Every time I get a call from an unknown number, I fear misunderstanding, ask nervously, 'Können wir vielleicht in Englisch sprechen?!,' and feel shame when they hang up—trapped in a relentless cycle of fear and self-blame after six years in Berlin.
— Leo Kaveh, an expat and German citizen

PROBLEM

Fear and Shame!

In a group classroom, speaking opportunities are scarce, and when they come, many hesitate—no one wants to risk looking foolish in front of their peers.

Online solutions provide plenty of knowledge, but they don’t teach you how to speak—it’s like trying to learn to fly a plane by just reading the manual!

We believe the biggest problem for adults learning a new language is the psychological barrier: fear and shame. These barrier make it difficult for adults to learn languages as naturally as children do.

The real challenge is breaking through the

The real challenge is breaking through the psychological barrier.

Dancer


Dancer

SOLUTION

Human Interaction & Procedural Learning

Practice builds competence. Competence fosters confidence. Confidence, in turn, breaks the relentless cycle of fear and shame!

Through our mobile app, students practice the language in real-world scenarios by interacting with the LLM on topics recommended by the Nira ML Model. These topics are customized based on their interests, CEFR objectives, and proficiency level.

Afterward, students engage in conversations with a Speaking Companion on the same topics they practiced with AI. The conversation data is fed back into the Nira ML Model, further enhancing the learning process.

Human Interaction

Groups of 1-3 students regularly meet online with a Speaking Companion, who could be a college student, waitress, homemaker, delivery person, or even a teacher.

Procedural Learning

Powered by the Nira ML Model and integrated with LLMs, we offer a highly efficient and personalized learning experience tailored to each user, with a strong focus on speaking.

Practicing with AI reduces psychological barriers, while engaging in human conversations helps to completely overcome them.

SOLUTION

Target Users

Nira School seamlessly blends learning with human interaction to create a comprehensive and engaging educational experience.

Student

Someone who needs to communicate but isn’t forced to learn the language—for example, an expat living in Berlin or an Indian graduate building their career in India. This group represents the majority of language learners worldwide.

Speaking Companion

A native or fluent speaker seeking extra income who values helping others and enjoys engaging with people. They need a flexible side job that fits around their primary occupation and offers competitive pay.



PRODUCT

Design Thinking Approach

V 0.1

First iteration

An old German story has been modernized and adjusted for level using LLM, with a human editor reviewing the content to ensure accuracy.

  • Interactive
    Students actively engage with the app by speaking or writing responses to questions.
  • Read-Listen content
    They can read the text while simultaneously listening to AI-generated audio, enhancing comprehension.
  • Data collection
    All user-generated data is collected and analyzed to refine the learning process using the Nira ML Model.

V 0.2

First pivot

User feedback revealed that while a story might be a beautiful piece of literature, it may not resonate with every student, making the content less engaging.

  • Dynamic content
    Content is tailored to the user’s interests, featuring up-to-date topics such as current events. Once a topic is selected, the content is dynamically generated. This approach significantly enhances user engagement.

  • LLM-based translation
    We have replaced Google Translate with LLM-based translation, delivering context-aware and highly nuanced results for more meaningful and accurate knowledge exchange.



V 0.3

Coming soon ...

Our observations showed that while dynamic content is engaging and relatable, it hasn’t led to sustained traction, with users leaving the app after a short time.

  • Learning course
    A structured course with a clear deadline focused on a specific learning objective is essential, serving as the primary milestone.
  • Speaking Companion
    Students should engage with the speaking companion. Isolation kills motivation.
  • Regular meetups
    Students should have regular weekly meetups. These sessions with the Speaking Companion serve as mini deadlines.


Data

The student generates data by speaking or writing responses to questions, which, along with feedback from the LLM, is collected and analyzed.

Interests

The model leverages the student’s interests and proficiency levels to guide LLM content creation and inform speaking companions on conversation topics for online meetings.

CEFR

The Nira ML Model aligns with the Common European Framework of Reference (CEFR), tailoring content to the student’s proficiency level.

Science

By integrating scientific principles of learning—such as Memory Reinforcement, Spacing, and Interleaving—the ML Model creates a personalized learning experience.

Nira ML Model

Future Of Learning

A powerful recommendation engine designed to facilitate efficient procedural learning by prioritizing optimized practice over cognitive knowledge. Trained on exclusive student-generated data, it seamlessly guides LLM-driven content creation.


The Nira ML Model suggests online meeting topics tailored to benefit all students and leverages spoken content to continuously enhance each student’s learning experience.

Waiting List

Join the future of learning





CONTACT US

Keep In Touch

Have questions or need assistance? We're here to help! Feel free to reach out to us anytime at contact@nirashcool.com, and our team will get back to you as soon as possible. Your feedback and inquiries are always welcome!