How to Build an In-House AI Calling Stack (2026)
Engineering blueprint for building an in-house voice AI calling stack in 2026: LiveKit vs Pipecat, LiteLLM, Silero VAD v5, SIP trunking, and MCP self-learning.
VOICE AI & CALLING INTELLIGENCE
Discover architectural breakdowns, telephony benchmarks, and conversational AI strategies to scale your voice agents.
Watch a real AI-to-human handoff close a lead in under 3 minutes.
Engineering blueprint for building an in-house voice AI calling stack in 2026: LiveKit vs Pipecat, LiteLLM, Silero VAD v5, SIP trunking, and MCP self-learning.
A complete architectural guide to building an AI calling agent from scratch using Python, WebRTC, LiveKit, Deepgram, and Cartesia, compared against deploying in 2 minutes with Tough Tongue AI.
Compare LiveKit vs Pipecat for voice AI agents: WebRTC infrastructure vs pipeline frame processing, SIP scaling, barge-in latency benchmarks, and code tests.
A beginner guide to understanding the difference between raw model APIs and dedicated Voice AI frameworks.
Learn how to build a real-time, low-latency Voice AI agent in Python using LiveKit and OpenAI. From the core loop to production WebRTC architecture, this beginner guide has you covered.
Learn how to implement the Observer Pattern for building real-time guardrails in voice AI agents. Monitor for compliance violations, hallucinations, and off-script behavior without adding latency to the conversation.
Learn how to execute slow backend database lookups and API calls asynchronously in voice agents without stalling speech playback or introducing awkward conversation pauses.
A definitive guide on how real-time voice agents detect end-of-turn speech boundaries, prevent premature interruptions, and handle user barge-in instantly without robotic audio stutter.