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 venture that will blend Side’s deep experience in quality‑assurance (QA) outsourcing with Modl.ai’s cutting‑edge AI technology to create a new, AI‑enhanced QA platform for the video‑game industry. Modl.ai, founded in 2018, secured $1.7 million in seed capital two years after its inception and has since focused on building AI tools that can automate parts of the testing workflow. While earlier AI‑driven QA solutions required developers to hand over complete builds, source code, or integrate SDKs and plugins, the new system promised by Modl.ai eliminates that friction.
According to co‑founder Christoffer Holmgard, the approach now treats the game exactly as a human tester would receive it – a compiled build delivered to a console or PC, with no need for internal code access. The AI observes the game’s visual output, simulates player inputs, records every on‑screen event, and then passes the resulting data set to a second AI layer that flags potential defects, escalates them to a human reviewer, and asks whether corrective action is warranted. 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 using natural‑language prompts.
This dialogue helps the system construct a semantic model of the game world, mechanics, and expected behaviours. Holmgard explains that the interaction is deliberately conversational: "We just chat with the system about our game, but we also feed it images, design docs, and any other relevant material." Once the AI has a baseline understanding, developers define test objectives. These can range from traditional regression cases – such as verifying that a character’s jump height remains consistent after a patch – to more exploratory scenarios that are specifically crafted to leverage the AI’s pattern‑recognition capabilities. Holmgard stresses that human expertise is still crucial at this stage: "You need to shape the prompts and the language so the AI knows exactly what to look for." During a test run, the system captures a rich set of artefacts: textual logs, short video clips that serve as evidence, and comprehensive telemetry.
These artefacts are bundled into a bug report that is handed over to a human QA specialist. The specialist reviews the findings, decides whether each issue is a genuine defect, a design choice, or a false positive, and provides feedback that the AI ingests to improve future iterations. Holmgard notes that this feedback loop helps the AI differentiate between bugs and intentional features, a distinction that can be subtle in game design.
Side sees the partnership as a pathway to elevate its workforce. Chief Commercial Officer Martin McBride envisions QA staff transitioning into "AI engineers" who design prompts, interpret AI‑generated insights, and fine‑tune the testing pipeline.
This shift, he argues, moves employees up the value chain, allowing them to earn higher wages, pursue new career trajectories, and potentially repatriate jobs to regions that have lost testing work due to cost pressures. "Instead of a linear ladder from junior tester to senior tester, we can now offer a route toward AI‑focused roles," McBride says. The automation of repetitive, low‑value tasks is another key benefit. Smoke tests, regression checks, and other routine verifications consume a large portion of a tester’s day.
By offloading these to the AI, human testers can focus on strategic analysis, creative exploratory testing, and higher‑level quality assessments. "The tool reduces the burden of repetitive tests, freeing our people to think more strategically and grow their careers," McBride adds. Modl.ai’s Chief Product Officer Benedikte Mikkelsen echoes this sentiment, pointing out that many current QA activities involve monotonous, repeatable flows that a machine can execute more consistently than a human. "If you free testers from running the same sequence over and over, they can concentrate on evaluating gameplay feel, balance, and other nuanced aspects that truly require human judgment," she explains.
Both companies are careful to stress that AI will not replace QA professionals. McBride notes that testing rates in certain low‑cost regions remain so low that a full AI takeover is economically infeasible. Instead, the technology acts as an augmentation tool, enabling testers to stay relevant and extend their careers while maintaining a human‑in‑the‑loop safety net. "There will always be a human in the loop – that’s our ethos," he says, describing AI as a sliding scale rather than a binary replacement.
Regarding the types of games the solution can handle today, Side’s Chief Operating Officer Oliver Deslandes admits that the platform is best suited for titles with relatively simple, repeatable mechanics – such as puzzle games, card games, or other low‑pace experiences. Fast‑paced, 3D open‑world or fighting games present additional challenges that the team plans to tackle in later phases.
Deslandes emphasizes that early adopters will likely be studios willing to experiment and co‑develop the technology, accepting that initial results may be modest but that the partnership offers a clear roadmap toward more sophisticated AI‑driven QA. In summary, the Side‑Modl.ai collaboration aims to blend human expertise with machine efficiency, creating a hybrid QA model that reduces repetitive workload, improves defect detection, and opens new career pathways for testers. The six‑month MOU will serve as a proving ground for this approach, with the ultimate goal of scaling the solution across a broader range of game genres and geographic markets once the technology matures.