Side, a seasoned 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 effort to build an AI‑enhanced quality‑assurance (QA) platform that blends Side’s extensive testing expertise with Modl.ai’s cutting‑edge machine‑learning capabilities.
Modl.ai, a relatively new entrant to the gaming sector, was founded in 2018 and secured $1.7 million in seed capital two years later. Its founders have spent the past several years refining AI tools that can automatically detect bugs, performance regressions, and other issues in video games. According to Martin McBride, Side’s chief commercial officer, the partnership “combines the best of what Side brings to the table with the most advanced AI technology Modl.ai has developed, creating a unique solution for the games industry.” He adds that the collaboration aims to deliver what many in the sector refer to as the “holy grail” of QA: a system that leverages AI to augment human testers without replacing them. Historically, AI‑driven QA solutions required developers to hand over entire game builds or even source code to the testing vendor.
Modl.ai’s earlier offering relied on an integration model that used a plugin and SDK, demanding deep access to the game’s internals. This approach proved cumbersome and created friction for developers, as noted by Modl.ai founder Christoffer Holmgard, who described the process as “difficult over time.” The new system eliminates the need for such intrusive integration. Holmgard explains that the product is treated exactly as a human tester would receive it: the game is installed on a device that mirrors the end‑user’s hardware, and the AI runs the game by observing the screen, simulating inputs, and recording every interaction.
The resulting data set is then fed to a second AI layer that scans for anomalies, flags potential bugs, and escalates findings to a human reviewer for final validation. The first phase of the workflow is what Modl.ai calls “building game knowledge.” Developers upload assets, design documents, screenshots, and other relevant materials, then converse with the AI in natural language to teach it the fundamentals of the title. "All of this is in natural language," Holmgard says.
"We just chat with the system about our game, but we also add images and design docs, so the AI builds a contextual understanding." Once the AI has a baseline comprehension, developers specify the testing objectives. These can range from traditional test cases—such as checking level loading times or UI responsiveness—to more exploratory scenarios that are specifically crafted to suit the AI’s strengths.
Holmgard stresses that human expertise remains essential at this stage: "You need to adapt the prompting and language to guide the AI to do the right things." During a test run, the system automatically generates bug reports that include textual descriptions, short video clips as evidence, and comprehensive log data. These artifacts are handed over to a human QA specialist, who reviews each report and decides on the appropriate action within the production pipeline.
Holmgard notes that distinguishing a genuine bug from an intended feature can be challenging for AI alone, and that human feedback helps the model learn these nuances over time. "Feedback from testers—‘this was a bug, this was not, here’s why’—allows the system to become attuned to the subtleties of game design," he says. Side envisions a longer‑term shift in the role of QA professionals. By equipping testers with AI tools, the company hopes to elevate them from repetitive, low‑value tasks to more strategic positions such as AI engineers or data analysts.
McBride explains, "Instead of a career path that stops at senior tester, our people can become AI engineers, earn higher salaries, and open new career pathways. This also lets us bring jobs back to regions where they have previously disappeared due to cost pressures." The impact on day‑to‑day work is equally significant. McBride points out that the AI handles many of the monotonous smoke tests and regression checks that would otherwise consume testers’ time.
"When we automate those repetitive tasks, our staff can focus on strategic analysis, creative testing, and higher‑order problem solving, making their careers more fulfilling," he says. Benedikte Mikkelsen, Modl.ai’s chief product officer, echoes this sentiment: "There are very tedious tests that testers repeat over and over. An AI can take over those flows, freeing humans to assess gameplay, explore edge cases, and perform more inventive testing. That’s the core value proposition." Both leaders are careful to stress that AI will not replace QA workers but rather augment them.
McBride notes that the price point for manual testing in certain low‑cost regions remains so low that a complete AI takeover is not yet feasible. By providing advanced tooling, Side can retain talent, extend careers, and move employees up the value chain. He describes AI as a “sliding scale” where "there will always be a human in the loop," which he frames as the company’s core ethos. When asked about the types of games the solution currently supports, 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 adventures are still a ways off," he says. "We’re focusing on projects that are appropriate for the current capabilities, and we’re looking for partners willing to pilot the technology and grow with us." Deslandes emphasizes that the journey is iterative.
Early adopters will help shape the system’s evolution, providing real‑world data that can be used to expand its applicability to more complex games in the future. He concludes, "If you’re at the table with us now, doing pilots, you’ll see how the tech matures and where it can take us." In summary, the Side‑Modl.ai partnership aims to create a hybrid QA model that leverages AI for speed and consistency while retaining human judgment for nuance and strategic insight. By doing so, it hopes to raise the professional standing of QA staff, reduce repetitive workload, and ultimately deliver higher‑quality gaming experiences to consumers worldwide.