Powerful, flexible, and human-sounding AI voice agents for enterprise call automation
Portable context for terminal coding agents
Stage
Startup
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Founded
2025
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Based in
IN
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Pricing model
Freemium
Open source
Pricing
Usage-based: $0.07-$0.31 per minute for AI voice agents, $0.002+ per message for AI chat agents. Components: Voice infrastructure $0.055/min, Text-to-speech $0.015/min (varies by provider), Language models $0.003-$0.160/min, Telephony $0.015/min. Monthly subscriptions: Phone number $2/month, Concurr
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Key features
Real-time voice orchestration with concurrent call handling at scale
No-code visual agent builder with drag-and-drop workflows
LLM-powered simulation testing for edge-case validation
Real-time CRM integration and data synchronization
Pre-built agent templates for 22 industries
Multilingual support in 42+ languages
HIPAA and GDPR compliance with data residency options
Enterprise-grade infrastructure with 99.99% uptime and 6-region deployment
Unified call analytics and sentiment tracking dashboard
Outcome-based pricing for qualified leads and booked appointments
Context Ledger for curating admitted instructions, files and memory
Deterministic context admission before model processing
Workflows with Mother agent team design and checking
Love Spot drawing board with Matilda companion
Desktop app with theme customization
Support for GPT, Claude and Gemini models
Terminal and desktop app sharing state
Portable context for terminal coding agents
What makes it different
Real-time data sync and CRM writeback with 384ms latency instead of manual data entry
Pay only for outcomes achieved (early access) instead of minutes consumed
Pre-built templates for 22 industries with 49 ready-to-deploy playbooks
3.4x higher connect rate compared to traditional dialing
Deploy production-ready agents in under 30 minutes without infrastructure setup
Deterministic context admission ensures agents see processed context before model receives it
Context Ledger provides transparent curation of agent inputs
Mother agent orchestrates multi-agent workflows with checking and merged results
Finn
Elpis