B2B SaaS Provider · vs · MarTech Vendor
Deepgram vs Murf AI
Structured technology and market comparison · 2026
Direct Feature Comparison
Deepgram · vs · Murf AIVoice AI APIs for speech, voice agents and audio intelligence.
Voice AI software for speech generation, dubbing and voice agents.
Analyze all overlapping signals and tech stacks for Deepgram and Murf AI
Compare mutual enterprise clients, monetization models, live market signals, and partner networks directly in the interactive Knowledge Graph.
Comparison Analysis
What is the main difference between Deepgram and Murf AI?
When comparing Deepgram and Murf AI, both platforms operate within the Conversational AI & Chatbots, Chat & Conversational UI, and Large Language Models (LLM) & AI ecosystem. Deepgram is positioned as Voice AI APIs for speech, voice agents and audio intelligence, whereas Murf AI focuses on Voice AI software for speech generation, dubbing and voice agents. Decision-makers evaluate both solutions when orchestrating their commercial monetization and technology stack.
What are the top alternatives to Deepgram and Murf AI?
When evaluating Deepgram and Murf AI, enterprise buyers also consider other platforms in Conversational AI & Chatbots, Chat & Conversational UI, and Large Language Models (LLM) & AI. You can discover the full competitive landscape and evaluate other alternatives by viewing their respective footprint profiles on Polaris7.
How do the corporate scale, structure, and headquarters of Deepgram and Murf AI compare?
Deepgram is headquartered in United States (founded in 2015) with 201–500 employees. Murf AI is based in United States (founded in 2020) with 50–200 employees. Complete ownership, subsidiary trees, and corporate affiliations are documented across Polaris7.
Market Signals
Recent Market Signals & Activity: Deepgram vs Murf AI
Documented market movements, strategic partnerships, product releases, and regulatory developments mapped across Polaris7.
Deepgram
Recent Signals
- ·techcrunchM&A
Deepgram acquires Daily to bolster voice AI infrastructure
Deepgram, a leading provider of speech-to-text and voice AI models, has announced the acquisition of Daily, the company behind the popular open-source voice AI framework Pipecat. The financial terms of the deal were not disclosed, but Deepgram has committed to keeping Pipecat open source. Pipecat manages voice and video streams, integrating STT, LLMs, and TTS while reducing latency. Deepgram aims to leverage Pipecat to enhance its real-time voice and video infrastructure, allowing developers to build expressive voice agents with pluggable models. Additionally, Deepgram is launching the Real-Time Context Standard (RCS), an open protocol co-developed with the Pipecat team, to standardize metadata in voice AI interactions. Daily had raised over $62 million from investors like Tiger Global and has been part of Y Combinator, like Deepgram.
- Deepgram acquires Daily, maker of open-source voice AI framework Pipecat
- Deal amount undisclosed; Pipecat remains open source
- Daily had raised over $62 million from Tiger Global and others
- ·DEV CommunityConversational AI & Chatbots
Developer Builds Multilingual AI Voice Agent 'Sadie'
A developer, Ayush Shinde, built Sadie — a multilingual AI voice agent — during the "10 Days of AI Voice Agents — #VoiceForBharat Edition" challenge. Over ten days he implemented real-time voice conversations, Hindi-English code-mixing support, persistent (permissioned) memory, tool integration, outbound phone calling via SIP, human escalation via Discord webhooks, an analytics dashboard, and multi-agent specialist handoffs (grammar, maths, full-stack). The system integrates LiveKit for real-time transport, Deepgram for STT, Google Gemini as the LLM brain, and Murf Falcon for TTS, with SQLite for memory and Next.js/Chart.js for analytics. The post documents architecture, implementation details, encountered bugs (telephony SIP encryption, logging issues, import paths), and instructions to run the public repository and demo.
- Ayush Shinde built an AI voice agent named Sadie during the "10 Days of AI Voice Agents — #VoiceForBharat Edition" challenge.
