AWS Public Sector Blog
Built with teachers, powered by AWS: How Sanoma Learning created Sanna, its AI teacher assistant
More than half of teachers across Europe already use AI in their work according to Sanoma Learning’s annual European Teacher Survey. Most use generic tools that were not designed for the classroom, leaving many unsure whether they can trust the outputs or whether these tools improve learning outcomes.
Sanoma Learning, the leading K-12 learning provider in Europe—supporting 25 million students across 11 countries—saw the gap between what teachers were using and what they needed. Working with Amazon Web Services (AWS), Sanoma built an AI teacher assistant, an educational AI product grounded in the learning materials teachers already use and aligned with national curricula. Teachers in seven countries helped shape it through the testing and pilot phase, with 1,500 using it in their classrooms this spring, ahead of the full product launch.
On October 1st, the teacher assistant was launched as Sanna by Sanoma Learning in selected European markets, including Finland, Sweden, the Netherlands, Belgium, Poland, Italy and Spain.
Educational AI, not generic AI
Sanoma Learning is Europe’s largest K-12 educational publisher, and Oleg Sokolov, senior director for data and AI at Sanoma Learning, considers that position as much an obligation as an opportunity.
“We do not believe in a future where AI replaces a teacher,” he said. “We believe in a future where AI complements teachers and helps spend their time where it matters most—with their students.” He expects AI to become an integral part of the classroom, working alongside the teacher.
Teachers told Sanoma they wanted real guidance and trustworthy products, something more than generic AI assistants that can’t truly complement a teacher because they don’t know what a specific classroom is learning. If you ask an AI assistant for practice problems, the answers might be right, but the method is wrong or too advanced for the grade.
Sokolov sees three things that set Sanoma apart from general AI companies building these tools. Sanoma publishes the textbooks and workbooks teachers already use, so it has something to ground AI in. It has hundreds of pedagogical experts across Europe who develop those materials and work with teachers every day, so Sanna reflects how each subject is taught. Schools already trust how Sanoma handles their data because Sanoma has spent years building digital products with the General Data Protection Regulation (GDPR) and the EU AI Act in mind.
An innovation workshop in Amsterdam
AWS had been Sanoma’s cloud provider for years, but the two had never worked together to build a new product. AWS offered Sanoma an Innovation Acceleration engagement, and in March 2025, the teams met in Amsterdam. Sanoma brought representatives from four countries, and pedagogical experts from its editorial side. AWS brought its global EdTech vertical leader, education specialists, and members of the AWS Generative AI Innovation Center (GenAIIC).
AWS facilitated a two-day session using the Amazon Working Backwards process, guiding the group from the pain points teachers had already reported toward a defined product vision. Starting from the teacher, not the technology, the group turned a broad ambition into a concrete set of ideas the teams could build. Not every idea could come first. AWS helped Sanoma weigh the possibilities against teacher impact and technical feasibility, narrowing a long list of potential features down to the use case worth prototyping. After the workshop, the teams turned the concept into concrete requirements, including what grounded in the curriculum meant in practice, how sources should surface for teachers, and the guardrails needed to satisfy GDPR and the EU AI Act.
From product requirements to prototype in six weeks
The collaboration moved quickly. The AWS GenAIIC, a team that pairs AWS scientists and engineers with customers to build production generative AI, worked with Sanoma’s engineers. Drawing on reusable components, the joint team had a first prototype ready in only 6 weeks. Sanoma built Sanna on Amazon Bedrock, which the team can use to choose the model that fits the job and switch to a different one as the product evolves, without rebuilding anything.
Building Sanna alongside teachers
Dozens of teachers in four European countries tried that prototype in May and June 2025. Sanoma conducted additional testing in fall 2025, with a larger pilot in February 2026. Then, in April 2026, Sanoma opened a scaled pilot to 1,500 teachers across seven countries. That was the first time teachers used Sanna in real lessons rather than a test setting.
Dominique Lemmi, UX research competence lead at Sanoma Learning, embedded a researcher within the AI team. Early on, the team met with teachers every 2 weeks, using a mix of research methodologies, including longitudinal diary studies, interviews, and surveys, to continuously gather feedback. Because each market follows its own curriculum, the product needed to accommodate different local requirements. Some teachers preferred open prompts, while others wanted guided prompts. Teachers also asked for editable and printable outputs, in addition to a visible link to the source chapter. Sanoma incorporated this feedback into the product.
Instead of being skeptical, teachers signed up for the pilot voluntarily. They came to sessions curious about what other teachers were saying and excited to provide their ideas. “We weren’t building for them, but with them,” Lemmi said. Sokolov thinks that’s also why adoption went so well. Teachers who help build a product see the process and understand it, whereas a finished product handed to them directly can leave them hesitant.
How Sanna works
Sanna looks like a familiar text-based AI interface and is tailored to teachers’ needs. A teacher can select options such as subject, book, or chapter, or type directly into Sanna using natural language. Every output is grounded in their material, with sources the teacher can check against the actual textbook. In guided mode, the teacher selects options—grade level, difficulty, and learning needs—then presses generate.
Sanna also helps differentiate lessons. A teacher can ask for a version of the chapter’s exercises for students with dyslexia, a harder version for advanced students, or a simpler text for children learning the local language. Sanna returns formatted sheets ready for the classroom, along with lesson plans and tests. Many teachers report saving time, but Sokolov thinks the differentiation matters more. “They don’t have much time to spare,” he said. “Now, they can do more.”
What the pilot showed
By the end of the spring term, Sanoma had a clear picture of how the 1,500 teachers in the pilot used Sanna. The results were stronger than Sokolov had expected:
- 88 percent of teachers said the quality of the output matched or beat what they would have produced themselves.
- 75 percent used outputs directly in the classroom.
- More than 80 percent said they would be disappointed if they lost Sanna.
- Teachers rated their likelihood of adopting the product at about 4.8 out of 5, with similar scores for how well it fits their workflow.
Those in the pilot told Lemmi’s team that because preparing lessons took less time, they could spend more of the day coaching individual students. One teacher described Sanna as an extension of themselves, one that helps without taking control of the classroom away.
Keeping the teacher in control
Sanna was soft launched to teachers October 1, 2026. A grading and feedback module is also in the works. It will scan paper tests, group similar answers to the same question, and suggest a score against the teacher’s own criteria so that the teacher can calibrate across the whole class at once. “AI suggests, AI helps, AI organizes,” Sokolov said. “Then, the teacher makes the call and actually does the grading.”
Ask Sokolov or Lemmi what other EdTech teams should take from this experience, and both come back to the teachers. Build with them, keep them in the loop, and learn what trust means to them. For Sanoma’s teachers, trust was about pedagogically grounded content from Sanoma’s trusted materials, sources they can see, control over the output, and confidence that the product is safe to use, technically and personally.
Lemmi always remembers who the product is ultimately for. “The end receiver is always the student,” she said. When a teacher can prepare a lesson for each student in the room and still have time to coach and support them, Sanna is helping deliver on Sanoma Learning’s mission: enabling teachers and schools to help every child reach their potential, while keeping teaching a deeply human act.”
To explore opportunities to build great products for education, connect with the AWS EdTech team.