Overview

Velma Voice Analytics API, a product from Modulate, is designed to analyze and interpret emotion, tone, and intent from voice conversations. Rather than focusing solely on transcription, Velma is an audio-native model, listening to the voice conversation directly and analyzing the acoustic signals that carry the conversation's meaning.

This tool turns voice conversations into actionable signals and behaviors. It can process both live streams and recordings, integrating with third-party tools.

One of Velma's unique features is its ability to analyze behaviors and escalate risks. A typical application includes alerting to potential risks like fraud or impersonation scams, with each alert including data on the type of threat and confidence level.

The tool can recognize a range of emotions expressed by speakers - from frustrated and anxious to calm and confident. Through its Audio-native Ensemble Listening Model (ELM), Velma is capable of understanding the nuances in conversation typically lost in other models that rely heavily on pure word transcription.

Velma aims to capture more than just words; it seeks to understand the full spectrum of a conversation, even to the point of detecting deepfake voices or spoofed calls.

The tool offers comprehensive conversation summaries, listing detected key behaviors, speaker topics, speaker emotions, and sentiment analysis among others.

This makes it a suitable tool for various use cases like fraud prevention, policy enforcement, voice agent understanding, and user safety among others across industries like customer experience centers, IT & helpdesk, gaming & social, and financial services.

With these detailed insights, Velma can contribute to better decision making and problem-solving in these settings.

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Velma API by ModulateInitial

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Initial release

June 29, 2026

Initial release of Velma API by Modulate.

Author

Modulate AI

@kirsten-a

Company

Modulate

🇺🇸 United States

Stats

5 tools

Beginner

Joined: February 2026

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Freemium

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$1.25/unit

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Pay-as-you-go

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Voice recognition Velma API by Modulate

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Pros and Cons

Pros

Analyzes emotion, tone, intent

Audio-native model

Processes live streams and recordings

Third-party tool integration

Risk escalation

Alerts for potential risks

Detailed threat data

Wide range of emotion recognition

Audio-native Ensemble Listening Model

Detects deepfakes and spoofed calls

Comprehensive conversation summaries

Applies to various use cases

Suitable for diverse industries

Influences decision making and problem-solving

Fraud and impersonation scam detection

Behavior analysis

Analyzes speaker topics and emotions

Performs sentiment analysis

Enhances user safety

Helps in policy enforcement

Financial services application

Helps understand voice agents

Detects key behaviors in conversation

Offers customer experience analytics

Useful in gaming and social

Assists in fraud prevention

Contributes in problem solving

Helps in decision support

Helps in IT & helpdesk

View 24 more pros

Cons

May not understand context

Potential false positives

Dependent on acoustic quality

Problems with overlapping voices

Limited behavioral analysis

Misinterpretation of speaker dynamics

Possible language dependency

Weak in noisy environments

Needs specific integration

Varying accuracy across accents

View 5 more cons

Q&A

What is Velma API?

Velma API is a product from Modulate, designed to analyze and interpret emotion, tone, and intent from voice conversations. Instead of focusing solely on transcription, this product encompasses voice recognition, voice analysis including emotion detection, tone analysis, intent analysis, and risk escalation. It is also used for detecting fraud and impersonation scams, and offers robust behavior analysis. Velma API operates as an audio-native model and can process live streams and recordings, integrating seamlessly with third-party tools.

How does Velma API recognize a range of emotions expressed by speakers?

Velma API recognizes a range of emotions by listening to the voice conversation directly and analyzing the acoustic signals. Instead of relying on the words that are said, Velma uses its Audio-native Ensemble Listening Model (ELM) to understand the nuances typically conveyed through tone of voice and speech patterns. This methodology enables it to identify emotions ranging from frustration and anxiety to calm and confidence.

Can Velma API process live streams and recordings?

Yes, Velma API is capable of processing both live streams and recordings. This flexibility allows it to be utilized in a variety of real-time and post-event analytical applications.

Can Velma API integrate with third-party tools?

Yes, Velma API has the ability to integrate seamlessly with third-party tools. This capability enhances its versatility in different technological ecosystems.

What is Velma API's unique feature of analyzing behaviors and escalating risks?

Velma API has a unique feature of not just detecting behaviors but also escalating risks. It uses its comprehensive emotion, tone, and intent analysis capabilities to alert users on potential risks like fraud or impersonation scams in real-time. In essence, it transforms voice conversations into actionable alerts on risky behaviors.

