Amira is Science in Action

Amira isn’t your typical edtech reading program. Amira is a learning agent grounded in decades of neuroscience, reading science, and AI. Unlike traditional reading technologies, Amira listens as students read, responds in real time, and dynamically adjusts instruction based on what the student needs. 

‍

Amira is built on decades of brain research into how children learn to read. Amira’s design reflects how neural pathways for decoding, fluency, comprehension, and attention develop over time. Amira listens as students read, then applies models aligned with cognitive neuroscience, activating the regions responsible for phonological processing, orthographic mapping, semantic understanding, and executive function. This allows Amira to deliver instruction and tutoring that mirrors how the brain builds skilled reading.

‍

Amira is built on frameworks like Scarborough’s Reading Rope and Duke’s Active View of Reading. Amira supports explicit, systematic instruction in decoding, fluency, comprehension, and vocabulary, aligned with how reading skills develop in the brain.

‍

Yes. As students read aloud, Amira analyzes real-time behaviors—like miscues, hesitations, and fluency patterns—to deliver micro-interventions personalized to each student’s current cognitive profile.

‍

Amira is based on 30+ years of research from institutions like Carnegie Mellon and validated through studies in neuroscience, cognitive psychology, and reading development. Its design reflects how the brain processes language, memory, attention, and meaning-making.

‍

Amira supports students across reading levels, including early readers, multilingual learners, and those needing intervention. Amira’s feedback and scaffolds are designed to match each learner’s developmental stage and instructional needs.

How does Amira work for students with accents and/or speech impediments?

Amira is designed with inclusivity in mind. Its AI models are trained on a wide array of speech samples, including different regional accents, dialects, and speech characteristics. Amira achieves this by listening for the intended reading skills, not just perfect pronunciation which reduces flags for dialect differences. And rather than flagging students for speech patterns, Amira instead responds to reading miscues that will impact comprehension, decoding, or fluency. Additionally, Amira has been evaluated for performance across dialects, multilingual learnings, and students with speech or language difficulties to ensure every student is supported. 

Note: While Amira can accommodate a variety of speech patterns, it is not a diagnostic tool for speech or language disorders. Its role is to surface reading patterns, not replace SLP services. 

‍

Amira is intentionally designed to keep teachers at the center of learning. Every design decision reflects a commitment to ethical, transparent, and research-aligned use of AI in education. Amira’s models are trained on children’s speech and reading, ensuring every recommendation aligns with brain-based reading development. 

Amira operates on secure, private infrastructure, never shares student data with public AI platforms, and does not use data to train large language models. All student voice data is de-identified, used only for educational purposes, and remains fully under district control.

For Amira, responsible AI means protecting students, ensuring transparency, and staying grounded in the science of learning.

‍