At Sorise Tech, we revolutionize the learning experience by integrating advanced AI technology.
Teacher’s have tons of pastpapers to mark every year
All schools don’t have the same level of experienced teachers evaluating. it lacks standard.
Teachers are unable to focus 100% on improving students level due to the burden.
Students are receiving their pastpaper evaluation each year without proper guidelines
Students have to wait for a alengthy period of 2 to 3 days to have them evaluated.
Costs parents huge amount of money to have them evaluated from professional teachers.
You should choose Sorise for multiple reasons as it transforms past paper evaluations by offering a streamlined, cost-effective solution that benefits both students and teachers. It also reduces the heavy marking workload for teachers, ensures consistent, high-quality assessments, and provides students with clear, timely feedback.
With Sorise, teachers can focus more on personalized instruction, and students get faster, more detailed evaluations, as Sorise helps them. The need for expensive professional evaluations is eliminated. Choose Sorise for efficient, fair, and accessible academic support.
Initially, Sorise aimed to provide concise answers to every question. However, after research and feedback from Cambridge professors, we realized this approach lacked the necessary depth for full understanding. This prompted us to shift towards responses that are both accurate and contextually rich.
To improve overly simplistic answers, we integrated the Cambridge Marking Scheme (CMS) into Sorise. This ensures responses align with academic standards and exam criteria, offering detailed, relevant guidance. Students now receive accurate, tailored support to help them score higher and be better prepared for their exams..
We faced a challenge integrating PDFs into our database, which only accepts formats like Excel or JSON. To resolve this, we extracted relevant data from the PDFs and converted it into a structured format compatible with the system. This ensured data integrity while enabling seamless integration into our database.
To solve the PDF integration challenge, we used Python and AI algorithms to extract and process data from the PDFs. Machine learning models ensured accuracy and efficiency during extraction, which was then converted into Excel format for database compatibility. This approach enabled seamless integration of previously unmanageable PDF content.
Education isn’t one-size-fits-all. Different learners have unique needs, learning styles, and preferences.
Flexibility across a wide variety of devices, operating systems, and large and small scree
Managing updates and changes in code without disrupting user experience.
97% accuracy in finding feedback for objective and descriptive answers. Also, approved by Cambridge professors.