New unified platform combines AI voice agent automation with Real-time agent assistance and Auto QA, enabling healthcare payers to reduce average handle time (AHT) and improve first contact resolution (FCR) in their call centers.

IRVING, Texas and SAN FRANCISCO, Jan. 7, 2026 /PRNewswire-PRWeb/ -- Voicegain, a leader in AI Voice Agents and Infrastructure, today announced the acquisition of TrampolineAI, a venture-backed healthcare payer-focused Contact Center AI company whose products supports thousands of member interactions. The acquisition unifies Voicegain's AI Voice Agent automation with Trampoline's real-time agent assistance and Auto QA capabilities, enabling healthcare payers to optimize their entire contact center operation—from fully automated interactions to AI-enhanced human agent support.

Healthcare payer contact centers face mounting pressure to reduce costs while improving member experience. The reasons vary from CMS pressure, Medicaid redeterminations, Medicare AEP volume and staffing shortages. The challenge lies in balancing automation for routine inquiries with personalized support for complex interactions. The combined Voicegain and TrampolineAI platform addresses this challenge by providing a comprehensive solution that spans the full spectrum of contact center needs—automating high-volume routine calls while empowering human agents with real-time intelligence for interactions that require specialized attention.

"We're seeing strong demand from healthcare payers for a production-ready Voice AI platform. TrampolineAI brings deep payer contact center expertise and deployments at scale, accelerating our mission at Voicegain." — Arun Santhebennur

Over the past two years, Voicegain has scaled Casey, an AI Voice Agent purpose-built for health plans, TPAs, utilization management, and other healthcare payer businesses. Casey answers and triages member and provider calls in health insurance payer call centers. After performing HIPAA validation, Casey automates routine caller intents related to claims, eligibility, coverage/benefits, and prior authorization. For calls requiring live assistance, Casey transfers the interaction context via screen pop to human agents.

TrampolineAI has developed a payer-focused Generative AI suite of contact center products—Assist, Analyze, and Auto QA—designed to enhance human agent efficiency and effectiveness. The platform analyzes conversations between members and agents in real-time, leveraging real-time transcription and Gen AI models. It provides real-time answers by scanning plan documents such as Summary of Benefits and Coverage (SBCs) and Summary Plan Descriptions (SPDs), fills agent checklists automatically, and generates payer-optimized interaction summaries. Since its founding, TrampolineAI has established deployments with leading TPAs and health plans, processing hundreds of thousands of member interactions.

"Our mission at Voicegain is to enable businesses to deploy private, mission-critical Voice AI at scale," said Arun Santhebennur, Co-founder and CEO of Voicegain. "As we enter 2026, we are seeing strong demand from healthcare payers for a comprehensive, production-ready Voice AI platform. The TrampolineAI team brings deep expertise in healthcare payer operations and contact center technology, and their solutions are already deployed at scale across multiple payer environments."

Through this acquisition, Voicegain expands the Casey platform with purpose-built capabilities for payer contact centers, including AI-assisted agent workflows, real-time sentiment analysis, and automated quality monitoring. TrampolineAI customers gain access to Voicegain's AI Voice Agents, enterprise-grade Voice AI infrastructure including real-time and batch transcription, and large-scale deployment capabilities, while continuing to receive uninterrupted service.

"We founded TrampolineAI to address the significant administrative cost challenges healthcare payers face by deploying Generative Voice AI in production environments at scale," said Mike Bourke, Founder and CEO of TrampolineAI. "Joining Voicegain allows us to accelerate that mission with their enterprise-grade infrastructure, engineering capabilities, and established customer base in the healthcare payer market. Together, we can deliver a truly comprehensive solution that serves the full range of contact center needs."

A TPA deploying TrampolineAI noted the platform's immediate impact, stating that the data and insights surfaced by the application were fantastic, allowing the organization to see trends and issues immediately across all incoming calls.

The combined platform positions Voicegain to deliver a complete contact center solution spanning IVA call automation, real-time transcription and agent assist, Medicare and Medicaid compliant automated QA, and next-generation analytics with native LLM analysis capabilities. Integration work is already in progress, and customers will begin seeing benefits of the combined platform in Q1 2026.

Following the acquisition, TrampolineAI founding team members Mike Bourke and Jason Fama have joined Voicegain's Advisory Board, where they will provide strategic guidance on product development and AI innovation for healthcare payer applications.

The terms of the acquisition were not disclosed.

