Enterprise Voice AI platform for Speech-to-Text, Text-to-Speech, and Voice Agents
Connect your AI agent to App Store data
Stage
Established
Not given
Founded
2015
Not given
Based in
US
Not given
Pricing model
Freemium
Freemium
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/
Free tier: track rankings and competitors for one app with no card required. Grow plan: from $9.99/month per workspace, includes app integrations and MCP access. Investigate one app costs $9.99/month (up to three apps per workspace). Use LAUNCH code at checkout for 20% off while keeping the subscrip
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
23 MCP tools for iOS app analysis
Keyword ranking history by storefront
Competitor tracking and keyword overlap inspection
Apple Ads campaign data integration
RevenueCat subscription and revenue snapshots
Read-only Apple Ads tools
Hosted MCP endpoint with remote access
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
Maintains separate data boundaries between sources to avoid false attribution
Separates missing ranks from measured drops in analysis
Connects paid and organic data with revenue context in one investigation