Side, a seasoned services provider, has entered into a six‑month memorandum of understanding (MOU) with Denmark‑based artificial‑intelligence specialist Modl.ai to co‑develop an AI‑powered quality‑assurance platform for video games. The agreement binds the two companies together for half a year, during which they will integrate Side’s extensive QA expertise with Modl.ai’s cutting‑edge machine‑learning technology to create a hybrid testing solution that keeps a human in the loop. Side, previously known as PTW, has been a fixture in the outsourcing and testing market for many years.
Modl.ai, by contrast, is a newer player that launched in 2018 and secured $1.7 million in seed capital two years later. According to Martin McBride, Side’s chief commercial officer, the partnership “marriage[s] the best of Side’s testing know‑how with the most advanced AI capabilities Modl.ai has built.” He adds that the gaming industry has long chased a “holy‑grail” AI system that can genuinely augment QA services, and that this joint effort could finally deliver that promise. Earlier AI‑based QA tools, including earlier versions from Modl.ai, required developers to hand over entire game builds or even source code so the AI could analyse the product.
That approach proved cumbersome, creating friction for studios that needed to protect intellectual property and manage large data transfers. Founder Christoffer Holmgard explains that the new solution eliminates the need for deep integration. Instead, the game is delivered to the AI exactly as a tester or consumer would receive it—installed on a comparable device, run, and observed.
The system works by capturing the on‑screen activity, simulating player inputs, and compiling a comprehensive data set of every event that occurs. A second AI layer then reviews this data, flags anomalies, and escalates potential bugs to a human reviewer for validation. Holmgard describes the first phase as “building game knowledge.” Developers upload assets, design documents, screenshots, and other relevant material, and then converse with the AI in natural language to teach it the game’s mechanics, story beats, and visual style.
Once the AI has a solid understanding, the development team defines the test scenarios they wish to explore. These can range from traditional test cases—such as verifying menu navigation or level loading—to more exploratory tasks that are specially crafted to leverage the AI’s pattern‑recognition abilities.
Holmgard stresses that human expertise is still required at this stage to phrase prompts correctly and guide the AI toward meaningful actions. When a test run (or “session,” as Modl.ai calls it) completes, the platform generates a bug report that includes textual descriptions, short video clips serving as evidence, and the full log of system events. These reports are handed to seasoned QA specialists, who assess the findings and decide how to proceed within the production pipeline.
One of the persistent challenges in game QA is distinguishing a genuine defect from an intentional feature. Holmgard notes that continuous feedback from human testers helps the AI refine its judgment over time, gradually learning which patterns constitute bugs and which are part of the game’s design. Side sees this collaboration as a catalyst for reshaping career paths within its organization. McBride envisions QA staff evolving into “AI engineers,” moving up the value chain and gaining higher‑paying, more strategic roles.
By automating repetitive, low‑skill tasks—such as smoke tests for each new build—testers can focus on higher‑order analysis, creative exploration, and gameplay assessment. This shift not only promises more fulfilling work for employees but also opens the possibility of bringing jobs back to regions where they have previously migrated due to cost pressures. Benedikte Mikkelsen, Modl.ai’s chief product officer, echoes this sentiment, pointing out that many current tests are monotonous and could be handled by a machine. Freeing humans from those chores allows them to concentrate on evaluating the player experience, designing novel test scenarios, and applying their creative instincts—activities that add real value to a game’s final quality.
Both executives are clear that AI will not replace QA professionals. McBride emphasizes that the price point for manual testing in some low‑cost markets remains so low that a complete AI takeover is unrealistic. Instead, the technology acts as an enhancer, lifting testers’ capabilities and extending their careers. He describes AI as a “sliding scale”: the more sophisticated the AI tools become, the higher the proportion of work that can be automated, yet a human will always remain in the decision‑making loop.
This philosophy, he says, is the core ethos of Side. When asked about the types of games the system can handle today, COO Oliver Deslandes admits that the current focus is on simpler titles—puzzle games, card games, and other experiences with repeatable mechanics. Fast‑paced 3D open‑world or fighting games present greater technical challenges and will be addressed in later phases.
The company is seeking early adopters willing to pilot the technology, acknowledging that results may vary based on the client’s expectations and budget constraints. In summary, the Side‑Modl.ai partnership aims to blend human expertise with AI efficiency, creating a QA workflow that reduces tedious manual work, improves bug detection accuracy, and opens new professional avenues for testers. While the technology is still maturing and best suited to less complex games at this stage, both firms view the collaboration as a stepping stone toward a future where AI and human insight work hand‑in‑hand to deliver higher‑quality gaming experiences.