Side, a veteran services provider formerly known as PTW, has entered into a six‑month memorandum of understanding (MOU) with Danish 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 the strengths of both companies.
While Side brings decades of experience in delivering QA services to the gaming industry, Modl.ai contributes cutting‑edge machine‑learning expertise that it has been honing since its 2018 launch and its $1.7 million seed round two years later. Martin McBride, Side’s chief commercial officer, describes the partnership as a marriage of complementary capabilities: “The MOU essentially fuses what Side does best with what Modl.ai excels at, creating a unique solution for the games sector. One of the holy‑grail goals for the industry right now is to use AI to augment QA in a meaningful way. No one has cracked that puzzle yet – we think we are close.” Historically, AI‑based QA tools required developers to hand over complete builds or even source code to the testing vendor.
Modl.ai’s earlier offering relied on a plugin‑and‑SDK integration that forced developers to expose internal assets, a process that proved cumbersome and, as founder Christoffer Holmgard admits, “became difficult over time.” The new approach eliminates that friction. Instead of digging into the game’s internals, the system treats the product exactly as a human tester would: it runs the game on a device that mirrors the end‑user’s hardware, watches the screen, simulates inputs, records every event, and then passes the resulting data to a second AI layer that flags anomalies, generates bug reports, and escalates items that need human judgment. The first phase of the workflow is what Modl.ai calls “building game knowledge.” Developers upload assets, design documents, screenshots, and even converse with the AI in plain language to teach it the context of their title.
Holmgard explains, “All of this happens in natural language. We chat with the system about the game, feed it images, design docs, and other artefacts, so the AI builds a mental model of what the game is supposed to do.” Once the AI has a basic understanding, developers specify the testing scope. This can range from conventional test cases—such as verifying menu navigation or level loading—to more exploratory scenarios that are tailored to the strengths of the AI. Holmgard notes that human expertise is still essential at this stage: “You need skilled people to craft prompts and guide the AI so it performs the right actions.” During a test run, the system captures a wealth of evidence: textual logs, short video clips that illustrate the issue, and comprehensive telemetry.
These artifacts are compiled into a bug report that is handed to a human QA specialist for review. The specialist decides whether the finding is a genuine defect, a intended feature, or a false positive, and provides feedback that the AI uses to refine its future judgments. Over time, this feedback loop helps the model differentiate subtle design nuances, reducing both missed bugs and unnecessary tickets.
Side sees this collaboration as a catalyst for reshaping QA careers. Rather than remaining confined to repetitive manual testing, staff can evolve into AI engineers who design prompts, interpret model outputs, and fine‑tune the system. McBride says, “Our people can move up the value chain—from junior tester to senior tester, and eventually to AI engineer.
That progression not only raises salaries but also opens new career paths and makes it possible to bring jobs back to regions where low‑cost testing has disappeared.” The AI tool also promises a more satisfying work environment. By automating the monotonous smoke tests and regression checks that accompany every new build, testers are freed to focus on strategic analysis, creative testing, and gameplay evaluation.
“When the repetitive work is offloaded to the AI, our testers can think more strategically and grow their expertise,” McBride adds. Benedikte Mikkelsen, Modl.ai’s chief product officer, echoes this sentiment: “There are many tedious test flows that a human doesn’t need to repeat endlessly. If we automate those, the tester can concentrate on higher‑value activities like assessing game feel or designing novel test scenarios.
That’s the core value proposition of AI in QA.” Both leaders stress that AI will never replace human QA professionals; instead, it will act as a force multiplier. McBride points out that testing costs remain low in certain markets, making a full AI takeover impractical. By equipping people with AI‑assisted tools, Side can extend careers, retain talent, and improve overall quality. He sums up the company’s philosophy: “We view AI as a sliding scale—there will always be a human in the loop.
That’s our ethos. The tool lets us leverage AI’s strengths while keeping humans where they add the most insight, reducing errors and lifting the whole process to a higher level.” When asked about the types of games the solution can handle today, COO Oliver Deslandes is candid: the current version is best suited for simpler titles—puzzle games, card games, and other experiences with repeatable mechanics—not fast‑paced 3D open‑world or fighting games. “We’re targeting projects that have predictable loops and aren’t too rapid. Clients willing to pilot with us will help shape the next iteration, and as the technology matures, we’ll broaden the scope.” In summary, the Side‑Modl.ai partnership aims to create a hybrid QA ecosystem where AI handles high‑volume, low‑complexity testing while human experts provide the nuanced judgment and continuous feedback that keep the system accurate.
The six‑month MOU will serve as a proving ground for this model, with the ultimate goal of delivering faster, cheaper, and more reliable quality assurance for game developers worldwide.