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
Media Contact
Arun Santhebennur, Voicegain, 1 9725180863 701, arun@voicegain.ai, https://www.voicegain.ai
SOURCE Voicegain
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As we announced here, Voicegain Transcribe is an AI based Meeting Assistant that you can take with you to all your work meetings. So irrespective of the meeting platform - Zoom, Microsoft Teams, Webex or Google Meet - Voicegain Transcribe has a way to support you.
We now have some exciting news for those users that regularly host Zoom meetings. Voicegain Transcribe users who are on Windows now have a free, easy and convenient way to access all their meeting transcripts and notes from their Zoom meetings. Transcribe Users can now download a new client app that we have developed - Voicegain Zoom Meeting Assistant for Local Recordings - onto their device.
With this client app, any Local Recording of a Zoom meeting (explained below) will be automatically submitted to Voicegain Transcribe. Voicegain's highly accurate AI models subsequently process the recording to generate both the transcript (Speech-to-Text) but also the minutes of the meeting and the topics discussed (NLU).
As always, you get started with a free plan that does not expire. So you can get started today without having to setup your payment information.
Zoom provides two options to record meetings on its platform - 1) Local Recording and 2) Cloud Recording.
Zoom Local recording is a recording of the meeting that is saved on the hard disk of the user's device. There are two distinct benefits of using Zoom Local Recording
Zoom Cloud Recording is when the recording of the meeting is stored on your Zoom Cloud account on Zoom's servers. Currently Voicegain does not directly integrate with Zoom Cloud Recording (however it is on our roadmap). In the interim, a user may download the Cloud Recording and upload it to Voicegain Transcribe in order to transcribe and analyze recordings saved in the cloud.
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Zoom allows you to record individual speaker audio tracks separately as independent audio files. The screenshot above shows how to enable this feature on Zoom.
Voicegain Zoom Meeting Assistant for Local Recording supports uploading these independent audio files to Voicegain Transcribe so that you can get accurate speaker transcripts
The entire Voicegain platform including the Voicegain Transcribe App and the AI models can be deployed On-Premise (or in VPC) giving an enterprise a fully secure meeting transcription and analytics offering.
If you have any question, please sign up today, and contact our support team using the App.
Since June 2020, Voicegain has published benchmarks on the accuracy of its Speech-to-Text relative to big tech ASRs/Speech-to-Text engines like Amazon, Google, IBM and Microsoft.
The benchmark dataset for this comparison has been a 3rd Party dataset published by an independent party and it includes a wide variety of audio data – audiobooks, youtube videos, podcasts, phone conversations, zoom meetings and more.
Here is a link to some of the benchmarks that we have published.
1. Link to June 2020 Accuracy Benchmark
2. Link to Sep 2020 Accuracy Benchmark
3. Link to June 2021 Accuracy Benchmark
4. Link to Oct 2021 Accuracy Benchmark
5. Link to June 2022 Accuracy Benchmark
Through this process, we have gained insights into what it takes to deliver high accuracy for a specific use case.
We are now introducing an industry-first relative Speech-to-Text accuracy benchmark to our clients. By "relative", Voicegain’s accuracy (measured by Word Error Rate) shall be compared with a big tech player that the client is comparing us to. Voicegain will provide an SLA that its accuracy vis-à-vis this big tech player will be practically on-par.
We follow the following 4 step process to calculate relative accuracy SLA
In partnership with the client, Voicegain selects benchmark audio dataset that is representative of the actual data that the client shall process. Usually this is a randomized selection of client audio. We also recommend that clients retain their own independent benchmark dataset which is not shared with Voicegain to validate our results.
Voicegain partners with industry leading manual AI labeling companies to generate a 99% human generated accurate transcript of this benchmark dataset. We refer to this as the golden reference.
On this benchmark dataset, Voicegain shall provide scripts that enable clients to run a Word Error Rate (WER) comparison between the Voicegain platform and any one of the industry leading ASR providers that the client is comparing us to.