About Voicegain

Voicegain offers healthcare payer-focused AI Voice Agents and a private Voice AI platform that enables enterprises to build, deploy, and scale voice-driven applications. Voicegain Casey is designed specifically for healthcare payers, supporting automated and assisted customer service interactions with enterprise-grade security, scalability, and compliance. For more information, visit voicegain.ai.

About TrampolineAI

TrampolineAI was a venture-backed voice AI company focused on healthcare payer solutions. The company applies Generative Voice AI to contact centers to improve operational efficiency, member experience, and compliance through real-time agent assist, sentiment analysis, and automated quality assurance technologies. For more information, visit trampolineai.com.

Media Contact:

Arun Santhebennur

Co-founder & CEO, Voicegain

press@voicegain.ai

Media Contact

Arun Santhebennur, Voicegain, 1 9725180863 701, arun@voicegain.ai, https://www.voicegain.ai

SOURCE Voicegain

‍

Voicegain is releasing the results of its 2025 STT accuracy benchmark on an internally curated dataset of forty(40) call center audio files. This benchmark compares the accuracy of Voicegain's in-house STT models with that of the big cloud providers and also Voicegain's implementation of OpenAI's Whisper.

In the years past, we had published benchmarks that compared the accuracy of our in-house STT models against those of the big cloud providers. Here is the accuracy benchmark release in 2022 and the first release in 2021 and our second release in 2021. However the datasets we compared our STT models was a publicly available benchmark dataset that was on Medium and it included a wide variety of audio files - drawn from meetings, podcasts and telephony conversations.

Since 2023, Voicegain has focused on training and improving the accuracy of its in house Speech-to-Text AI models call center audio data. The benchmark we are releasing today is based on a Voicegain curated dataset of 40 audio files. These 40 files are from 8 different customers and from different industry verticals. For example two calls are consumer technology products, two are health insurance and one each in telecom, retail, manufacturing and consumer services. We did this to track how well the underlying acoustic models are trained on a variety of call center interactions.

Why a separate benchmark for Call Center Audio Data ?

In general Call Center audio data has the following characteristics

1. Narrowband: Most telephony systems used in call center encode the audio in a limited bandwidth 8 kHz format. Unless AI models are trained on such audio, the recognition accuracy can be limited.
2. Noisy data: There is significant background noise and over-talk in call center audio recordings.
3. Accents: Call Center agents work in different international locations. Even the end customers in the US have different accents. So the STT engine needs to be tuned to different accents.

Results of our Benchmark:

How was the accuracy of the engines calculated? We first created a golden transcript (human labeled) for each of the 40 files and calculated the Word Error Rate (WER) of each of the Speech-to-Text AI models that are included in the benchmark. The accuracy that is shown below is 1 - WER in percentage terms.

Most Accurate - Amazon AWS came out on top with an accuracy of 87.67%

Least Accurate - Google Video was the least trained acoustic model on our 8 kHz audio dataset. The accuracy was 68.38%

Most Accurate Voicegain Model - Voicegain-Whisper-Large-V3 is the most accurate model that Voicegain provides. Its accuracy was 86.17%

Accuracy of our inhouse Voicegain Omega Model - 85.09%. While this is slightly lower than Whisper-Large and AWS, it has two big advantages. The model is optimized for on-premise/pvt cloud deployment and it can further be trained on client audio data to get an accuracy that is higher.

Custom Acoustic Model Training

One very important consideration for prospective customers is that while this benchmark is on the 40 files in this curated list, the actual results for their use-case may vary. The accuracy numbers shown above can be considered as a good starting point. With custom acoustic model training, the actual accuracy for a production use-case can be much higher.

Private Cloud/On-Premise Deployment

There is also another important consideration for customers that want to deploy a Speech-to-Text model in their VPC or Datacenter. In addition to accuracy, the actual size of the model is very important. It is in this context that Voicegain Omega shines.

Additional Result of our Streaming Speech-to-Text

We also found that Voicegain Kappa - our Streaming STT engine has an accuracy that is very close to the accuracy of Voicegain Omega. The accuracy of Voicegain Kappa is less than 1% lower than Voicegain Omega.

Reproducing this Benchmark

If you are an enterprise that would like to reproduce this benchmark, please contact us over email (support@voicegain.ai). Please use your business email and share your full contact details. We would first need to qualify you, sign an NDA and then we can share the PII-redacted version of these audio call recordings.

‍