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An agentic Core Orchestrator continuously scores, allocates, and risk-controls a live, rules-based index delivering ETF-style clarity with AI-driven adaptability.
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SAN FRANCISCO, Nov. 12, 2025 (GLOBE NEWSWIRE) — Months after launching its ETF-style Index powered by an Autonomous Portfolio Orchestrator, Sagehood.ai is detailing how the system selects, weights, and rebalances U.S. equities in real time using a coordinated network of specialized AI agents. The Index is engineered to deliver the operational simplicity investors expect from an ETF framework (transparent rules, scheduled rebalancing, auditable data), while the Orchestrator provides adaptive, explainable decision-making under changing market regimes. In addition, Sagehood.ai provides free access to deep, fresh analysis across more than 5,000 U.S. tickers, a scope that would normally require a team of hundreds of experts, now instantly accessible at no cost.
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Unlike traditional quant models or passive products that crowd into the same large-cap names, Sagehood.ai’s architecture runs a live Army of Agents: dedicated models for financial, news and filings NLP, social sentiment, macro regime mapping, technical structure, valuation, and portfolio risk. These agents feed a Core Orchestrator that decides which names enter or exit the Index and when to rebalance, backed by kill-switches, drift monitors, and consensus thresholds.
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What “ETF-Style Index” Means at Sagehood.ai
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Index, not a dashboard: Constructed and maintained via rules, published holdings, and a set rebalance schedule, just like an ETF index methodology.
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Autonomous Portfolio Orchestrator under the hood: Specialist agents produce signals; the Core Orchestrator approves changes and enforces risk controls.
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Operational clarity, adaptive intelligence: Investors get ETF-style transparency with AI that can respond to regime shifts.
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Core Capabilities
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Live Multi-Signal Equity Selection
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The Orchestrator continuously ranks U.S. large-cap names via ensemble scoring across fundamental disclosures, macro sensitivity, capital flows, technicals, and sentiment. Each security is scored independently by specialist agents, then approved or rejected by the Core Orchestrator.
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Programmatic Portfolio Construction
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Approved names are slotted into a 30-name, equally weighted Index (~3.33% per name) drawn from the S&P 500 universe. Signals update weekly; the live Index is rebalanced monthly. The approach targets adaptability without uncontrolled turnover or style-drift.
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Dynamic Risk Modulation
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Before any rebalance goes live, the Orchestrator checks concentration, sector exposure, and volatility stress. Sector weight caps and drift alarms prevent any single narrative or theme from silently dominating the portfolio.
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Continuous Feedback Loop
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Signals can be down-weighted or killed if the agents detect structural breaks—for example, when liquidity, sentiment, or macro tone abruptly flips. The goal is a self-correcting Index process that adapts without abandoning rules.
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Human-Grade Explainability, Machine-Grade Speed
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Every Index change comes with an audit trail: which agents pushed for or against a name, what risk flags appeared, and what final override logic the Orchestrator applied.
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Free Research Access
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Sagehood.ai’s research layer delivers comprehensive, continuously refreshed analysis on 5,000+ U.S. tickers coverage breadth that typically demands hundreds of human analysts and makes it available free to users. This includes multi-source signal context, recent catalysts, and structured summaries aligned to the same agentic framework that powers the Index.
English (US)