Currently Voicegain calculate the following two(2) KPIs
a. Median Word Error Rate: This is the median WER across all the audio files in the benchmark dataset for both the ASRs
b. Fourth Quartile Word Error Rate: After you organize the audio files in the benchmark dataset in increasing order of WER with the Big Tech ASR, we compute and compare the average WER of the fourth quartile for both Voicegain and the Big Tech ASR
So we contractually guarantee that Voicegain’s accuracy for the above 2 KPIs relative to the other ASR shall be within a threshold that is acceptable to the client.
Voicegain measures this accuracy SLA twice in the first year of the contract and annually once from the second year onwards.
If Voicegain does not meet the terms of the relative accuracy SLA, then we will train the underlying acoustic model to meet the accuracy SLA. We will take on the expenses associated with labeling and training . Voicegain shall guarantee that it shall meet the accuracy SLA within 90 days of the date of measurement.
1. Click here for instructions to access our live demo site.
2. If you are building a cool voice app and you are looking to test our APIs, click here to sign up for a developer account and receive $50 in free credits
3. If you want to take Voicegain as your own AI Transcription Assistant to meetings, click here.
Twilio platform supports encrypted call recordings. Here is Twillo documentation regarding how to setup encryption for the recordings on their platform.
Voicegain platform supports direct intake of encrypted recordings from the Twilio platform.
The overall diagram of how all of the components work together is as follows:
Bellow we describe how to configure a setup that will automatically submit encrypted recordings from Twilio to Voicegain transcription as soon as those recordings are completed.
Voicegain will require a Private Key in a PKCS#8 format to decrypt Twilio recordings. Twilio documentation describes how to generate a Private Key in that format.
Once you have the key, you need to upload it via Voicegain Web Console to the Context that you will be using for transcription. This can be done via Settings -> API Security -> Auth Configuration. You need to choose Type: Twilio Encrypted Recording.
We will be handling Twilio recording callbacks using an AWS Lambda function, but you can use an equivalent from a different Cloud platform or you can have your own service that handles https callbacks.
A sample AWS Lambda function in Python is available on Voicegain Github: platform/AWS-lambda-for-encrypted-recordings.py at master · voicegain/platform (github.com)
You will need to modify that function before it can be used.
First you need to enter the following parameters:
The Lambda function receives the callback from Twilio, parses the relevant info from it, and then submits a request to Voicegain STT API for OFFLINE transcription. If you want, you can modify, in the Lambda function code, the body of the request that will be submitted to Voicegain. For example, the github sample submits the results of transcription to be viewable in the Web Console (Portal), but you will likely want to change that, so that the results are submitted via a Callback to your HTTPS endpoint (there is a comment indicating where the change would need to be made).
You can also make other changes to the body of the request as needed. For the complete spec of the Voicegain Transcribe API see here.
Here is a simple python code that can be used to make an outbound Twilio call which will be recorded and then submitted for transcription.
Notice that:
It has been over 7 months since we published our last speech recognition accuracy benchmark. Back then the results were as follows (from most accurate to least): Microsoft and Amazon (close 2nd), then Voicegain and Google Enhanced, and then, far behind, IBM Watson and Google Standard.
Since then we have obtained more training data and added additional features to our training process. This resulted in a further increase in the accuracy of our model.
As far as the other recognizers are concerned:
We have decided to no longer report on Google Standard and IBM Watson accuracy, which were always far behind in accuracy.
We have repeated the test using similar methodology as before: used 44 files from the Jason Kincaid data set and 20 files published by rev.ai and removed all files where none of the recognizers could achieve a Word Error Rate (WER) lower than 25%.
This time only one file was that difficult. It was a bad quality phone interview (Byron Smith Interview 111416 - YouTube).
You can see boxplots with the results above. The chart also reports the average and median Word Error Rate (WER)
All of the recognizers have improved (Google Video Enhanced model stayed much the same but Google now has a new recognizer that is better).
Google latest-long, Voicegain, and Amazon are now very close together, while Microsoft is better by about 1 %.
Let's look at the number of files on which each recognizer was the best one.
Note, the numbers do not add to 63 because there were a few files where two recognizers had identical results (to 2 digits behind comma).
We now have done the same benchmark 4 times so we can draw charts showing how each of the recognizers has improved over the last 1 year and 9 months. (Note for Google the latest result is from latest-long model, other Google results are from video enhanced.)
You can clearly see that Voicegain and Amazon started quite bit behind Google and Microsoft but have since caught up.
