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 venture that will integrate Modl.ai’s AI capabilities into Side’s quality‑assurance (QA) workflow, creating a hybrid system that blends machine intelligence with human expertise. Modl.ai, a relatively new player in the gaming sector, was founded in 2018 and secured $1.7 million in seed funding two years later. While the company has already experimented with AI‑driven QA tools, earlier versions required developers to hand over complete game builds or even source code via a plugin and SDK.
This “integration‑based” approach proved cumbersome and created friction for developers, as noted by Modl.ai founder Christoffer Holmgard. The new solution, however, eliminates the need for any internal access. Instead, developers supply the same product they would eventually deliver to a QA tester or the end‑user, install it on a comparable device, and let the AI observe the game’s visual output, simulate inputs, and compile a comprehensive data set of in‑game events.
Once the raw data is collected, a second AI layer analyses it, flags potential defects, and escalates the findings to a human reviewer. Holmgard describes this as a two‑stage process: the first stage builds “game knowledge” by allowing developers to upload assets, design documents, screenshots, and other contextual information. The interaction is conducted entirely in natural language, effectively turning the AI into a conversational partner that learns the game’s mechanics and design intent.
After the AI has a solid understanding, developers specify the testing objectives—ranging from traditional test cases to novel scenarios that exploit the AI’s strengths. At this point, human insight is essential to craft prompts that guide the AI toward the desired outcomes. When a testing session—referred to by Modl.ai as a “run”—concludes, the system generates detailed bug reports that include textual descriptions, short video snippets (the “evidence”), and full log files. These artifacts are handed over to a seasoned QA specialist, who reviews the findings, validates whether an issue is truly a bug or an intended feature, and decides the next steps for the production pipeline.
Holmgard emphasizes that distinguishing bugs from features is a nuanced task that benefits from continuous feedback loops. Over time, as human testers label reports and provide rationale, the AI refines its judgment, becoming more attuned to the subtleties of game design.
Side sees this collaboration as a pathway to elevate its QA workforce. Chief Commercial Officer Martin McBride explains that the AI tool will free testers from repetitive, low‑value tasks such as smoke tests and routine verifications, allowing them to focus on strategic analysis, creative testing, and higher‑order problem solving. In practice, this shift could enable QA staff to transition into AI‑engineering roles, thereby moving up the value chain, earning higher salaries, and opening new career trajectories. McBride argues that this upskilling could also reverse the off‑shoring trend that has seen QA jobs migrate to low‑cost regions; by adding AI‑centric responsibilities, Side can justify retaining talent in higher‑cost markets.
The company’s chief operating officer, Oliver Deslandes, clarifies that the current AI solution is best suited for simpler game genres—puzzle titles, card games, and other experiences with repeatable, slower mechanics. Fast‑paced 3D open‑world or fighting games remain a longer‑term goal because they demand real‑time perception and rapid decision‑making that the present system cannot yet handle. Deslandes stresses that early adopters will likely be clients willing to pilot the technology and accept the iterative nature of its development. Modl.ai’s chief product officer, Benedikte Mikkelsen, reinforces the value proposition: many existing QA tasks are monotonous and could be automated without sacrificing quality.
By offloading these chores to AI, human testers can concentrate on evaluating gameplay feel, exploring edge cases, and conducting more imaginative tests—activities that add genuine value to the final product. Both parties agree that AI will never fully replace human QA professionals. Instead, it acts as an augmentative layer that reduces error rates, speeds up testing cycles, and elevates the overall quality of the work. McBride sums up the philosophy by describing AI as a “sliding scale”: there will always be a human in the loop, ensuring that the technology serves as a tool rather than a replacement.
This ethos underpins the partnership, aiming to combine the best of Side’s established QA processes with Modl.ai’s cutting‑edge AI research to deliver a more efficient, scalable, and satisfying testing experience for developers and gamers alike.