Building voice analytics tools and conversational AI used to require years of telephony experience. Now, it's accessible via API.
Voice Analytics and Conversational AI platforms are growing at mind-boggling speeds.
Conversation intelligence platform Gong recently tripled its valuation, adding some 1.5 billion dollars in enterprise value. Live transcription platform Otter.ai has seen . Conversational AI provider Replicant is and has seen in five months.
Related articles
What's behind the success of these companies? A combination of timing and technological progress. The events of 2020 emptied call centers and offices, and rendered in-person meetings a remnant of bygone times. With communication now happening almost exclusively through a phone or computer, the professional world re-discovered the promise of artificial intelligence. Suddenly, AI was mature enough to generate real, actionable insights from conversations and affordable enough to be offered in a neat enterprise service package.
What if you could build telephony like you would build a web app—making simple API calls to execute the functions you need, and knowing that the back-end is taken care of?
Artificial intelligence startups may be hesitant to explore the Conversational AI and Voice Analytics space because they don't know telephony. It's understandable—why worry about complex telephony infrastructure, protocols like VoIP and SIP and telephony-centric languages when you could apply your AI to simple web apps much more easily?
Don't worry; we'll handle it
What if you could build telephony like you would build a web app⸺making simple API calls to execute the functions you need, and knowing that the back-end is taken care of?
With Telnyx, you can access every telephony resource you need to build captivating conversations, all via API. Our Voice API enables intuitive control over in-depth telephony functions, so your developers can focus on creating valuable insights for your users instead of squashing obscure telephony bugs.
What's more—our APIs run on our own private, global network. We built it from the ground up for real-time communications, with multi-cloud reliability and direct interconnects with Tier-1 telephony carriers across the globe. Simply plug into the Telnyx network and reliably reach your customers wherever they are.
Voice analytics is the extraction of useful data and insights from spoken conversations. You can glen insights like sentiment analysis, talk-time ratios, topic tagging and keyword alerting by analyzing the audio data from a conversation. In many cases, voice analytics is carried out over remote communications like phone calls or video calls, because these forms of communication can feed all of the call's audio to one endpoint for processing. Voice analytics is commonly used in transcription, revenue and sales intelligence and customer experience applications.
Here's a snapshot of some popular Telnyx voice features and how they empower voice analytics without the fuss:
Speech recognition is an immensely powerful tool for streamlining customer experience workflows, collecting information over the phone and enhancing the accessibility of phone and video conversations. With our new speech-to-text transcription tools, it's easily enabled with a single API command.
No more storing, accessing and parsing recordings to transcribe speech to text after the fact. No more relying on expensive third-party speech recognition libraries to generate your transcriptions. With Telnyx, everything is handled live on-call, delivered via webhook and guaranteed by a confidence score, so you can be sure about the accuracy of your transcriptions.
Watch a demo of our transcription tools in action-you can set everything up in less than five minutes!
Call media is the foundation for any AI or voice analytics use case. With Telnyx, you can access media post-call through on-demand programmable call recording, or in real-time through media forking.
Programmable call recording allows you to start, stop, pause and resume single- or dual-channel recordings in your desired audio format, at any point, in any call, all via API. Your recordings are stored securely in the cloud and accessible via API so you can extract call contents for analysis and learning.
You can also manage and delete recordings via API to keep full control over your data sets.
Post-call analysis is a powerful tool for creating voice insights, but real-time, in-call voice AI has shown even more robust growth in recent months. Embedding voice analytics into a live call unlocks futuristic applications like bespoke real-time transcription, AI voice responders and live in-call sentiment analysis. These immensely complex operations rely on ultra-fast processing of call audio through natural language processing (NLP) algorithms.
Luckily, the Telnyx Voice API removes a vast amount of complexity by allowing you to duplicate the media from any live call in real-time, send it through your AI and act upon the results, all while the call is ongoing. Thanks to our real-time communications network, media is delivered almost instantaneously, allowing for true real-time transcription or conversation.
All of this is accomplished with simple REST API commands, so you don't need to hire a telephony engineer to leverage world-class telephony in your app.
Done incorrectly, conversational AI can be confusing and disconcerting to end users. With Telnyx, you can ensure your customers stay informed at all times, and communicate critical information with programmable text-to-speech (TTS). By passing simple text strings into an API call, you can speak natural-sounding text in a wide range of languages and accents powered by Amazon Polly.
You can also build variables into your TTS strings to customize your customer experience, or play custom messages, tones and hold music from audio files to personalize your call flow.
With all of these features at the tips of your fingers via API, you can build futuristic, programmable Interactive Voice Response (IVR) menus for incoming calls. Simple commands allow you to gather and process inputs from your callers and route calls through your menu accordingly. Real-time media forking empowers your callers to speak their way through your menu instead of awkwardly pressing dial pad buttons.
There's a real opportunity to build the next generation of interaction with conversational AI and voice analytics. If you're tempted to get involved and want the flexibility to move as fast as the industry does, we can help. Telnyx provides an API-level black box to handle your communications layer so you don't need to hire telephony engineers—instead, you can focus on your customers.
Chat with a voice API expert today to find out how we can build together.
What is AI voice analytics? AI voice analytics is the process of extracting insights from spoken conversations by analyzing transcripts, acoustics, and interaction patterns. Teams use it to understand customer intent, measure sentiment and agent performance, and spot compliance risks.
How does AI voice analytics work? Systems capture audio, transcribe speech to text, and apply NLP plus acoustic analysis to detect keywords, topics, emotion, silence, and overlap. The platform then scores interactions, flags moments that matter, and feeds dashboards or downstream workflows.
How can you tell if a voice is AI-generated? Listen for overly consistent pacing, flat emotion, odd breath placement, and glitches on complex sounds that humans usually vary. Verification often combines anomaly detection with metadata checks, consent workflows, and source corroboration.
Can ChatGPT do voice AI? ChatGPT can handle voice input and produce spoken responses, and it can summarize or extract themes from transcripts. For production-grade analytics like diarization, prosody scoring, and real-time compliance, teams typically pair conversational models with specialized signal processing.
What are the top use cases and benefits of AI voice analytics? Common outcomes include faster QA, automated compliance monitoring, churn risk detection, sales coaching, and routing based on real-time sentiment. Insights can also guide proactive outreach, where MMS marketing supports richer follow-ups with visuals or short clips that reinforce the message.
How do you combine AI voice analytics with messaging data for omnichannel insights? Unify call transcripts, acoustic scores, and outcomes with ticketing, chat, and messaging threads in your CDP to see the full journey. Cross-channel reporting often pairs voice metrics with SMS vs MMS data models to capture both text-only and media-rich interactions.
How do teams operationalize voice analytics insights in real time? Set triggers that launch workflows when thresholds are met, such as escalating a call, opening a ticket, or sending a post-call summary. Many teams also deliver rich media updates through a programmable MMS API so supervisors or customers get context with images or clips immediately.
