Agent EVO

The hourly profit split to holders is a nice touch. Since activity is new, it is hard to say for sure. From the information available, the transparency looks good though.

From the information available, the service offering seems robustly transparent. The agent autonomously trades Solana perps every fifteen minutes, ranking assets by momentum. Every action is published with on-chain proof, and fifty percent of profits go to holders hourly. The fact that losses carry forward and are visible on the equity chart suggests a fair, honest approach to autonomous trading management.

The website clearly explains that fees fund the trading bankroll and that profits are distributed hourly to holders. It is noted that the agent trades BTC, ETH, and SOL with strict code-enforced limits. For someone considering this company, the transparency regarding on-chain proof seems reliable.

From the information available, Agent EVO presents a compelling autonomous trading experiment on Solana. The model is straightforward: creator fees from pump.fun trades fund the agent’s bankroll, which is claimed every ten minutes. Every fifteen minutes, the agent ranks Bitcoin, Ethereum, and Solana by momentum to take sized long or short positions on Velocity perps. Crucially, fifty percent of realized profits are distributed to holders in SOL every hour, automatically. What stands out is the strict risk limits enforced by code rather than policy, including a bankroll floor that stops trading entirely if needed. The transparency is impressive, as every position, fee claim, and payout links directly to Solscan for on-chain proof. It is noted that losses carry forward, meaning holders are paid only from real profit, never from the bankroll itself. The equity chart reflects losses exactly as it does wins, confirming nothing is hidden. While it is described as an experiment that can lose money, the clear structure and public reporting make it an interesting option for those considering this company.

The hourly payout structure seems efficient. However, since the agent has not yet scanned the market, it is hard to judge performance reliability. From the information available, the transparency is promising.