GAUSS2Discuss a pilot Real-world conversation data for voice AI
Gauss² transforms approved operational audio into rights-scoped, privacy-treated, evidence-linked datasets for training and evaluating voice agents, speech systems, and conversation intelligence.
01 Why real conversations
Production conversations include interruptions, poor connections, accents, hesitation, corrections, transfers, and unexpected questions. Those moments are often where voice systems break—and where generic, scripted datasets have the least to teach them.
We build private datasets from the conversations that matter to your product, your users, and your market.
Natural conversations, not generic public corpora.
Data selected or sourced for a defined model need.
Approved sources, clear use terms, and careful handling.
02 What we do
Two paths to a dataset made for your voice product.
Use audio you already have
We identify the conversations that matter, remove sensitive details, create accurate transcripts and labels, and package the result for training or evaluation.
Source data you do not have
When the right conversations do not exist in-house, we source or collect new real-world audio around the language, channel, customer journey, and edge cases your system needs to handle.
03 Use cases
Training data and test sets shaped around real product behavior.
Teach agents to handle interruptions, objections, transfers, escalation, and task completion in natural conversation.
↗Improve transcription and speaker detection across phone audio, accents, background noise, overlap, and difficult recordings.
↗Train systems to identify intent, questions, objections, commitments, next steps, and outcomes from real calls.
↗Test performance on representative conversations, including the failure cases that clean benchmarks tend to miss.
↗04 Sample package
A Gauss² delivery is more than a folder of audio. Each conversation arrives with the transcripts, labels, permissions, and quality notes your team needs to understand and use it.
Request the full sampleaudio/Privacy-treated conversation clips✓transcripts/Speaker turns with precise timestamps✓labels/Intents, events, and outcomes✓dataset-card.pdfSource, permitted use, and limitations✓quality-report.pdfCoverage, checks, and known edge cases✓Customer “The last invoice is higher than I expected.”
Agent “I can walk through the difference with you.”
Illustrative structure only. No private source audio is shown.
05 Data you can stand behind
We confirm where the audio came from and what it may be used for before work begins.
Sensitive details are removed or replaced in the transcript and audio as the use case requires.
Every package states the permitted use, handling requirements, limits, and source history in plain language.
06 How a pilot works
We start with a focused pilot built around one model need. Your team reviews the actual output before either side commits to a larger program.
Tell us the behavior, market, channel, or failure case your model needs to learn.
We determine whether to use approved audio you have or source new conversations.
We prepare a small, representative package with the agreed privacy treatment and labels.
Your team reviews the sample against its model and acceptance criteria.
Once the pilot proves useful, we expand the dataset and deliver it in your preferred format.
GAUSS207 About Gauss²
Casey Gauss founded Viral Launch, an analytics software company for ecommerce brands, and built its data science team. That experience made one lesson clear: models and analytics are only as useful as the data underneath them.
Co-founder Corey Gauss helped lead operations at Viral Launch and has spent years working with healthcare call centers, where sensitive voice data, quality control, and day-to-day operational reality meet.
Gauss² brings that data, operations, and call-center experience together to build private conversation datasets that solve real product problems.
Casey Gauss on LinkedIn08 Start with a pilot
Tell us what your voice system needs to understand. We will help determine whether the right first step is a pilot using existing audio or a custom data collection.