy that AI operates on a "sliding scale"—a spectrum where human involvement is always present to some degree. "There will always be a human in the loop; that’s our ethos," McBride asserts. By removing human error from repetitive tasks, the combined system can achieve higher consistency and fewer mistakes.
When asked about the types of games the solution currently supports, COO Oliver Deslandes admits 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 remain a longer‑term goal.
"We’re focusing on titles where the AI can demonstrate value now, while we continue to refine the platform for more complex experiences," he explains. Deslandes adds that the journey is collaborative: "Clients willing to pilot the solution with us will see how the technology evolves. It’s a partnership, and the results will shape the next iteration of the AI system." In summary, the Side‑Modl.ai MOU marks a strategic effort to blend seasoned QA expertise with cutting‑edge AI, aiming to reduce repetitive workload, enhance bug detection accuracy, and create new career pathways for testers. While the technology is currently geared toward less complex games, both companies view the collaboration as a stepping stone toward broader, more sophisticated AI‑driven quality assurance across the gaming industry.