Solutions  >  Education  >

Solutions in ed-tech, delivery, adaptive learning, using Artificial Intelligence.

Common Use Cases

As often said, education is the most powerful weapon which can be used to change the world. Data-driven technologies further can augment the speed, ability, and percision of educators. We can enable in-depth focus on student's performance, progress, and provide on-demand and personalized learning. By serving content with self-paced labs, customized curriculums, and focus on mastery-based learning, we can transparently assess a student's ability to utilize information, not just cram for a test. While automation and adaptive learning tools can reduce time constraints and improve content delivery, advances in natural language processing and deep learning methods allow for automated grading, response, and summarization of unstructured text and images.

SFL Scientific Solutions

SFL Scientific works in multiple areas at the intersection between education and technology We work on improving the way educational assessments are delivered, reported, and used to help each student learn. Our text extraction algorithms incorporate decades of experience and the world's cutting edge research. Below are other solutions we work on:

 Metacog human learning AI


Metacog Inc.




Analyze student input, time-series, and performance data and integrate with learning analytics platform.


Used time-series and NLP techniques in conjunction with supervised learning algorithms to extract key features from behavior and process data.

Tools & Technologies:

Python, NLP, Neural Networks, XGBoost, AWS.

 SFL Scientific is a AWS consulting partner for data science, big data, and artificial intelligence development..
 microsoft preferred service & machine learning partner

About Us

DISCOVER MORE: SFL Scientific is a data science consulting firm offering custom development and solutions, helping companies enable, operate, and innovate using machine learning and predictive analytics. We accelerate the adoption of AI and deep learning and apply domain knowledge & industry expertise in solving complex, R&D, and novel business problems with data-driven systems.