Students often struggle to get the individualized attention they need to thrive. Teachers have limited bandwidth, and traditional tutors can be expensive, and have relatively narrow subject matter expertise. Publishers and EdTech companies have looked to AI student assistants to help fill this need, but it is difficult to build AI student assistants that have robust knowledge about a wide array of subjects, have high accuracy in their responses, and make effective use of the vast amount of educational content available in their catalog, while maintaining educational integrity by guiding students instead of just providing them with answers.

Our AI Student Assistant is built with Generative AI models fine-tuned on your corpus of educational content as well as content generated from human experts in a wide variety of educational fields, including math, biology, physics, chemistry, coding, and more. These models leverage advanced retrieval augmented generation (RAG) to ground responses in the most relevant texts, giving students confidence in response accuracy. The solution dynamically learns each student's strengths and weaknesses and preferred pace, providing tailored guidance at scale, and helping them reach their full potential.

• Conversational AI Student Assistant
  Help students deepen their understanding of topics by guiding them through a collaborative learning process. Instead of just providing answers, it empowers students to think critically, engage with the material, and find solutions on their own, fostering long-term comprehension and academic success.

• AI-powered Progress Tracking & Recommendation Engine
  Our advanced recommendation engine allows students to carefully assess gaps and areas for improvement taking into account study materials and exam topics. This makes sure that they can invest time into the right topics but also to build confidence by tracking progress over time.

• Support for Multi-Modal interactions
  Simple text-based interactions are not enough to ensure true learning progress. Our AI Student Assistant uses multimodal models to understand and reason over charts, images, and text to provide more robust guidance on the course material. Voice models can be included to collect speech input which helps students to really practice new language skills, as well as speech output to help with pronunciations or learning on the go.

This powerful Generative AI solution was built with:

• Advanced GenAI Models are fined-tuned using your data and human subject matter expert data from the Scale Data Engine. Models are fine-tuned to your educational terminology, corpus of educational content, and database schemas. These models are combined with our state-of-the-art RAG pipelines to produce a highly accurate student assistant grounded in your materials.
• State-managed agentic workflows for reasoning against complex constraints.
• Bespoke prompt engineering and turning, including in-context learning, few-shot learning, and task decomposition.