Crypto startup Axal automates trading with AI agents

The tool is ideal for non-technical crypto fans who are interested in the space but aren’t day traders or DeFi experts

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US-based startup Axal is combining crypto trading with AI agents. They’re starting with automated trades through their Autopilot tool, which lets users set a risk tolerance level and other restrictions to automate trading with crypto and stablecoins.

The team told me in an interview that the tool currently uses Ethereum L2 chains Base, Optimism and Arbitrum on the backend, with plans to add Solana in the coming weeks. 

Autopilot users can fund their accounts via crypto wallets, or by using an email and funding with Venmo. Once personal trading preferences and settings are set up, Autopilot’s AI agents can get to work.

There’s a wide range of functionality with Autopilot, but it’s more newbie-friendly and ideal for non-technical crypto fans who like crypto but aren’t day-traders or DeFi experts. Autopilot can collect stablecoin yields, engage with DeFi tools, and trade BTC, ETH, memecoins and other tokens. Users can also make a custom index of specific tokens for the AI agents to trade. 

It’s not an intimidating tool, and it seems like there are enough parameters that can be set to ensure there will be no major surprises. But like with any AI tool, hallucinations are still possible.

Axal’s team is aware of this flaw, but they see the blockchain as one way to verify that requested tasks are actually completed per instructions. 

“You can literally look onchain that this thing that you wanted this agent to do, it actually did,” Axal Head of Strategy and Operations Ari Santos said.

Under the hood, Axal’s also using zero-knowledge co-processors and Optimistic oracles to verify information.

“If a model hallucinates, it still has collateral at stake and it gets slashed. Whoever’s running the model, or the model itself, if it has very low accuracy, it’s just taking that risk,” Axal founder Ashlan Ahmed told Blockworks, explaining that hallucinating models are essentially punished for mistakes.

The team has plans for future AI tools, including one that can automate more daily tasks such as ordering food for delivery based on a general request or booking travel when given travel dates and preferences.

“There’s a lot of different people in the agentic space,” Axal Head of Growth Jacob Kozhipatt acknowledged. “What we believe is that in order for the agentic feature to happen, people need some form of guarantee that it’ll actually be done the way that you asked to be done.”

This interview has been edited and condensed for clarity.


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