Portfolio

comevis
Thinking
Wir hören in Ihre Marke rein: Von der Exploration bis zum Tracking.
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Methodik: comevis Sonic Profiling

comevis
Design
Wir gestalten Ihren Klang:
Vom Audio Branding über die Klangarchitektur bis zur Corporate Voice.
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Methodik: comevis Sonic Coding

comevis
Make it Real
Wir gehen weiter:
In unseren Science Labs und unseren Studios.
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Methodik: comevis Sonic Producing

comevis Care
Performance Corporate Voice & Soundservices
Licensing (GEMA-frei), Services, Produktionsmanagement, QS, Joure Fix, Check, Report









Challenges of AI Voice Agents
Many voicebots work technically, but do not deliver the desired experience:
Low User Acceptance:
Customers bypass the voice agent or cancel.
Unclear Dialogues:
Conversations become confusing or end in dead ends.
Inaccurate Speech Recognition (STT):
Dialects, technical terms, or ambient noise are not recognized accurately.
Low-Quality Voices (TTS):
Voices sound artificial, monotonous, or not in line with the brand.
Pronunciation Problems:
Names, products, or technical terms are pronounced incorrectly or inconsistently.
AI Hallucinations:
Models provide incorrect or fictitious answers, e.g., due to unsuitable training data.
Why Traditional Approaches Fail
Many companies have implemented AI voice solutions in recent years. Some work well, but many only work partially or not at all.
What started as an innovation project quickly becomes an operational risk.

Targeted Measures for Stability, Quality, and Acceptance
AI Voice Agent Emergency Assistance is not a restart, but rather a targeted intervention where the real problems lie – technically, conceptually, and qualitatively.
We have been working on automation solutions and the productive use of AI for over 12 years. Many providers lack this experience and treat AI voice agents primarily as a topic for innovation or demonstration.
Our Instant Support in Detail
Increase User Acceptance
Optimization of dialogue and language through consistent conversational design.
Resolve Vague Dialogues
Redesign of conversation logic, intents, and handovers without dead ends.
Improve Speech-to-Text (STT)
Model selection, fine-tuning, and configuration for reliable detection in real-world operation.
Optimize Text-to-Speech (TTS)
Selection and optimization of natural voices that are consistent with the brand.
Fix Pronunciation Problems
Fine-tuning of emphasis, names, and technical terms for consistent output.
Avoiding AI Hallucinations
Introduction of anti-hallucination mechanisms for reliable AI responses.
From a Problem Case to a Stable AI Voice Agent
Stable operation instead of unpredictable expenses
Better comprehensibility instead of frustrating dialogues
Increased acceptance instead of circumvention by users
Reliable answers instead of hallucinations




















