Welcome to issue #33 of our recently launched Q&A series, Startup Spotlight.

This series is all about diving into the world-class technological innovation conducted by exciting startups. Getting to grips with the technology, the mission, and even the stories behind them.

In each edition we sit down with a different startup founder, leader, or operator in an easily digestible conversational style Q&A format.

Today we interviewed Rajeshwari Iyer & Kavitha Ravindran, Co-founders of sAInaptic, to find out more about the power of AI in interactive learning.


  • 💡 How sAInaptic use technology to reduce workload for teachers and improve grades for students
  • 💻 The company who believes that all students deserve access to personalised and interactive learning – without the hefty expense of a tutor
  • 🎓 From GCSE to A-Level and beyond: sAInaptics expansion plans create a brighter future for students and teachers

For many 15- and 16-year-olds across the country, studying for GCSE’s can be a daunting time. Getting the grades is stressful.

With teacher workloads bursting at the seams, it’s often impossible for all students in a class to receive personalised feedback, giving them little guidance on where or how to improve – ultimately affecting their end result. Some parents resort to hiring a private tutor, but for most, this is simply is out of reach.

sAInaptic identified this problem and decided to create a tool designed to make life easier for students, parents, and teachers.

Through a simple but clever web app, GCSE Science students can enjoy a completely personalised, interactive learning experience tailored to their abilities.

Thanks to sAInaptic’s trailblazing AI tech, they can practice exam-style questions aligned with the three main exam boards and will be given instant, teacher-like feedback providing helpful insights on how to progress – offering them a real chance at achieving the best possible grades.

And the important thing here is… it’s affordable. Genius, isn’t it?

It seems that sAInaptic have made a giant leap forward in the EdTech world, but what makes them stand out from other learning apps in an already flooded market?

What hurdles have they faced on their journey to date?

And finally, where next?

We asked, Rajeshwari and Kavitha answered. Here we go.👇

What is the mission of your company?

We are on a mission to solve two primary issues that face education today:

– disparity in student outcomes due to lack of accessible and affordable personalised education

– increased teacher workload and poor work-life balance

Today, personalised and interactive learning is available only to those who can afford expensive tutors, resulting in a growing divide in student achievements. Moreover, in a traditional school setting, it's impossible for teachers to give meaningful feedback to ALL of their students and within a reasonable time frame, let alone instantly and in the moment.

At the same time, teachers are struggling, spending 20% of their time marking student work, especially open-ended questions, often outside of their working hours! Marking is maligned with inconsistencies and collating data to derive meaningful insights on student performances is huge manual task.

sAInaptic's free-text automarking algorithm, wrapped up in a sleek web-app solves both these issues by providing instant, meaningful feedback for every student response. With open-ended questions, students learn in the moment and can course-correct.

It also returns homework and tests that have already been marked to a high level of accuracy along with class-level and student-level insights to teachers so they are equipped to target their teaching and focus on 1-1 interventions where needed.

sAInaptic's web-app is accessible on any device and offers personalised education at an extremely affordable cost. 

How are you using technology to help solve that problem?

sAInaptic's automarking engine is based on natural language processing, which is a type of artificial intelligence that 'understands' free text.

Our technology has been trained to mark GCSE Science questions of varying difficulty just as a teacher or examiner would. It has been fine-tuned to understand the language of Science (which in NLP world is different from plain English). For every open-ended question answered in our app, students receive instant predicted score and teacher-like feedback on aspects of their answer they were awarded marks for and a note on what they could have included to improve their answer. 

What's your unique selling point?

Our USP is automarking of open-ended questions.

The EdTech market is flooded with apps that deliver learning content in the form of bitesize videos and assess only on multiple choice questions. This is great but is leading to information overload and meaningless clicking through MCQ options.

Teachers and schools also do not have a choice but to rely on reducing their workload by setting automarked homework based solely on MCQs which unfortunately tests only recall and therefore assessing real grasp of knowledge consolidation falls back on labour-intensive tasks such as developing good open-ended questions and marking them.

sAInaptic provides an interactive tool where students can practice the art of constructing free text responses by actively recalling scientific concepts and applying that knowledge to open-ended questions and getting instant feedback on their performance so they can course correct, which is a scientifically proven technique to improving student outcomes.

For teachers, sAInaptic provides a bank of high quality exam-style questions which can be used for setting independent tasks, which does not add to the teacher marking work-load but also gives access to instant insights on student progress. 

What have been the greatest challenges to date?

One of the biggest challenges as an early-stage start-up, especially in the EdTech industry has been in raising awareness about our product, its accuracy and educating our stakeholders (teachers & students) that the AI will improve the more they use it.

We are still gathering evidence of the fact that the machine marks in a more standardised manner when compared to teachers and that its accuracy is well within the variability that is seen among teachers and examiners.

We have tried to keep the machine's marking and feedback very transparent so that teachers and students can see when the machine goes wrong and give them the ability to correct the machine in-app and during the course of their teaching & learning.

This has in fact resulted in a great feedback loop that helps us as a business to streamline our retraining of our algorithm and also helps in building confidence among students as they get to self-reflect (by comparing their answer to the model answer that we provide in-app).

So far we have received some fantastic feedback from teachers, parents and students and so think we have done well in overcoming these challenges. 😊

What major milestones have you achieved, and what's next!?

As a business, we raised a pre-seed round last year, without which, we would not be talking here today! The fundraise has helped us launch our revision product which was adopted by thousands of users in the days leading up to the exam season.

We are in the process of developing our school product which will be launched later this year – we have had some great feedback from the teachers who participated in our pilot programme and we can't wait to show them what is coming up next!

Once this is out of the way, we will be concentrating on growth and in making our algorithm more intelligent. This means that while the algorithm marks only seen questions right now, it will be intelligent enough to mark new unseen questions in the future. We will also be moving onto A-levels late next year.

Thanks, Rajeshwari!

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