- Sadie supports real-time voice, Hindi-English code-mixed conversations, permissioned persistent memory (SQLite), external tool integration, outbound phone calls, human escalation, analytics, and specialist agent handoffs.
- Core technical stack includes LiveKit (real-time audio), Deepgram (Speech-to-Text), Google Gemini (LLM), Murf Falcon (TTS), SQLite, Next.js, and Chart.js.
- ·DEV CommunityConversational AI & Chatbots
10-Day AI Voice Agent Stops Scam Calls
A developer built 'Suraksha Saathi', an AI voice agent prototype to help families detect and respond to scam calls in 10 days. The agent uses Deepgram for speech recognition, a Google Gemini model for reasoning, Murf AI's Falcon TTS for fast speech output, and LiveKit for real-time connectivity. Features include Hindi support via Devanagari-only output, a consent-based memory to remember callers, a panic button that alerts a human fraud team via Discord, real-time scam tracking dashboard, and mid-call voice-engine handoffs to escalate to an investigator persona. The author published the post on DEV and shared source code on GitHub.
- Author built an AI voice agent named Suraksha Saathi in 10 days.
- Architecture: Deepgram (ASR) → Google Gemini (LLM) → Murf AI Falcon (TTS) → LiveKit (real-time audio).
- Agent enforces Hindi output in Devanagari, implements consent-based memory, and a panic button that notifies a human fraud team via Discord.
Murf AI
Recent Signals
- ·DEV CommunityConversational AI & Chatbots
Bharat Buddy: 10-Day Voice AI Tutor Build
A developer built "Bharat Buddy," a multilingual voice-first AI tutor during the "10 Days of Voice Agents — VoiceForBharat Edition." The project integrates real-time audio via LiveKit, LLM reasoning, and Murf Falcon TTS to support Hindi, English and Hinglish. Features include user memory, tool calling, AI-initiated outbound calls, human escalation, specialist agent handoffs (e.g., a Maths Practice Specialist), and a simple call-analytics dashboard backed by SQLite. The author documents technical challenges (function-calling schema mismatches, secret management) and publishes the project repository on GitHub.
- Bharat Buddy is a multilingual voice tutor that supports Hindi, English and Hinglish and is voice-first.
- The project uses LiveKit for real-time voice communication, an LLM for reasoning, and Murf Falcon (Murf AI) for text-to-speech.
- Implemented features include memory, tool calling, AI-initiated outbound calls, human escalation workflows, specialist-agent handoffs, and call analytics stored in SQLite.
- ·DEV CommunityConversational AI & Chatbots
Voice AI Assistant for Indian Farmers Built in 10 Days
A developer built "Farm & Field," a voice AI assistant for Indian farmers during the 10 Days of Voice Agents — VoiceForBharat Edition by Murf AI. The system integrates Speech-to-Text, an LLM, Text-to-Speech, and real-time transport (Deepgram, Google Gemini, Murf Falcon, LiveKit) with SQLite-backed memory, weather and market-price tools, human escalation, a specialist crop agent, outbound calling via LiveKit SIP, and call analytics. The agent supports Malayalam, English, and Manglish, requests consent before storing memory, and hands off to humans or specialists when appropriate. The project code is available on GitHub.
- Author built Farm & Field during the 10 Days of Voice Agents — VoiceForBharat Edition by Murf AI.
- Core stack: Deepgram (STT), Google (Gemini) for LLM, Murf Falcon (TTS), and LiveKit (real-time transport).
- Features include multilingual Malayalam/English/Manglish support, memory-with-consent, weather and market-price tools, human escalation, and a Crop Problem Specialist agent.
Compare their exact ecosystem overlaps.
Explore all deep relationships in Polaris7. Discover exactly which mutual clients, integrated technologies, and overlapping partners Deepgram and Murf AI share across the market ecosystem.
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