# Team

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Agent Arc is built by a multidisciplinary team with experience spanning institutional finance, large-scale trading infrastructure, applied AI research, and decentralized systems engineering.

Core contributors include engineers and researchers with prior experience at organizations such as **JP Morgan**, **TikTok**, **Crypto.com**, **Cake DeFi**, **DBS Bank**, **EY**, **KPMG**, **Nomura Asset Management**, **UBS**, and **Lloyds**, alongside founders and operators who have built and scaled products across Web3, AI, and financial systems.

The team combines backgrounds in:

* **Institutional trading systems and market infrastructure**
* **Machine learning and applied AI (NLP, deep learning, robotics)**
* **Blockchain protocol engineering and exchange integration**
* **Risk management, compliance, and financial operations**

Agent Arc’s research efforts are supported by external AI researchers with academic and applied backgrounds in robotics, adversarial learning, and autonomous systems.

**AI Research Partners:**

* **Peter Lorenz** : A Ph.D. trained ML researcher with a background in robotics, autonomous driving, and adversarial AI. He has worked on real-world autonomous systems from drones and simulators to robust perception and model security, across NTU,  MIT-IBM, and defense R\&D. \
  \
  Research: <https://scholar.google.com/citations?user=sb4hPQMAAAAJ&hl=en>


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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://agent-arc.gitbook.io/agent-arc-docs/overview/litepaper/team.md?ask=<question>
```

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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.
