Skill UI

A comprehensive SDK for building real-time, bidirectional voice AI applications using Azure AI services within the .NET framework. This library facilitates seamless voice interactions, supporting WebSocket communication, advanced features like function calling, and handling audio/text streaming events for developing sophisticated virtual assistants.

The Azure AI VoiceLive SDK for Java enables real-time, bidirectional voice conversations with AI assistants. Using WebSocket technology, this SDK supports low-latency streaming, advanced features like turn detection, noise reduction, and customizable voice selection (OpenAI/Azure). It is ideal for developers building sophisticated voice bots or interactive voice applications in Java.

This SDK enables the development of real-time, conversational AI applications using Azure Cognitive Services. It supports bidirectional communication via WebSockets, allowing for continuous audio streaming (mic input) and receiving synthesized speech output. Ideal for building voice assistants, IVR systems, and interactive voice experiences.

This SDK provides a comprehensive interface for building real-time, bidirectional voice AI applications using Azure AI services. It supports streaming audio input/output via WebSocket, handling transcription, text-to-speech, and complex session management. Ideal for developing robust voice assistants and interactive AI agents in both Node.js and modern browser environments.

This skill provides capabilities for bidirectional audio processing using fal.ai models. It supports Text-to-Speech (TTS), converting written text into natural-sounding speech, and Speech-to-Text (STT), accurately transcribing spoken audio into readable text. Use this skill for applications requiring high-quality audio input analysis or synthetic voice generation, such as virtual assistants, content digitization, or multilingual communication tools.

Comprehensive expertise in designing and implementing low-latency, production-ready voice AI applications and conversational agents. Covers the full stack from real-time audio streaming (WebRTC, LiveKit) to advanced NLU and speech synthesis (OpenAI, ElevenLabs, Deepgram). Ideal for building next-generation voice assistants, virtual call centers, and voice-enabled mobile experiences while optimizing for perceived responsiveness and latency budgets.

Auri is an advanced, next-generation voice assistant built upon Amazon Alexa and the powerful Claude AI model. Unlike traditional assistants, Auri conducts real, contextual conversations, enabling deep reasoning, remembering user context via DynamoDB, and providing natural, empathetic responses in Brazilian Portuguese. It elevates interactions from simple commands to complex, multi-turn dialogues requiring sophisticated natural language understanding.

AgentPhone is an API-first platform designed for developers building AI agents with advanced telephony capabilities. It allows agents to manage phone numbers, make/receive voice calls, and handle SMS messages. Developers can utilize hosted mode for simple AI interactions or webhook mode for custom, complex logic, making it ideal for building sophisticated customer support bots or virtual assistants.

This Java SDK enables real-time bidirectional voice conversations with AI assistants using WebSocket technology. It supports authentication via API Key or DefaultAzureCredential, configuration for audio input/output (24kHz PCM), voice selection (OpenAI/Azure), and event handling for session management and function calling. Ideal for building voice-enabled applications.

Build real-time voice AI assistants in JavaScript/TypeScript with Azure Voice Live SDK, supporting bidirectional WebSocket communication, audio streaming, VAD, transcription, and function calling.

Operate Famulor voice AI assistants, calls, campaigns, messaging, knowledge, telephony and workspace settings through the hosted Streamable HTTP MCP server. Discover live tools, pick the smallest toolset, verify changes, and respect authorization boundaries.

Voice agents enable natural human-AI conversation through speech recognition and synthesis. This skill covers low-latency architectures like speech-to-speech pipelines and STT-LLM-TTS workflows. It includes optimization strategies for sub-800ms response times, voice activity detection, and integration with tools like Deepgram, ElevenLabs, and OpenAI. Ideal for building production-ready voice assistants with natural interaction flows.