Google seems to have the longest development cycles with very little improvement since Sept. 2021 till very recently. Microsoft, on the other hand, releases an improved recognizer every 6 months. Our improved releases are even more frequent than that.
As you can see the field is very close and you get different results on different files (the average and median do not paint the whole picture). As always, we invite you to review our apps, sign-up and test our accuracy with your data.
When you have to select speech recognition/ASR software, there are other factors beyond out-of-the-box recognition accuracy. These factors are, for example:
1. Click here for instructions to access our live demo site.
2. If you are building a cool voice app and you are looking to test our APIs, click here to sign up for a developer account and receive $50 in free credits
3. If you want to take Voicegain as your own AI Transcription Assistant to meetings, click here.
Today, we are really excited to announce the launch of Voicegain Transcribe, an AI based transcription assistant for both in-person and web meetings. With Transcribe, users can focus on their meetings and leave the note taking to us.
Transcribe can also be used to convert streaming and recorded audio from video events, webinars, podcasts and lectures into text.
Voicegain Transcribe is an app accessible from Chrome or Edge Browser and is powered by Voicegain's highly accurate speech recognition platform. Our out-of-the-box accuracy of 89% is on par with the very best.
Currently there are 3 main ways you can use Voicegain Transcribe:
If you join meetings directly from your Chrome or Edge browser (without any downloads or plug-ins), then you can use this feature to send audio to Voicegain. Examples of meeting platforms include Google Meet, BlueJeans, Webex and Zoom.
On a Windows device, browser sharing also works with a client desktop app like Zoom and Microsoft Teams. On a Mac/Apple device, browser sharing support desktop apps.
Voicegain offers a downloadable Windows client app that is installed on the user's computer. This app accesses Zoom Local Recordings and automatically uploads them for transcription to Voicegain Transcribe.
Zoom has two types of recordings - Local Recordings and Cloud Recordings. This app is for Local Recordings - where the recording is stored on the hard disk of the user's computer. To learn more about Zoom local recording click here.
Zoom also allows a separate audio file for each participant's recording. Voicegain App supports upload of these individual participant's audio file so that the speaker labels are accurately assigned to the transcript.
Users may also upload pre-recorded audio files of their meetings, podcasts, calls and generate the transcript. We support over 40 different formats including mp3, mp4, wav, aac and ogg). Voicegain supports speaker diarization - so we can separate speakers even on a single channel audio recording.
Currently we support English and Spanish. More languages are in our roadmap - German, Portuguese, Hindi.
Users can organize their meeting recordings and audio files into different projects. A project is like a workspace or a folder.
Users can save the voice signatures of meeting participants and users so that you can accurately assign speaker labels.
Voicegain can also extract meeting action items, positive and negative sentiment.
Users can also mask - in both text and audio - any personally identifiable information.
We are adding a feature where Voicegain Transcribe can join any meeting by having the user just enter the meeting url and inviting Voicegain Transcribe.
We are also adding a Chrome extension that will make it much easier to record and transcribe web meetings.
By signing up today, you will be signed up on our forever Free Plan - which makes you eligible for 120 mins of Meeting Transcription free every month . Once you are satisfied with our accuracy and our user experience, you can easily upgrade to Paid Plans.
If you have any questions, please email us at support@voicegain.ai
[Updated: 5/27/2022]
In addition to the current support for English, Spanish, Hindi, and German languages in its Speech-to-Text platform, Voicegain is releasing support for many new languages over the next couple of months.
You can access these languages right now from the Web Console or via our Transcribe App or via the API
Upon request we will make these languages available for your testing. Generally, they can be available within hours from receiving a request. Please contact us at support@voicegain.ai
The Alpha early access models differ from full-featured production models in the following ways:
As alpha models are being trained on additional data, their accuracy will improve. We are also working on punctuation, capitalization, and formatting of each of those models.
We will update this post as soon as these languages are available in the Alpha early access program.
Since our language models are created exclusively with End-to-End Deep Learning, we can perform transfer learning from one language to another, and quickly support new languages and dialects to better meet your use case. Don’t see your language listed below? Contact us at support@voicegain.ai, as new languages and dialects are released frequently.
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