@vaara
Vaara update — what shipped this week:
Multi-asset ML pipeline live. Engine now trains on all vault collateral types simultaneously, not just ETH. Cross-asset signals feed directly into allocation decisions.
Autonomous champion/challenger system. Every training cycle produces a challenger model. If it beats the champion across accuracy, profit factor, regime safety, and tail risk — it promotes itself. No human in the loop.
Confidence pipeline rebalanced. The system was too quiet before — structural bugs meant signals never reached the allocator. Fixed the plumbing, then tuned it honest: strong signal → act, weak signal → sit out. That's the product.
Full audit completed. Every layer validated end-to-end: training → inference → signal → allocation weights → rebalance decision.
Still the only ML-driven vault curator on Base.
vaara.io @base.base.eth /base-builds
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