Side, a seasoned services provider formerly known as PTW, has entered into a six‑month memorandum of understanding with Danish artificial‑intelligence specialist Modl.ai. The partnership is designed to create a hybrid, AI‑driven quality‑assurance (QA) platform that blends the strengths of both organisations. 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. Side, by contrast, has been operating in the services arena for many years, giving it deep expertise in large‑scale testing operations.
Martin McBride, Side’s chief commercial officer, summed up the collaboration: “The MOU essentially fuses Side’s extensive QA capabilities with Modl.ai’s cutting‑edge AI technology into a single, differentiated solution. The industry has long searched for a reliable way to augment QA with AI, and we believe we have finally cracked it.” Earlier attempts at AI‑enhanced QA required developers to ship complete builds to external testing firms, where the AI would run against the code.
Modl.ai’s previous offering relied on an integration model that demanded a plugin, an SDK, and direct access to source code. This approach introduced considerable friction and, as founder Christoffer Holmgard notes, became unwieldy over time. The new system eliminates the need for any internal code access.
Holmgard explains: “We treat the product exactly as you would hand it to a human tester or eventually to a consumer. The game runs on a device that mirrors the target platform, our AI watches the screen, simulates key actions, records every event, and then passes the data to a second AI layer that flags potential bugs. That layer escalates uncertain findings to a human reviewer for final judgment.” 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.
The system ingests these inputs, forming a contextual model of the game’s mechanics, narrative, and visual style. Once the AI has a foundational understanding, developers specify the testing objectives. These can range from traditional test cases—such as verifying menu navigation or level loading—to novel scenarios that leverage the AI’s pattern‑recognition strengths.
Holmgard emphasizes the role of human expertise at this stage: “Crafting effective prompts and guiding the AI’s language is a skill. Humans must translate testing goals into queries the AI can act upon.” During a test run, the AI records textual logs, short video clips (referred to as “evidence”), and comprehensive telemetry. This package is then handed to a senior QA specialist, who reviews the findings, validates true defects, and decides the next steps in the production pipeline.
One persistent challenge for AI in gaming is distinguishing a genuine bug from an intentional feature. Holmgard notes that continual feedback from human testers refines the system’s judgment.
“The AI learns from the prompts you give it, the game knowledge you build, and the corrective feedback you provide on each bug report. Over time it becomes more attuned to the nuances of your design philosophy.” Side envisions a broader shift in career trajectories as a result of this technology. McBride explains that QA personnel can evolve into AI engineers, moving up the value chain and commanding higher salaries. “Instead of a linear path from junior tester to senior tester, we can offer a route that includes AI‑tool development and data‑science skills.
This not only enriches careers but also opens the possibility of bringing jobs back to regions that lost them due to low‑cost testing models.” The AI tool also promises to make QA work more satisfying. By automating repetitive smoke tests and routine verifications, testers can focus on strategic analysis, creative exploration, and higher‑order problem solving. “When the mundane tasks are offloaded to the AI, our people have the bandwidth to think critically about gameplay balance, user experience, and emergent issues,” McBride says. Benedikte Mikkelsen, Modl.ai’s chief product officer, adds that many current tests are monotonous and could be performed more efficiently by machines.
“If a tester is spending hours repeating the same flow, that time could be redirected toward assessing the fun factor or devising innovative test scenarios. That’s the core value proposition of AI‑assisted QA.” Both leaders stress that AI will never fully replace human QA staff.
The price of testing in certain low‑cost regions remains too low to eliminate human involvement entirely. Instead, AI serves as an enabler, allowing testers to stay relevant longer and advance their skill sets. McBride describes AI as a “sliding scale”: there will always be a human in the loop, ensuring quality while leveraging AI’s speed and consistency.
Regarding the types of games the solution currently supports, COO Oliver Deslandes is candid: the technology 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 are focusing on projects where the gameplay loop is predictable enough for the AI to model effectively.
As the platform matures, we’ll expand to more complex genres, but for now we’re partnering with studios willing to pilot this approach and help shape its evolution.” In summary, the Side‑Modl.ai alliance aims to create a hybrid QA ecosystem where AI handles high‑volume, low‑complexity testing, while seasoned human experts oversee interpretation, nuance, and strategic decision‑making. The partnership reflects a broader industry trend toward augmenting, rather than replacing, human talent with intelligent tools, ultimately delivering faster, more accurate bug detection and opening new career pathways for QA professionals.