Inside Praktika's conversational approach to language learning
January 22, 2026 at 5:00 AM
Summary
TL;DR
Praktika evolved from a single-model tutor into a multi-agent system with a persistent memory layer and speech-first UX. A new long-term memory system correlated with a 24% Day-1 retention lift and doubled revenue.
What actually happened
The founders built Praktika to address the gap between classroom English and real speaking confidence.
The product shifted from rule-based NLP/early models to GPT-era conversational tutoring.
The architecture moved from a single agent to multiple specialized agents coordinating a lesson loop.
Memory and speech recognition were treated as core interaction mechanics, not add-ons.
Key numbers
24% increase in Day-1 retention after introducing long-term memory.
Revenue doubled in a few months after the memory change.
Millions of learners.
Nine languages supported.
Why this was hard
Learners need real-time adaptation; scripted flows break when confidence and context shift.
Relevant memory must reflect “what just happened,” not stale history.
Non-native speech includes hesitations and restarts that typical fluent-speech systems mishandle.
Balancing conversation quality, pedagogy, and efficiency requires parallel reasoning.