Fathom is an AI notetaking platform that records, transcribes, summarizes, and organizes meetings so users can stay focused on the conversation. The platform supports bot-based and bot-free capture, giving individuals and teams flexible ways to capture meeting notes. Fathom provides accurate transcripts, instant summaries, action items, follow-up details, and searchable meeting history. Users can ask questions across meetings, monitor key topics, and turn conversations into next steps for sales, customer success, marketing, and internal teams. Fathom integrates with tools such as Google Meet, Zoom, Microsoft Teams, Gmail, Slack, Salesforce, HubSpot, Notion, Asana, ChatGPT, Claude, Zapier, and public API or MCP workflows. Built for teams and individuals, Fathom helps reduce meeting admin, improve follow-through, and keep important decisions visible.
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Google Cloud’s Speech API processes more than 1 billion voice minutes per month with close to human levels of understanding for many commonly spoken languages. Powered by the best of Google's AI research and technology, Google Cloud's Speech-to-Text API helps you accurately transcribe speech into text in 73 languages and 137 different local variants. Leverage Google’s most advanced deep learning neural network algorithms for automatic speech recognition (ASR) and deploy ASR wherever you need it, whether in the cloud with the API, on-premises with Speech-to-Text On-Prem, or locally on any device with Speech On-Device.
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MAI-Transcribe-2-Streaming
MAI-Transcribe-2-Streaming is a low-latency streaming transcription model built for real-time speech applications, delivering transcripts in 60 languages with automatic, continuous language detection. Rather than waiting for someone to finish speaking, it produces initial partial transcripts just over 100 ms after receiving audio, revises them as more context arrives, and commits stable text quickly. This allows voice applications to begin reasoning, calling tools, or displaying live transcripts while a person is still speaking. Microsoft reports that the model ranks No. 1 for both final and partial transcript accuracy on Artificial Analysis. MAI-Voice-2.1 complements it with multilingual text-to-speech across 23 languages and 26 locales, allowing a single voice to switch languages while maintaining the same speaker identity and adopting native accents.
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