Side, a seasoned services provider, has entered into a six‑month memorandum of understanding with Denmark‑based artificial‑intelligence specialist Modl.ai to co‑develop an AI‑powered quality‑assurance (QA) platform. The agreement binds the two companies to collaborate on a system that blends Side’s deep testing experience with Modl.ai’s cutting‑edge machine‑learning capabilities, aiming to create a more efficient and scalable QA solution for the games industry. Side, formerly known as PTW, has been a fixture in the outsourcing and testing market for many years. Modl.ai, by contrast, is a relatively new 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 “effectively combines the strongest assets of Side and Modl.ai into a unique offering.” He adds that the industry’s long‑standing “holy‑grail” of using AI to augment QA has never been fully realized—until now, in his view. Earlier AI‑driven QA tools, including Modl.ai’s first‑generation product, required developers to ship entire builds or even share source code with the testing vendor. That approach relied on an integration‑heavy plugin and SDK, which proved cumbersome and created friction for development teams. As Modl.ai founder Christoffer Holmgard explains, the new system eliminates the need for any internal access.
“We treat the product exactly as you would hand it to a QA tester or eventually to a consumer,” he says. “You load it onto a comparable device, our solution runs the game by watching the screen, simulating inputs, and logging everything that happens. A second AI then reviews that data, flags potential bugs, and escalates them for human verification.” 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 converse with the AI in plain language.
“All interactions are in natural language,” Holmgard notes. “We can chat about the game, attach images, feed design docs, and the AI gradually forms an understanding of the title.” Once the AI has a baseline comprehension, developers specify the testing objectives. These can range from traditional test cases to novel scenarios that are especially suited to AI‑driven exploration.
Holmgard stresses that human insight is still essential at this stage: “You need expertise to craft prompts and guide the AI so it performs the right actions.” During a test run—referred to by Modl.ai as a “session”—the system captures text logs, short video clips (the “evidence”), and comprehensive telemetry. This package is then handed over to a senior QA specialist who reviews the findings and decides the next steps for the production pipeline.
One of the persistent challenges in game testing is distinguishing a genuine bug from an intentional feature. Holmgard explains that ongoing feedback from human testers helps the AI refine its judgment.
“The AI learns from prompts, the pre‑built game knowledge, and the corrective feedback we provide over time, becoming more attuned to the nuances of each title.” Side envisions a future where QA professionals evolve into AI engineers, shifting the value chain upward. McBride argues that this transition can revitalize job markets that have suffered from low‑cost testing labor. “Instead of a linear career from junior tester to senior tester, our people can become AI engineers, earn higher salaries, and even bring those roles back to regions where they previously disappeared,” he says.
The automation of repetitive, mundane tests frees testers to focus on strategic analysis, creative problem‑solving, and higher‑level quality decisions. Benedikte Mikkelsen, Modl.ai’s chief product officer, echoes this sentiment: “Many current tests are tedious and involve repeating the same flow thousands of times. An AI can handle that, allowing humans to concentrate on assessing gameplay, exploring edge cases, and performing more inventive testing.” Both leaders stress that AI will not replace QA staff but will augment them.
McBride notes that the cost of manual testing in certain low‑wage regions remains too low to eliminate entirely, so a hybrid approach is more realistic. By providing sophisticated tooling, Side aims to extend careers, improve job satisfaction, and retain talent longer. Regarding the technology’s current scope, Side’s chief operating officer Oliver Deslandes admits that the AI solution 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 titles where the gameplay loop is predictable and not overly rapid,” he says.
He adds that early adopters willing to pilot the system will help shape its evolution and demonstrate its cost‑saving potential. In summary, the Side‑Modl.ai partnership seeks to blend human expertise with artificial intelligence to create a more efficient, accurate, and rewarding QA process. By keeping a human in the loop, treating AI as a sliding scale rather than a replacement, and empowering testers to become AI engineers, the collaboration aims to set a new standard for quality assurance in the gaming sector while opening pathways for higher‑value employment across the globe.