Students engage with realistic AI personas in immersive professional scenarios, developing critical skills through discovery-based learning that mirrors real-world challenges.
Bringing Learning Cases to Life Through Dynamic Simulation Universes
SNAPLAB bridges the gap between theoretical learning and practical application by transforming static educational content into immersive, AI-driven simulations. Students step into realistic professional scenarios, interact with authentic AI personalities, and navigate real-world complexities in a safe, controlled environment that promotes both engagement and educational effectiveness.
Focus on HOW students reach solutions, not WHAT they develop. Students learn to approach stakeholders, identify requirements, and iterate on findings through real-world case scenarios.
Cases can be tailored to follow curriculum requirements in real-time, fitting seamlessly into existing educational structures. AI personas maintain realistic schedules with team meetings and busy periods, creating authentic professional environments.
Example: 3 sessions of 20 minutes each, distributed over 3 weeks. Allows students time to develop and iterate between sessions. Key findings can be discussed in classroom and plenum sessions, enabling collaborative learning from each other's discoveries.
SNAPLAB cases are multi-round simulations with incremental complexity where students engage with AI personas across company hierarchies, developing critical skills in stakeholder management, requirements engineering, and collaborative problem-solving through realistic professional scenarios.
Fine-tuned AI models based on extensive research and personality tests. Our persona vectors deliver authentic behavioral traits and high-precision responses that accurately mimic real personality types with exceptional consistency. Learn more about our research methodology.
Each case supported by detailed documentation with ISBN numbers for academic reference. Case-specific learning objectives clearly defined with teacher facilitation guides.
Our methods are grounded in educational technology research and validated through peer-reviewed publications in AI-powered learning. We have contributed scholarly articles to academic journals, advancing the understanding of simulation-based pedagogical approaches and their impact on student learning outcomes.
AI personas can change opinions based on student interactions. Characters may not show up or become unavailable, requiring adaptation.
Calendar-based meetings, deadlines, and unforeseen disruptions. Evolving constraints that change during implementation. Some constraints may be revealed later if students are not asking about them, changing complexity.
Cases that respond dynamically to student decisions and progress. Greater directional possibilities with unique learning paths.
Different student groups discover different information from the same characters. Multiple valid solution approaches.
SNAPLAB enables efficient whole-class management through AI-synthesized insights from student interactions, facilitating collaborative discussions where different groups share diverse approaches and solutions to the same challenges.
Use synthesized findings to facilitate classroom discussions. Compare different student group discoveries and approaches. Share diverse findings and solutions across the class.
AI synthesizes the most important information and key metrics from student interactions. Teachers receive core findings without reading through all communication logs, with automated extraction of critical insights for efficient classroom management.
Evaluates HOW students approach unknown tasks, their problem-solving methodology, and strategic thinking patterns rather than just final outcomes.
Measures students' ability to connect information across multiple interactions, adapt strategies based on new discoveries, and refine their approach iteratively.
Assesses individual and group reflection capabilities, including awareness of learning progress, identification of knowledge gaps, and metacognitive development.
Evaluates professional interaction quality, communication effectiveness, and ability to build productive relationships with AI personas representing diverse stakeholders.
Students receive continuous, contextual feedback throughout their case interactions. The AI-powered feedback system provides guidance on communication strategies, suggests areas for deeper investigation, and offers insights to enhance learning outcomes during the simulation experience.
Professionally designed scenarios with academic documentation
ISBN 978-87-94215-01-7
Design a fair and efficient team scheduling system through stakeholder interviews. Students gather requirements from a project manager and four supporters with competing priorities, then deliver a Product Requirements Document.
Duration: 45–60 minutes · Level: Intermediate
ISBN 978-87-94215-02-4 · Coming soon
Test a newly-learned sales framework with a real client after the formal course material has ended. Students apply theory in a live conversation — adapting the framework to the client's context, handling objections on the fly, and demonstrating that they can move from classroom knowledge to practical use.
Focus: Applied sales practice · framework adaptation under real conditions
ISBN 978-87-94215-03-1 · Coming soon
Lead a high-stakes meeting during an unfolding crisis. Students balance time pressure, conflicting information from stakeholders, and the need to make decisions with incomplete data — all while keeping the team aligned.
Focus: Crisis handling · decision-making under uncertainty
Our platform is built on Nordic business ethics principles emphasizing transparency, collaborative decision-making, work-life balance, and flat organizational culture with open communication and accessible leadership. SNAPLAB operates on isolated virtual environments with locally deployed language models on Danish encrypted servers, ensuring complete student data sovereignty and GDPR compliance.
We incorporate comprehensive AI safety measures including LLM safety middleware that mitigates AI jailbreaking and inappropriate responses, with extensive synthetic testing across thousands of conversation scenarios.
Advanced safety checks mitigate AI jailbreaking and inappropriate responses
Thousands of synthetic datasets of conversation scenarios tested across models
Locally deployed models eliminating external API dependencies
Professional Platform Access with Demo Case Integration
Student/educator access to learning simulations with demo case available for selection. Experience the full SNAPLAB functionality through the actual scheduling case.
Educator access to case development tools and custom scenario creation. Collaborative case design with educational validation.
Teacher/administrator access to student progress monitoring and interaction analysis. Comprehensive learning analytics.
Experience the SNAPLAB platform with access to diverse case studies across multiple professional domains. Explore existing simulations, interact with AI personas in various scenarios, or collaborate with the SNAPLAB team to develop new cases tailored to your specific educational requirements and curriculum objectives.