# Introduction

OriginTrail is an ecosystem building **collective, trusted memory** for AI. The core ecosystem technology is the **Decentralized Knowledge Graph (DKG)**, a decentralized, permissionless network of nodes, through which both humans and machines can share knowledge, reason together, and preserve context across time.

Modern AI is powerful but ungrounded. It predicts without knowing, hallucinates, forgets what it said, and relies on data controlled by a few centralized platforms. LLMs in particular have an "explainability" problem - why did an LLM respond a certain way, based on what knowledge, coming from which source?

The **Decentralized Knowledge Graph (DKG)** hosts **Knowledge Assets** that encode facts, data provenance, and meaning in a tamper-proof way. The network is hosted by a set of independent **DKG Nodes**. Anyone can run a **DKG network Node** - organizations and individuals - contributing to the DKG and at the same time building upon their knowledge in a **privacy-preserving** way. Thus the DKG ensures that no single entity can rewrite, censor, or monopolize the collective memory. Decentralization keeps AI accountable, bias-resistant, and aligned with human diversity.

OriginTrail’s **neuro-symbolic approach** combines the structure and reasoning of **symbolic AI** with the creativity and pattern recognition of **neural AI**. This enables AI systems to think with context, grounding their outputs in verifiable knowledge rather than probabilistic guesses.

The DKG grows through human participation. Researchers, developers, and citizens can all publish, link, and improve knowledge — ensuring that the world’s intelligence is shaped by the many, not the few.

**Core operations**

* **Publishing knowledge:** Turning data into structured, verifiable Knowledge Assets
* **Knowledge discovery:** Querying, traversing, and monetizing knowledge in the decentralized graph and its *paranets*
* **Trusted sharing:** Cryptographically verify authenticity and provenance of knowledge
* **Neuro-symbolic reasoning**: Infer new facts based on rules, leveraging graph-based reasoning in combination with LLMs and GenAI models

We encourage developers to [try out the DKG Node](/getting-started/decentralized-knowledge-graph-dkg.md) and build their first DKG based agent with it, to get a feel of what the technology can do.

### Three ways to get started

<table data-view="cards"><thead><tr><th></th><th></th><th data-hidden data-card-cover data-type="image">Cover image</th><th data-hidden data-card-target data-type="content-ref"></th></tr></thead><tbody><tr><td><a href="/pages/k35Bb4xuuyzuDsBFw36I">Build your DKG Agent</a></td><td>Begin your journey on the Decentralized Knowledge Graph by setting up your first DKG Node and Agent. This is your entry point into the verifiable knowledge economy.</td><td><a href="/files/YOOMUwtHKn5m4B1rCaKQ">/files/YOOMUwtHKn5m4B1rCaKQ</a></td><td></td></tr><tr><td><a href="/pages/Vu9W50PFZojeXfMmum7e">Contribute to the DKG</a></td><td>Activate your DKG Node and join the decentralized knowledge economy by staking TRAC.</td><td><a href="/files/8A0Hm7mXdGiS2LWXTtBv">/files/8A0Hm7mXdGiS2LWXTtBv</a></td><td><a href="/pages/dtuirMm1gzZC1yMaxF4y">/pages/dtuirMm1gzZC1yMaxF4y</a></td></tr><tr><td><a href="/pages/j5AmBVHqZYv76tJop4js">Learn more about the DKG</a></td><td>Explore the core concepts behind the DKG and how it powers verifiable, intelligent AI.</td><td><a href="/files/mQZ3VQwOwzTtZtow9DoQ">/files/mQZ3VQwOwzTtZtow9DoQ</a></td><td></td></tr></tbody></table>

{% hint style="success" %}
This site is a constantly updated, work-in-progress official OriginTrail documentation built by the OriginTrail community and core developers.

Find the "Edit on GitHub" button in the upper-right corner and submit your updates as pull requests (or do it directly in the [docs GitHub repo).](https://github.com/OriginTrail/dkg-docs)

We appreciate any feedback, improvement ideas, and comments.
{% endhint %}


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# Agent Instructions: 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://docs.origintrail.io/readme.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.