Leadlock
Leadlock is a speech-to-speech voice AI platform built specifically for GoHighLevel agencies, helping them answer every call, qualify leads, book appointments, and update GHL pipelines in real time. Unlike traditional voice AI stacks that chain speech-to-text, an LLM, and text-to-speech, it supports true multimodal speech-to-speech through OpenAI Realtime and Gemini Live, alongside xAI Grok and ElevenLabs options, enabling sub-second latency, natural turn-taking, and interruptions. Agencies can choose from more than 72 voices across multiple providers and select different models for different agents and use cases. Native GoHighLevel integration connects contacts, calendars, pipelines, opportunities, tags, custom fields, workflows, and sub-accounts without middleware or Zapier-style glue. Before answering, agents can pull caller history and CRM context to personalize conversations from the first ring.
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Grok Voice 3.0
Grok Voice 3.0 is a speech-to-speech model offered through the Grok Voice Agent API for developers building real-time voice applications. It accepts audio and text and returns spoken audio or text through a WebSocket session, supporting conversational turn-taking, interruptions, and function calling. Developers can connect the model to custom functions and server-side tools, including web search, X search, collections, and remote MCP servers. The API is intended for interactive voice agents such as customer-support and service-call experiences, and is also used for voice interactions in Tesla vehicles and Grok Bot. Billing is usage-based, with audio charged per minute and text input events billed separately. The API documentation includes setup instructions and examples for Python and JavaScript clients.
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Inworld Realtime STT
Inworld Realtime STT is a realtime streaming STT API that understands users beyond their words. It combines low-latency speech recognition with voice profiling, extracting emotion, vocal style, accent, age, and pitch directly from raw audio so downstream LLMs and TTS systems can respond with more adaptive, expressive behavior. Developers can stream audio in real time, transcribe complete files, or extract voice profile signals through one unified API, with realtime bidirectional streaming over WebSocket, synchronous transcription for full audio files, voice profile signals on every streaming chunk, and multi-provider support through a single model ID. Every audio chunk can produce a realtime profile of the speaker with confidence scores, giving LLMs structured context such as whether a user sounds sad, frustrated, soft, high-pitched, or calm.
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GPT-Realtime-2.1
GPT-Realtime-2.1 is OpenAI’s reasoning model with tool use for low-latency voice agents and complex speech-to-speech workflows. It updates GPT-Realtime-2 with improved alphanumeric recognition, silence and noise handling, and interruption behavior, helping applications understand spoken code, manage imperfect audio, and respond more naturally when users pause or talk over the agent. Developers can configure reasoning effort to balance deeper thinking against latency and output usage, while strong instruction following helps the model stay aligned with a defined role, tone, and workflow. It accepts and produces both audio and text, can take images as input, and supports function calling so an agent can retrieve information or perform actions during a conversation. The model has a 128,000-token context window, supports up to 32,000 output tokens, and includes reasoning-token support for extended interactions.
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