Zaion has developed its own ASR, NLU, SLM, and LLM models, optimized for conversational interactions in contact centers, which combine performance, speed, and accuracy.
Word Error Rate (WER)
25% off compared to generic models
Alphanumeric accuracy
+18% compared to standard ASRs
Latency
Automatic Speech Recognition
Speech recognition optimized for telephony and alphanumeric data (zip codes, contract numbers, license plate numbers).
Natural Language Understanding
Understanding of intents and entities trained on a domain-specific data bank to ensure accurate request routing.
Language models
A smart combination of Small Language Models and Large Language Models (LLMs) for summarizing, rephrasing, and analyzing content with domain-specific constraints.
Zaion trains and fine-tunes models using vocabulary, intent, and customer journey data from the insurance, banking, public sector, and energy industries, among others.
Integration of OpenAI, Anthropic, and Mistral for complex reasoning and flexible generation tasks, with cost control and hallucination management.
Pour les tâches répétitives et structurées, Zaion privilégie des modèles légers (<10B paramètres) pour la performance.
The platform natively supports voice (ASR → text → LLM → TTS) and text (chat, email) using a unified architecture.
Fine-tuning based on millions of real-world multichannel customer service interactions.
Each AI building block is independently optimized and intelligently orchestrated.
Hallucination detection, fallback, and automatic human escalation.
Insights are fed back into the system each month to retrain and refine the models.
