Enterprise Voice AI platform for Speech-to-Text, Text-to-Speech, and Voice Agents
Neuro-symbolic AI for enterprise agents that combine language understanding with symbolic logic in one integrated runtime
Stage
Established
Established
Founded
2015
2017
Based in
US
US
Pricing model
Freemium
Contact for pricing
Pricing
Flux STT Streaming: $0.0065/min (Pay As You Go), $0.0057/min (Growth); Flux Multilingual Streaming: $0.0078/min (Pay As You Go), $0.0068/min (Growth); Nova-3 Monolingual Streaming: $0.0048/min (Pay As You Go), $0.0042/min (Growth); Nova-3 Multilingual Streaming: $0.0058/min (Pay As You Go), $0.0050/
Not given
Key features
Flux STT with turn detection and interruption handling
Nova-3 multilingual speech recognition in 50+ languages
Ultra-low latency under 300 milliseconds
Keyterm prompting with up to 90% higher keyword recall
Flux TTS with latency as low as 80ms
Speaker diarization and multi-speaker audio detection
Smart formatting with automatic punctuation and capitalization
Automatic redaction of sensitive information
Custom models for edge-case scenarios
Flexible deployment options: cloud, in-VPC, or self-hosted
One integrated runtime combining neural and symbolic systems
Deterministic policy enforcement before action
Complete execution trace for every turn
Natural language program authoring with code generation
Consistent decisions from identical inputs
CPU-based logic execution with lightweight language models
Managed service and custom enterprise deployment options
What makes it different
Conversation-aware speech platform with native turn-taking detection and interruption handling
Unified single API combining STT, TTS, and LLM orchestration to reduce complexity and latency
Flux TTS that thinks before speaking to maintain tone and expression across conversations
Enterprise-grade accuracy with custom vocabulary injection and industry-tuned models
Foundational AI company with research-driven innovation and continuous model improvements
Symbolic logic governs decisions instead of neural weights
Lower operational costs through CPU-based logic and lightweight models
Deepgram
Apollo-1