Consensus Capital
Autonomous capital allocation powered by a multi-agent AI investment committee. Propose, debate, vote, execute.
Abstract
Consensus Capital is an AI-powered investment system in which autonomous agents act as an investment committee. Each agent proposes trades with confidence scores and rationale; the committee debates, votes, and reaches consensus before execution. Capital allocation shifts are tracked in real time, producing a transparent audit trail of how and why capital moves. This whitepaper describes the architecture, agent roles, consensus mechanism, and risk framework.
Problem Statement
Traditional quant and discretionary strategies rely on a single model or a small team. Biases, blind spots, and execution lag limit performance. Meanwhile, multi-signal, multi-timeframe decisions are hard to scale and to explain. Investors want systematic, auditable allocation that can adapt at speed without sacrificing transparency or governance.
- • Single-model systems lack diversity of view and debate
- • Human committees are slow and don't scale
- • Black-box execution makes attribution and audit difficult
- • No clear link between consensus, confidence, and capital shifts
The Consensus Capital Solution
Consensus Capital runs a multi-agent committee where specialized AI analysts (e.g. signal, risk, macro, momentum) propose trades. Proposals are debated and voted on; only approved ideas move capital. The system records every proposal, vote, and allocation change, so users see exactly how consensus was reached and how it drove the portfolio.
Committee Design
Agent Roles
Identifies entry and exit signals from market data, on-chain activity, and quantitative factors. Proposes trades with confidence scores.
Evaluates position sizing, drawdown, correlation, and tail risk. Can veto or downsize proposals that exceed risk tolerances.
Incorporates regime, liquidity, and cross-asset context. Adjusts proposal priors based on macro view.
Tracks trend strength and momentum regime. Proposes or opposes based on alignment with current momentum.
Consensus & Execution
Proposals require a defined voting threshold (e.g. majority or supermajority) to be executed. Each vote is recorded with agent ID and timestamp. Executed trades update the Capital Allocation Curve; tooltips and logs show which proposal drove each allocation change (e.g. "Trade Approved — +3.2% allocation to SOL").
Technology Architecture
Consensus Capital combines agent orchestration, real-time voting, and execution infrastructure to run the committee and record every decision.
Isolated execution for each agent with access to market data, risk limits, and proposal schema. Outputs structured proposals with confidence and rationale.
Collects votes, applies threshold rules, and produces approved trade list. Full audit trail of proposals and votes with timestamps.
Translates approved trades into orders and updates the Capital Allocation Curve. Tracks portfolio weights and attribution to each committee decision.
Roadmap
- • