Voice AI to improve and protect human interactions

delight customers, lower cost, and prevent fraud in…

Banking Insurance Commerce Enterprise Security Financial Services Contact and Call Centers Healthcare Telecommunications Crypto
Voice AI

Introducing the first AI with contextual intelligence about the person. Real-time analysis of signals in the human voice, in any language, with a single API call


Studies show 90% of human communication is non-verbal. This challenges ‘voice-only’ interactions in customer care centers and with AI voice agents, leading to underwhelming customer service success or worse, fraud. Powered by custom-built AI models, our patent-protected solutions reveal gender, age and other non-verbal information about the caller - and deliver it in a fast, frictionless, privacy preserving manner - shedding light on the demographics of the caller, reducing fraud risk, improving outcomes and performance.

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Physiology, Not Speech Based:

Voice communicates so much more than words; holding critical information, distinctions, micro-features, and bio-markers unavailable elsewhere

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Privacy Preserving, Customer First Approach:

High fidelity, passive voice authentication without the need for personally identifiable information

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Language Agnostic, Text Independence and Real Time:

In only a few seconds, VoxEQ extracts valuable profile information about the speaker from the bio-signals generated from their voice, instantly. No special phrases or transcribing required

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No Voice Enrollees, No Problem:

VoxEQ provides results that can be used with, or without, voice prints on file

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Multi Factor:

VoxEQ provides critical insights by reading several different key signals, delivering higher accuracy than single factor solutions in the market today

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Review Past Calls:

Analyze existing enrolled or archived voiceprints in bulk batches or one-off to vet for fraudsters already ‘poisoning the well’

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Seamless Integration:

On-premises deployment or via the largest cloud-based Platform as a Service (PaaS) and Contact Center as a Service (CSaaS) providers

Transform Your Fraud Prevention, Customer Care and Conversational AI performance with Verify, Persona, and Prompt Solutions


 Multi-Factor, Voice-Based 3rd Party Impersonation Fraud and Synthetic (Deep-Fake) Identification for Customer Care Centers, In-house or Business Process Outsourcers for Financial Institutions, Insurers and other fraud targets

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Voice-Based Customer Segmentation and Demographic Insights of Unknown Callers for Commerce Enablement via Customer Care Centers, Work Force Management and Dynamic Script/Coaching providers

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Enrich LLM Prompts with caller/audience demographics to make AI voice agents smarter and optimize conversational AI outcomes in any industry

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We spend a lot of time talking to, and working with, large banks, insurers, online platforms, and others. They all have critical fraud and security issues and though there are products in market to help, many find that these products are not up to the task; too many false positives, too many false negatives, too opaque, too rigid in tuning for their specific business needs, or too large for the level of service or customization required. VoxEQ is different. Reach out for a demo, to discuss a pilot engagement or to learn more.

– Jack Caven, CEO, VoxEQ

Stay Updated with the Latest News and Updates from VoxEQ

Genesys App Foundry Verify Tile crop

Monday Jul 1st, 2024

VoxEQ’s voice AI fraud prevention and customer segmentation tools now available on Genesys AppFoundry

Verify, Persona and Prompt products, now available of the Genesys AppFoundry, improve and protect human interactions to prevent fraud, defend against fakes and delight customers at a lower cost. The first AI with contextual intelligence about the person, delivering real-time analysis of signals in the human voice, in any language with a simple API.

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Next Generation Customer Care Call Handling

Tuesday May 7th, 2024

Next Generation Customer Care Call Handling

CASE STUDY: The adoption of conversational AI and virtual agents is growing fast, fueled by Large Language Models (LLMs). Today, verbal input from the caller is converted to speech-to-text (STT), then used as a prompt for an LLM to inform its response.

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imposter fraud risk detection

Tuesday Apr 30th, 2024

Deploying the AI solution for imposter-fraud risk detection

CASE STUDY: When a US Federal Agency with insurance-like responsibilities investigated innovative technologies to improve and protect their call- based communications, it tapped AI tools from VoxEQ to identify risk factors early in the call to safeguard citizens, boost performance and improve outcomes.

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Monday Dec 11th, 2023

VoxEQ secures investment to bring voice AI breakthroughs to market, led by GOVO Venture Partners

VoxEQ, a provider of world class and proprietary artificial intelligence tools to understand the person behind the voice, today announced the addition of capital partners in its most recent funding round, led by GOVO Venture Partners

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Monday Jul 3rd, 2023

VoxEQ makes a voice analysis breakthrough, surpassing previous state-of-the-art systems for ‘age-from-voice’ prediction

VoxEQ, a provider of world class and proprietary artificial intelligence tools to understand the person behind the voice, today announced a breakthrough in “age from voice” prediction, besting the state of the art for accuracy by 2x

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The top 10 banks receive 44 Million calls a day, 29,000 will turn out to be fraud
VoxEQ's Verify offers the markets most accurate fraud prevention tools and defends against synthetics and other deep fakes
VoxEQ's Persona presents the most advanced demographics-from-voice capabilities for sales, marketing, call center agents and voicebots. Informs predictive agent routing, coaching and scripting - enabling and unlocking upselling and cross-selling opportunities
VoxEQ is sensitive to the privacy and fairness concerns of all who interact with our software and models. We don’t collect more data than we need to get the most accurate results from our models; we store and cross-index data responsibly
We ensure our models are trained in a manner that reduces bias; we don’t allow our models to be used in applications that may perpetuate bias or discrimination
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