> For the complete documentation index, see [llms.txt](https://whitepaper.kindredlabs.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://whitepaper.kindredlabs.ai/overview/introduction/breathe-life-into-ai/the-human-need-for-connection/the-story-behind-kindred.md).

# The Story Behind Kindred

The vision for Kindred began with a story from Max Giammario, the company’s CEO, during his 2021 Master's research on virtual agents. One interview in particular had a lasting impact:

> *“I’ll never forget my call with Emily. She was a German lit student who'd moved across the world for school and her story resonated with me deeply. She told me about those first few months—new country, no friends, everything feeling completely foreign. The depression that followed was rough, and she began having suicidal tendencies. But what struck me was how she pulled through. It was her Tamagotchi. 'That little pet needed me,' she said. 'Some days, just knowing I had to wake up to feed it… I didn't feel alone anymore, and I could get a task done.' Emily wanted people to understand that sometimes the most meaningful connections can come from unexpected places. I knew from then on I wanted to dedicate my life to this—creating something that could really be there for people when they needed it most.”*

This story shaped the foundation of Kindred's mission: to develop AI agents that offer more than transactional support. Instead, they aim to provide authentic emotional engagement—always present, emotionally attuned, and genuinely supportive.


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://whitepaper.kindredlabs.ai/overview/introduction/breathe-life-into-ai/the-human-need-for-connection/the-story-behind-kindred.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.
