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 effort to build an AI‑driven quality‑assurance (QA) platform that blends Side’s deep testing expertise with Modl.ai’s cutting‑edge machine‑learning capabilities. Modl.ai, a relatively new player in the gaming sector, was founded in 2018 and secured $1.7 million in seed capital two years later.
While the startup has already experimented with AI‑enabled QA tools, earlier versions required developers to hand over complete game builds—or even source code—so the system could run its analyses. That “integration‑based” approach, which relied on plugins and SDKs, proved cumbersome and created friction for studios, according to founder Christoffer Holmgard.
The new solution, Holmgard explains, eliminates the need for any internal access. "We treat the product exactly as you would hand it to a QA tester or eventually to the consumer," he says. "You load it onto a comparable device, our AI plays the game by watching the screen, simulating key actions, and recording every event. A second AI layer then reviews that data, flags potential bugs, and escalates them to a human reviewer for final judgment." The first phase of the workflow is what Modl.ai calls building “game knowledge.” Developers upload assets, design documents, screenshots, or any other relevant material, and then converse with the AI in plain language.
"All interactions are natural‑language based," Holmgard notes. "We can chat about the game, attach images, feed design docs, and the system gradually builds an internal model of how the game works." Once that knowledge base is in place, developers define the testing objectives. These can range from conventional test cases to novel scenarios that are specifically crafted to leverage the AI’s strengths. "Human expertise is still essential at this stage," Holmgard adds, "because you need to phrase prompts correctly and guide the AI to perform the right actions." When a test run—referred to by Modl.ai as a “session”—concludes, the platform automatically generates bug reports.
These reports include textual descriptions, short video clips that serve as evidence, and comprehensive log data. The output is then handed to a senior QA specialist, who reviews the findings and decides how to act on them within the broader production pipeline. One of the perennial challenges in game QA is distinguishing genuine bugs from intentional features.
Holmgard says that feedback loops from human testers are crucial for teaching the AI these subtleties. "Prompt engineering, the pre‑built game knowledge, and ongoing tester feedback all combine to fine‑tune the system over time," he explains.
"Testers label each report as a bug, not a bug, or a design‑intended behavior, and the AI gradually learns the nuance." Side sees this technology as a catalyst for reshaping career paths within its organization. Chief Commercial Officer Martin McBride envisions QA staff evolving into AI engineers, thereby moving up the value chain. "Instead of a linear progression from junior tester to senior tester, our people can become AI engineers, earn higher salaries, and open new career trajectories," he says. "That also gives us the chance to bring jobs back to regions where they have historically disappeared due to low‑cost labor pressures." McBride also stresses that AI is not intended to replace human testers but to augment them.
By automating repetitive, low‑value tasks—such as smoke tests for each new build—testers can focus on strategic analysis, creative exploration, and higher‑order problem solving. "The tool reduces the burden of tedious checks, allowing our staff to think more strategically and grow professionally," he adds. Benedikte Mikkelsen, Modl.ai’s Chief Product Officer, echoes this sentiment: "Many of the current tests are monotonous and can be run by a machine. That frees humans to evaluate gameplay, design innovative test scenarios, and add real creative value.
That's the core value proposition of AI in QA." Both leaders agree that AI will never fully eliminate the human element. "There will always be a human in the loop—that’s our ethos," McBride affirms, describing AI as a "sliding scale" where the proportion of automation can be adjusted but never reaches 100 %. He believes this hybrid approach reduces both workload and human error, leading to higher overall quality. When asked about the types of games the system can currently handle, Chief Operating Officer Oliver Deslandes is candid: the technology is best suited for simpler titles—puzzle games, card games, and other experiences with repeatable mechanics—rather than fast‑paced 3D open‑world or fighting games.
"We’re focusing on projects where the mechanics are predictable and the pace is moderate. Clients willing to pilot this journey with us will help shape the next generation of capabilities," he says. In summary, the Side‑Modl.ai partnership aims to combine robust human expertise with sophisticated AI to create a more efficient, scalable, and rewarding QA process.
By automating the mundane and preserving the critical human judgment, the collaboration hopes to set a new standard for game testing while opening up fresh professional pathways for QA talent worldwide.