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‑powered quality‑assurance (QA) platform that blends Side’s deep industry experience 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 financing two years later. Its chief commercial officer at Side, Martin McBride, describes the partnership as a marriage of the strongest assets each company brings to the table. “One of the holy‑grail aspirations for the games industry today is to harness AI to augment QA services in a way that truly adds value,” he says. “No one has cracked that problem yet, and we believe our combined solution does.” Historically, AI‑enhanced QA tools—including earlier versions from Modl.ai—required developers to ship entire game builds or even provide source code so that the AI could analyse the product.
This “integration‑based” model relied on plugins and SDKs, creating friction and, as founder Christoffer Holmgard notes, becoming increasingly cumbersome over time. The new approach eliminates the need for any internal access. Instead, developers deliver the game exactly as they would to a human tester or, ultimately, to a consumer.
The software runs on a device that mirrors the target platform, captures screen output, simulates player inputs, and records a comprehensive data set of every interaction. That raw data is then fed to a second AI engine that scans for anomalies, flags potential bugs, and escalates findings to a human reviewer. Holmgard explains the first phase as building “game knowledge.” Developers upload assets—artwork, design documents, even snippets of code—and converse with the AI in plain language.
The system absorbs these inputs, creating a contextual model of the game’s mechanics, narrative, and visual style. Once the knowledge base is established, developers specify the testing scope.
This can range from traditional test cases (e.g., “verify that the player can jump”) to novel scenarios that are deliberately crafted to exploit the AI’s strengths. “Human expertise is still essential at this stage,” Holmgard emphasizes.
“You need to phrase prompts correctly so the AI understands what you want it to do.” During a test run, the AI monitors gameplay, captures video snippets, logs events, and compiles textual descriptions of any irregularities. The output—comprising evidence videos, logs, and concise bug summaries—is handed to a seasoned QA specialist.
The specialist reviews each report, decides whether the issue is a genuine defect or an intended feature, and provides feedback that the AI incorporates for future iterations. Over time, this feedback loop refines the system’s ability to differentiate bugs from design choices. Side envisions a future where QA personnel evolve into AI engineers, shifting the value chain upward.
McBride points out that this transition can revitalize job markets in regions where low‑cost testing has migrated away. By upskilling staff, Side can offer higher wages, create new career pathways, and potentially repatriate jobs that were previously outsourced. The AI tool also promises to make QA careers more rewarding. Repetitive smoke tests and routine verification steps often bog down testers, limiting their capacity for strategic thinking.
By automating these monotonous tasks, the AI frees human testers to focus on higher‑level analysis, creative problem‑solving, and gameplay evaluation. "The tool reduces the burden of repetitive tests, allowing our people to think strategically and grow professionally," McBride says. Benedikte Mikkelsen, Modl.ai’s chief product officer, adds that many current tests are overly tedious. "You don’t need a human to repeat the same flow thousands of times.
Instead, they can concentrate on assessing gameplay or conducting more inventive testing," she explains, highlighting the value proposition of AI‑assisted QA. Despite the automation, McBride stresses that AI will never replace QA professionals entirely. The low price point of manual testing in certain regions makes a full AI takeover impractical. Instead, the technology acts as a force multiplier, enabling testers to perform higher‑value work while retaining their expertise.
"There will always be a human in the loop—that’s our ethos," he asserts, describing AI as a "sliding scale" where human oversight remains indispensable. Regarding the types of games the system can handle, Side’s chief operating officer Oliver Deslandes notes that the current focus is on simpler titles—puzzle games, card games, and other experiences with repeatable mechanics. Fast‑paced, 3D open‑world or fighting games present greater challenges and are slated for later development. "We’re targeting clients willing to embark on this journey with us," Deslandes says, acknowledging that early adopters may have demanding expectations around cost savings and performance.
In summary, the Side‑Modl.ai partnership aims to create a hybrid QA workflow where AI handles data‑intensive, repetitive testing while seasoned human experts guide, validate, and enrich the process. By blending automated efficiency with human insight, the collaboration aspires to raise the overall quality of games, elevate the skill set of QA staff, and reshape the global landscape of game testing.