
TUNiB
Conversational A.I. That People Emotionally Engage With

Description
TUNiB is an AI company focused on developing conversational AI solutions designed for deep user engagement. They provide services centered around Small Large Language Models (sLLMs), including 'Polyglot', the first fully open-source Korean sLLM for commercial use, and the development of custom, in-house sLLMs tailored to specific domains.
In addition to sLLM development, TUNiB offers Multi-Persona Chatbots, providing access to millions of pre-built personas or swiftly delivering tailored chatbot solutions via API integration to enhance user interaction. Their suite of NLP APIs aims to protect online platforms by detecting hate speech ('Safety Check') and masking private information ('De-identification'), alongside capabilities for text, image, news, and video analytics, emotion prediction, text-to-speech, and more. TUNiB emphasizes building technology rooted in humanity and high ethical standards.
Key Features
- Polyglot Foundation sLLM: First fully open-source Korean sLLM for commercial use.
- In-house sLLM Development: Creation of custom, domain-specific small language models.
- Multi-Persona Chatbots: Access to millions of pre-built persona chatbots and tailored chatbot API integration.
- Safety Check API: Detects 12 categories of toxicity across 4 severity levels.
- De-identification API: Detects and masks 14 types of personal information.
- NLP Analytics APIs: Offers APIs for Text, Image, News, and Video Analytics.
- Emotion Prediction API: Analyzes text to predict underlying emotions.
- Text-to-Speech API: Converts text input into synthesized speech.
Use Cases
- Developing emotionally engaging conversational AI applications.
- Building custom chatbots for specific industries or tasks.
- Integrating chatbots into platforms to enhance user engagement.
- Moderating online content for toxicity and hate speech.
- Protecting user privacy by masking personal information.
- Analyzing text, image, news, and video data for insights.
- Understanding user sentiment through emotion prediction.
- Creating voice applications with text-to-speech.
- Utilizing an open-source Korean language model for commercial projects.
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