FAQ
What is neuro-symbolic reasoning?
A hybrid of neural pattern recognition and symbolic logic/rules, enabling agents to decompose questions into verifiable logical steps—far beyond LLM next-token prediction or standard CoT—for transparent, reliable outputs.
How does infinite memory function?
Context is stored externally and retrieved dynamically, removing LLM window constraints and allowing agents to maintain complete histories indefinitely.
How does it differ from standard RAG or CoT?
We enhance RAG frameworks (LangChain/LangGraph/LlamaIndex) and CoT with symbolic decomposition: building explicit logical connections between sub-questions for deeper, more trustworthy reasoning.
What are the 15 emotions?
Empathy, happiness, sadness, excitement, curiosity, confidence, calm, enthusiasm, surprise, hesitation, gratitude, determination, frustration, boredom, anger—crafted for natural Digital Human and agent interactions.
Is it suited for production AI agents?
Yes: 30%+ hallucination reduction, explainable outputs for high-stakes use, scalable via GPUs, and proven in medical diagnostics, legal automation, and customer service agents.
How to integrate?
API-ready atop existing RAG stacks; contact us for agent/Digital Human demos in your domain.
Is it ChatGPT?
No. Even though we use an LLM as part of the app, Analog AI is much more. It consists of more than 400 specialized modules responsible for long-term memory, advanced reasoning, and emotional intelligence.
Unlike traditional LLMs, it can remember information without the need for expensive retraining, even learning directly from your users during interactions.
Why do I need a digital human and not just a chatbot?
We focus on industries where graphics and visual presentation play a critical role, such as fashion, real estate, automotive, and news media.
Analog AI digital humans are designed to engage users in a much more natural and emotional way.
However, we also offer a dedicated chatbot version, which is one of the most advanced standalone customer service chatbots available.
How can I train it?
There are two ways to train your agent: file upload and interactive training.
Initially, you can upload any documents you want the agent to learn from, including Word documents, PowerPoint files, PDFs, and more.
After uploading, you can start asking questions to test the agent’s understanding. Some information might not be covered in your documents, and although rare, the agent might sometimes hallucinate answers.
In such cases, you can use interactive training to correct mistakes immediately by chatting with the agent directly.
4. Is it a personal assistant?
Yes, you can also use Analog AI as an assistant.
You can ask it to deliver news tailored to your areas of interest, perform searches on different websites, or remember specific information for you.
Please note that these assistant features are currently in their early stages and will continue to evolve and improve over time.
What is neuro-symbolic reasoning?
A hybrid of neural pattern recognition and symbolic logic/rules, enabling agents to decompose questions into verifiable logical steps—far beyond LLM next-token prediction or standard CoT—for transparent, reliable outputs.
How does infinite memory function?
Context is stored externally and retrieved dynamically, removing LLM window constraints and allowing agents to maintain complete histories indefinitely.
How does it differ from standard RAG or CoT?
We enhance RAG frameworks (LangChain/LangGraph/LlamaIndex) and CoT with symbolic decomposition: building explicit logical connections between sub-questions for deeper, more trustworthy reasoning.
What are the 15 emotions?
Empathy, happiness, sadness, excitement, curiosity, confidence, calm, enthusiasm, surprise, hesitation, gratitude, determination, frustration, boredom, anger—crafted for natural Digital Human and agent interactions.
Is it suited for production AI agents?
Yes: 30%+ hallucination reduction, explainable outputs for high-stakes use, scalable via GPUs, and proven in medical diagnostics, legal automation, and customer service agents.
How to integrate?
API-ready atop existing RAG stacks; contact us for agent/Digital Human demos in your domain.
Is it ChatGPT?
No. Even though we use an LLM as part of the app, Analog AI is much more. It consists of more than 400 specialized modules responsible for long-term memory, advanced reasoning, and emotional intelligence.
Unlike traditional LLMs, it can remember information without the need for expensive retraining, even learning directly from your users during interactions.
Why do I need a digital human and not just a chatbot?
We focus on industries where graphics and visual presentation play a critical role, such as fashion, real estate, automotive, and news media.
Analog AI digital humans are designed to engage users in a much more natural and emotional way.
However, we also offer a dedicated chatbot version, which is one of the most advanced standalone customer service chatbots available.
How can I train it?
There are two ways to train your agent: file upload and interactive training.
Initially, you can upload any documents you want the agent to learn from, including Word documents, PowerPoint files, PDFs, and more.
After uploading, you can start asking questions to test the agent’s understanding. Some information might not be covered in your documents, and although rare, the agent might sometimes hallucinate answers.
In such cases, you can use interactive training to correct mistakes immediately by chatting with the agent directly.
4. Is it a personal assistant?
Yes, you can also use Analog AI as an assistant.
You can ask it to deliver news tailored to your areas of interest, perform searches on different websites, or remember specific information for you.
Please note that these assistant features are currently in their early stages and will continue to evolve and improve over time.
