Side, a seasoned services provider formerly known as PTW, has entered into a six‑month memorandum of understanding with Denmark‑based artificial‑intelligence company Modl.ai. The agreement sets the stage for a joint effort to build an AI‑driven quality‑assurance (QA) platform that blends Side’s extensive testing expertise with Modl.ai’s cutting‑edge machine‑learning capabilities. Modl.ai, a relatively new player in the gaming sector, was founded in 2018 and secured $1.7 million in seed financing two years later. While Side brings decades of experience in delivering testing services across multiple platforms, Modl.ai contributes a fresh perspective on how AI can augment, rather than replace, traditional QA processes.
"The MOU essentially combines the strongest assets of both companies into a unique offering," explains Martin McBride, Side’s chief commercial officer. "One of the holy‑grail ambitions for the games industry today is to harness AI to enhance QA.
No one has yet delivered a truly effective solution, and we believe this partnership gets us there." Earlier AI‑enabled QA tools, including earlier versions from Modl.ai, required developers to ship complete builds—or even source code—so that the AI could run tests. That approach relied on integration plugins and SDKs, creating friction and scalability issues, as noted by Modl.ai founder Christoffer Holmgard.
The new system eliminates the need for internal access. "We treat the product exactly as you would hand it to a QA tester or eventually to a consumer," Holmgard says. "You run it on a comparable device, and our solution 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 findings to a human reviewer for final validation." The workflow begins with what Modl.ai calls "building game knowledge." Developers upload assets, design documents, screenshots, or even converse with the AI in natural language to teach it the specifics of their title. This conversational approach helps the system develop a contextual understanding of gameplay mechanics, art style, and narrative elements. Once the AI has a baseline comprehension, developers define the testing scope—ranging from standard regression cases to novel scenarios tailored for AI interpretation. "Human expertise is still essential at this stage to craft the right prompts and guide the AI toward meaningful tests," Holmgard notes.
During a test run, the system produces a comprehensive bug report that includes textual descriptions, short video clips as evidence, and full log data. These artifacts are handed off to a human QA specialist, who reviews the findings and decides the appropriate next steps in the production pipeline.
One of the perennial challenges in game QA is distinguishing a genuine defect from an intended feature. Holmgard explains that continuous feedback from human testers helps the AI refine its judgment. "Prompt engineering, pre‑built game knowledge, and iterative human feedback all converge to teach the model what constitutes a bug versus a design choice," he says.
Over time, the AI becomes increasingly attuned to the nuances of each project. Side envisions a future where QA personnel transition into AI‑engineer roles, elevating the value chain of their workforce. "Our people can move beyond repetitive testing to become AI engineers, earning higher salaries and opening new career pathways," McBride asserts. This shift could also reverse the off‑shoring trend that has seen many testing jobs migrate to low‑cost regions.
By upskilling staff, Side hopes to bring talent back to markets where it previously vanished. McBride adds that AI will make QA careers at Side more rewarding. By automating mundane smoke tests and repetitive verifications, testers can focus on strategic analysis, creative problem‑solving, and higher‑level quality assessments.
"The tool reduces the burden of rote tasks, allowing our team to think more strategically and grow professionally," he explains. Benedikte Mikkelsen, Modl.ai’s chief product officer, echoes this sentiment: "Many current tests are tedious and can be run by a machine.
Freeing humans from those loops lets them concentrate on evaluating gameplay, exploring edge cases, and performing inventive testing that adds real value." Both leaders stress that AI is not a replacement for human QA workers but a catalyst for career advancement. "Testing costs are still low in certain regions, making a full AI takeover impractical," McBride says. "Providing our staff with AI tools extends their careers and keeps them engaged, while also improving accuracy and efficiency." Side’s philosophy frames AI as a "sliding scale"—a spectrum where human involvement never disappears.
"There will always be a human in the loop; that’s our ethos," McBride affirms. By combining AI speed with human judgment, the partnership aims to cut errors, streamline workflows, and raise overall quality.
When asked about the types of games the solution currently supports, COO Oliver Deslandes clarifies that 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’re focusing on titles where the AI can demonstrate value now, while working with partners willing to pilot the technology and help shape its evolution," Deslandes says. In summary, the Side‑Modl.ai collaboration seeks to create a hybrid QA ecosystem where AI handles the heavy lifting of data collection and preliminary bug detection, and seasoned human testers apply their expertise to validate and prioritize issues.
By doing so, the partnership hopes to deliver faster, more accurate testing, open new career trajectories for QA professionals, and ultimately set a new standard for quality assurance in the gaming industry.