AI AND ROBOTICS


process more cost effective. According to Saul Abrahams, VP


Business Development at AKA Foods, the real innovation lies not only in the use of AI but in how the system is able to replicate the way that food technologists already operate. He said: “Our approach recognises that the knowledge within a confectionery business is often tacit, historical, and highly specific. What we provide is a container – a secure, structured space where knowledge can be gathered, retained, and used actively for product development.” Traditional product lifecycle management (PLM) systems have tended to focus more on the final formulations, as inputs to procurement, and production planning. AKA Studio, in contrast, is designed around the product development journey – capturing every iteration, every ingredient switch, and every piece of feedback. “By capturing all perspectives from prototype iterations and sensory trials and integrating them into AI workflows, AKA Studio ensures that critical subjective feedback is never lost. This is particularly important given that such evaluations often guide formulation decisions as much as analytical data,” said Saul. Bringing together subjective product


evaluations with historical data, supplier specifications, analytical measurements, and sensory inputs and embedding it all within a searchable, AI-enabled workspace, is a notable differentiator from other product development tools.


The value of AI The value of AI in product development, Saul believes, is not in replacing the technologist but in elevating their ability to work more effectively and efficiently. “We are not trying to replace chocolatiers,” he said. “But many product development teams today are still using the same tools that were used 30 years ago – pen, paper, spreadsheets. What we can offer is the information and insights that can help them make smarter decisions faster, reducing duplications, and ensuring that any knowledge that is gained on the journey is retained.” In an industry where reformulation is


becoming ever more necessary – due to cost volatility, supply chain pressures, and changing consumer demands – a more efficient, structured, and secure approach is beneficial. Reformulation, Saul noted, is never simply a matter of switching one ingredient for another. “Even just changing a supplier can be a


experience into a structured resource which can be especially valuable for mid- sized manufacturers, where a single food scientist also have many other roles to perform within the business. Keeping data se c u r e


Security of recipe data is a critical concern in confectionery, where proprietary formulations represent core intellectual property. “AKA Studio addresses this issue through the use of strict isolation of customer data – whether deployed via secure cloud or private on-premise solutions,” explained Saul. “Further, our AI models are never trained on customer data ensuring that data remains within the control of each client.” The platform is accessible to users via


standard desktop or touchscreen devices, with functionality designed for benchtop and environments. It also supports digital input via touchscreen and also allows printing and manual data entry for facilities that may not be fully digitised. According to Saul, one of the biggest


OUR AI MODELS ARE NEVER


TRAINED ON CUSTOMER DATA ENSURING THAT DATA REMAINS WITHIN THE CONTROL OF EACH CLIENT


frustrations for technologists is transcribing technical data sheets and for this reason the solution also supports the ingestion of technical documents such as supplier PDFs. Saul also pointed out that the platform is not simply based on theory. AKA Foods has its own lab facilities, where its food technologists continually test the system on real food products. “The software is designed by food scientists, for food scientists,” he said.


high-stakes decision,” he said. “It involves intensive, iterative work, and typically costly and time-consuming trials.” While AI cannot eliminate the need for hands-on testing, it can help reduce the number of tests required by narrowing the field of possibilities and highlighting the most promising options earlier in the process. Traditionally, critical insights have


resided in the minds of food technologists with decades of experience. But, as Saul pointed out, many of these individuals are now coming up for retirement, and those replacing them may not have the same depth of understanding. When someone with decades of knowledge leaves a business most of that knowledge will go with them. With generative AI and what Saul referred to as ‘agentic workflows’, it becomes possible for organisations to capture data about what worked, what failed, and why during a product development project. This turns


A strategic benefit Saul highlighted one of AKA Studio’s more strategic benefits as revolving around the onboarding of new hires. He reasoned that the success of a new technologist will often depend less on their formal training and more on their ability to locate internal knowledge and connect with the right colleagues. “With a system like AKA Studio, those insights become accessible from day one. We help teams make better decisions earlier which results in fewer failed iterations, lower costs, and better outcomes,” he said. Ultimately, the greatest benefit of this AI-enabled solution for confectionery producers would appear to lie in a combination of speed, cost reduction, and knowledge retention surrounding product development. As AI tools become more integrated into product development workflows, the technology, used properly, can position itself not as a replacement for human insight, but as a multiplier of its value.


DECEMBER/JANUARY 2025/26 • KENNEDY’S CONFECTION • 51


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