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Built for speech-to-speech

DinoDial is the full-stack voice AI platform. Orchestration, observability, evals, and governance, built natively for speech-to-speech.

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THE REAL DIFFERENCE

Same problem, fundamentally different architecture.

LiveKit orchestrates STT → LLM → TTS. DinoDial was built for speech-to-speech from day one.

Enterprise ready

LiveKit requires AI devs and custom code. DinoDial is outcome-oriented — we handle the stack.

All-in-one

Observability, evals, and governance are baked in — not separate engineering efforts.

Future-proof

Speech-to-speech reduces latency and understands emotion. Three-pass loses that hop-by-hop.

HOW THEY COMPARE

DinoDial vs LiveKit Agents — out of the box

CategoryDinoDialLiveKit Agents
ArchitectureSpeech-to-speech nativeCascaded-first (multimodal added later)
AI observabilityLENS - unified infra + AI analyticsSession-level only (30-day retention)
Voice evalsDOJO - built-in, real audioThird-party required
AI guardrailsSENSEI - system-levelBuild your own
Engineering teamNo - opinionated platformYes - requires AI devs
THE HIDDEN COST

LiveKit is open-source. But production voice AI needs more than a transport layer.

LiveKit handles real-time audio well. But getting from "calls connect" to "calls work reliably at scale" requires a lot more — and that's where the real investment starts.

An engineering team to run it

LiveKit expects your team to manage API keys, orchestrate models, build state machines, and handle deployment. That's a significant investment for companies whose core business isn't AI infrastructure.

Observability beyond connection metrics

LiveKit Cloud offers transport-level monitoring. But knowing whether the connection held is different from knowing whether the conversation went well. Conversation-level observability is still something you'd need to build.

A testing and eval framework

There's no built-in testing layer — no adversarial scenarios, no campaign-specific evals. Most teams end up writing custom scripts or stitching together third-party tools that don't share context.

A governance and compliance layer

No guardrails, no human-in-the-loop workflows, no annotation system. For regulated industries, this is a significant gap to fill on your own.

Prompt management and agent evolution

LiveKit's guidance is to integrate with external tools like MLflow. Prompt versioning, model-specific formatting, and continuous agent improvement are left to your team.

Campaign intelligence and actions

No campaign-level visibility, no voice-driven queries, no actionable commands. Your campaign reporting depends on whatever your team has bandwidth to build.

Future-proof your voice AI stack.

See the full platform — orchestration, observability, evals, and campaign intelligence — built for speech-to-speech from day one.

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