How does Velma API alert to potential risks like fraud or impersonation scams?

Velma API alerts on potential risks like fraud or impersonation scams by analyzing the nuances of voice conversations and their implicit meaning through its Audio-native Ensemble Listening Model. As a result, it can detect risky behaviours and make real-time alerts to help mitigate these threats.

+ Show 14 more

What does each alert from Velma API include?

Each alert from Velma API includes data on the type of threat and the confidence level. This provides a comprehensive picture of the risk level and assists in immediate decision making.

What is Velma API's Audio-native Ensemble Listening Model (ELM)?

Velma's Audio-native Ensemble Listening Model (ELM) is a technology that allows it to comprehend the nuances in conversation that are typically lost in other models that rely heavily on pure word transcription. ELM analyzes the acoustic signals, captures meaning beyond words and provides a more complete understanding of voice conversations.

What is the purpose of Velma's deepfake voice or spoofed calls detection feature?

The purpose of Velma's deepfake voice or spoofed calls detection feature is to provide an additional layer of security and authenticity in voice interactions. By detecting artificially synthesized or impersonated voices, Velma API ensures that voice communications stay true, trusted and free from potential fraud or misinformation.

What does the comprehensive conversation summaries from Velma API contain?

The comprehensive conversation summaries from Velma API contains detected key behaviors, speaker topics, sentiment analysis, and speaker emotions. These summaries provide a clear, easy-to-parse overview of every conversation, making it a valuable source of insights and action points.

What are the possible use cases for Velma API?

Possible use cases for Velma API include fraud prevention, policy enforcement, voice agent understanding, and user safety. It can be used in contexts requiring high-level voice analysis, such as customer experience centers, gaming and social platforms, financial services to name a few.

Which industries can benefit from Velma API?

Industries that can benefit from Velma API range from customer experience centers to IT & helpdesk, gaming & social platforms, and financial services. Any industry seeking comprehensive voice analysis, emotion detection, fraud detection, and more, can leverage the powerful features of Velma API.

Can Velma API provide actionable signals from voice conversations?

Yes, Velma API does turn voice conversations into actionable signals and behaviors. By interpreting emotion, tone, and intent from voice conversations, Velma API can provide accurate and useful insights, allowing for measured actions based on voice interactions.

How does Velma API contribute to better decision making and problem-solving?

Velma API contributes to better decision making and problem-solving by providing detailed insights derived from voice conversations. By understanding conversation nuances and detecting behaviors, risk factors and emotions, decision-makers can have a more profound understanding of the situation, leading to more accurate and efficient problem-solving.

What does Velma API's voice analysis entail?

Velma API's voice analysis entails critical aspects like emotion detection, tone analysis, and intent analysis. By listening and analyzing the voice conversation directly, it's capable of capturing and interpreting data beyond the verbal content.

What role does Velma API play in fraud detection and prevention?

Velma API plays a significant role in fraud detection and prevention. It can alert to potential risks such as fraud or impersonation scams by analyzing voice conversations and behaviors in real time. This alert includes data on the type of threat and the confidence level, helping to prevent this type of fraudulent activity.

What capabilities does Velma API offer for Sentiment Analysis?

Velma API uses its advanced analysis capabilities to provide a nuanced view on sentiment. It not only identifies the basic sentiment of the conversation but also breaks this down to understand how each speaker contributes to it. This means metrics for individual speaker emotions and overall sentiment can be extracted and analyzed.

How does Velma API analyze Tone and Intent?

Tone and intent analysis in Velma API is powered by the Audio-native Ensemble Listening Model. This model allows Velma to extract the tone and intent from voice conversations by analyzing the acoustic signals. It captures not just the spoken words, but the way they are said, which often carries critical information about the conversation's intent and the speakers' emotional state.

What does it mean that Velma API is an audio-native model?

Being an audio-native model means that Velma API interprets emotion, tone, and intent directly from the audio signals in voice conversations. Unlike many conventional models which rely heavily on textual transcription, Velma API focuses on the non-verbal elements carried in the acoustic signals to understand conversation dynamics, making it a more comprehensive tool to analyze voice interactions.

Can Velma API detect deepfake voices?

Yes, Velma API can detect deepfake voices. Its sophisticated audio analysis techniques enable it to determine if a voice has been artificially generated or manipulated. This feature plays an important role in ensuring the authenticity of voice interactions and guarding against possible deepfake voice-based scams.

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Velma API by Modulate

Overview