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Comparison · ai-assistants

LiveKit Agents vs Alhena AI

Side-by-side trajectory, velocity, and editorial themes.

L
LiveKit Agents
AI-ASSISTANTS
6.3

LiveKit ships a v1.0 turn detector, its clearest move on voice-agent latency

◆ Current state

LiveKit Agents is a framework for building real-time voice AI agents, releasing frequently against a growing roster of STT/TTS/LLM providers. The recent line pairs steady provider work (AssemblyAI, Gemini, Cartesia model updates and fixes) with two capability releases that matter: a v1.0 Turn Detector that uses audio and text semantics to decide when the agent should speak, and Asynchronous Tools that hand control back to the LLM while long-running work streams updates.

◆ Where it's heading

The direction is toward the hard, differentiating parts of voice agents: natural turn-taking and responsiveness under long-running tool calls. Around those, LiveKit keeps broadening provider coverage so teams can swap models freely. The framework is competing on conversation quality and latency, not just integrations.

◆ Prediction

Expect continued turn-detector refinement and more async/streaming primitives, alongside a steady stream of new STT/TTS/LLM provider support as models ship.

A
Alhena AI
AI-ASSISTANTS
6.3

Alhena moves its AI off the helpdesk widget and onto the product page

◆ Current state

Alhena is a commerce-native AI platform for ecommerce support and shopping assistance, and its headline move is Embeddable Agents — five embeddable shopping experiences that put a focused AI assistant directly on storefront pages where purchase decisions happen. Around that launch, the feed builds out the platform's operational depth: built-in A/B testing (Experiments), multi-agent Profiles, a role-based notifications system, and team permissions. The rest is positioning content contrasting commerce-native AI with generic helpdesk bots.

◆ Where it's heading

Alhena is pushing its AI upstream from post-purchase support into the pre-purchase conversion moment, embedding on product pages rather than living in a chat bubble. Paired with revenue-focused A/B testing and multi-brand profiles, the direction is to be measured on conversion and revenue lift, not deflection — planting the platform in the storefront's decision path.

◆ Prediction

Expect Alhena to expand the embeddable surface (more page types and placements) and lean on Experiments to prove revenue lift, positioning against helpdesk-first AI as commerce-native and conversion-driven.

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