Side, a seasoned 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 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 efficiency with human insight. 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 been experimenting with AI‑driven testing for a few years, earlier versions of its technology required developers to hand over complete builds, source code, or to embed a proprietary SDK into their projects.
This “integration‑based” approach proved cumbersome, generating friction between developers and QA teams and limiting scalability, according to Modl.ai founder Christoffer Holmgard. The new solution, Holmgard explains, eliminates the need for deep internal access.
"We treat the product exactly as you would hand it to a QA tester or eventually to a consumer," he says. "The game runs on a device that mirrors the end‑user environment, while our AI watches the screen, simulates key inputs, records every interaction, and then passes the resulting data set to a second AI layer that flags anomalies, surfaces potential bugs, and escalates them to a human reviewer for final judgment." The process begins with what Modl.ai calls building "game knowledge." Developers upload assets—textures, models, design documents, even screenshots—and converse with the AI using natural‑language prompts. This conversational interface allows the system to form a contextual understanding of the game’s mechanics, narrative, and visual style. "All of this happens in plain English," Holmgard notes.
"You can chat with the model, feed it images, drop in design docs, and it gradually builds a mental model of your title." Once the AI has a baseline comprehension, developers define the testing scope. Test cases can range from traditional scripted scenarios to more exploratory prompts that are specifically crafted to exploit the AI’s strengths. Holmgard stresses that human expertise remains crucial at this stage: "You need to shape the prompts and guide the AI so it performs the right actions. That’s where a seasoned QA professional’s intuition comes into play." During a test run—referred to by Modl.ai as a "session"—the system captures textual logs, short video clips that serve as evidence, and comprehensive telemetry.
These artifacts are bundled into a bug report and handed off to a human QA specialist for verification. "The specialist reviews the evidence, decides whether the flagged issue is truly a defect, a feature, or an acceptable edge case, and then provides feedback," Holmgard says. "That feedback loop trains the AI over time, sharpening its ability to differentiate between bugs and intentional design choices." Side sees this feedback‑driven loop as a pathway to elevate its workforce.
Chief Commercial Officer Martin McBride explains that the partnership enables Side’s testers to transition from repetitive, low‑value tasks to roles akin to AI engineers. "Instead of climbing a ladder that ends at senior tester, our people can become AI engineers, earn higher salaries, and open new career trajectories," he states. "By moving these jobs up the value chain, we can even repatriate work to regions where QA has previously migrated because of cost pressures." McBride also argues that AI can make QA careers more rewarding.
The automation of routine smoke tests and regression checks frees testers to focus on strategic analysis, creative testing, and deeper gameplay evaluation. "When the machine handles the monotony, our staff can think critically, interpret data, and contribute to game design decisions," he adds.
Modl.ai’s Chief Product Officer Benedikte Mikkelsen echoes this sentiment, pointing out that many current tests are overly tedious. "You don’t need a human to repeat the same flow hundreds of times.
Let the AI handle that, and let people concentrate on assessing gameplay, crafting innovative test scenarios, and delivering higher‑impact insights. That’s the real value proposition of AI in QA." Both executives stress that AI will never replace human testers outright. The price differential for low‑cost testing labor in certain countries makes a full automation takeover impractical, McBride observes. "Our goal is to augment, not eliminate, the human element.
By providing sophisticated tools, we extend careers, raise skill levels, and keep talent engaged for longer periods," he says. Side’s philosophy treats AI as a "sliding scale"—a spectrum where human involvement is always present, albeit at varying intensities. "There will always be a human in the loop; that’s our ethos," McBride affirms. "The AI reduces repetitive workload and human error, allowing us to deliver higher‑quality results while keeping our people at the core of the process." When asked about the types of games the system can currently handle, Side’s Chief Operating Officer 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 on the roadmap but require further refinement. "We’re targeting clients willing to embark on this journey with us, even if they have modest expectations at the outset. Early adopters will help us iterate and expand the solution’s capabilities," Deslandes explains.
In summary, the Side‑Modl.ai collaboration aims to blend AI’s speed and consistency with the nuanced judgment of seasoned QA professionals. By automating the grunt work, enriching the tester’s role, and maintaining a human‑centric approach, the partnership aspires to reshape the economics and quality of game testing, paving the way for a more sustainable and rewarding industry landscape.