Side, a veteran 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 technology.
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. Its founders saw a gap in the market: existing AI‑powered QA tools required developers to ship complete builds or even share source code, creating friction and security concerns. The earlier versions of Modl.ai’s system relied on an integration model that used plugins and SDKs, demanding deep access to a game’s internals. As Modl.ai’s co‑founder Christoffer Holmgard explains, that approach “became difficult over time” because it slowed down the testing pipeline and raised confidentiality issues.
The new solution outlined in the MOU eliminates the need for any internal code access. Instead, developers hand over the same product they would eventually give to a QA tester—or even directly to a consumer. The game runs on a device that mirrors the target hardware, while Modl.ai’s AI watches the screen, simulates player inputs, records every on‑screen event, and compiles a comprehensive data set. A second AI layer then scans that data, flags potential bugs, and escalates the findings to a human reviewer for final validation.
A crucial first step is what Modl.ai calls “building game knowledge.” Developers upload assets, design documents, screenshots, and other relevant material, then converse with the AI in natural language to teach it the nuances of their title. Holmgard notes that the interaction is conversational: “We just chat with the system about our game, but we’re also adding in images, or we might upload our game design documents and so on.” Once the AI has a solid contextual foundation, the development team defines the test scenarios they wish to explore—ranging from classic regression cases to novel, AI‑friendly challenges. Human expertise remains indispensable at this stage.
Crafting effective prompts and guiding the AI’s language model requires a tester who understands both the game’s mechanics and the capabilities of the AI. After the AI runs a “session” (Modl.ai’s term for a test run), it produces bug reports that include textual descriptions, short video clips as evidence, and full log files. These artifacts are handed to a senior QA specialist, who reviews them, decides which issues merit further action, and provides feedback that helps the system learn over time. Distinguishing genuine bugs from intentional features is a known difficulty for automated testing.
Holmgard explains that iterative feedback from human testers fine‑tunes the AI’s judgment: “They will provide feedback to the bug reports and say: ‘This was a bug; this was not a bug; this was not a bug for this reason.’ Over time, the system gets attuned.” Side sees this collaboration as a pathway to elevate its workforce. Chief Commercial Officer Martin McBride envisions QA staff transitioning into AI‑engineer roles, thereby moving up the value chain.
“Instead of just doing testing and climbing the ladder from junior tester to senior tester, they can become an AI engineer,” he says. This shift promises higher salaries, new career trajectories, and the possibility of reshoring jobs that have migrated to lower‑cost regions. By automating repetitive, low‑skill tasks—such as smoke tests and routine verifications—testers can focus on strategic analysis, creative problem‑solving, and deeper gameplay evaluation. Chief Product Officer Benedikte Mikkelsen of Modl.ai echoes this sentiment, noting that many current tests are “tedious” and could be handled by a machine, freeing humans to assess gameplay quality and conduct more inventive testing.
Both companies stress that AI will not replace QA professionals but will augment them, allowing for more fulfilling work and reducing human error. When asked about the types of games the platform can currently handle, 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 or fighting games remain a longer‑term goal. “We are focusing on titles that are more appropriate at this stage,” Deslandes explains, emphasizing that early adopters will likely be studios willing to pilot the solution and tolerate the iterative nature of its development.
In summary, the Side‑Modl.ai partnership aims to create a hybrid QA workflow where AI handles high‑volume, repetitive testing while seasoned humans provide oversight, context, and continuous training for the system. The six‑month MOU will serve as a proving ground for this approach, with the ultimate objective of delivering a scalable, cost‑effective, and quality‑centric testing solution that respects both technical constraints and the creative nuances of game development.