Voice and speech AI platforms enable enterprises to convert, analyze and generate human speech at scale: from real-time phone agents and contact-center automation to meeting transcription, conversation intelligence and localized text-to-speech. As of late 2025, organizations prioritize accuracy, latency, multilingual support, privacy/compliance and integrations with CRM and collaboration tooling when selecting a solution. Key categories include Voice Synthesis and Transcription (realistic TTS, voice cloning, automated captions), Text-to-Speech APIs (dubbing, voice customization), Conversation Intelligence (call analytics, sentiment and action-item extraction) and AI Meeting Assistants (summary, follow-ups, searchable recordings). Representative platforms illustrate these use cases: ElevenLabs for high-fidelity TTS, voice cloning and voice-agent pipelines; Murf AI for multilingual TTS and dubbing; Fireflies and Recall.ai for meeting capture, transcription, summaries and metadata; Krisp for noise suppression, real-time transcription and audio quality features; ZenCall.ai, Simple Phones and OpenCall AI for AI phone agents and automated call handling (with HIPAA-capable options noted for healthcare workflows). Voize and Freya represent the growing class of enterprise-focused voice analytics and agent platforms that combine speech-to-text, LLM-driven intent understanding and text-to-speech response generation. When evaluating vendors, enterprises should weigh transcription accuracy, model governance, latency and deployment options (cloud, hybrid, on-device), privacy/consent for voice cloning, security/compliance (HIPAA, SOC2), and ecosystem integration (Zoom/Teams, CRMs). The current trend favors composable stacks—specialized APIs (capture/transcribe, conversation intelligence, TTS) stitched into platform workflows—allowing teams to balance quality, cost and regulatory requirements without overcommitting to a single monolithic provider.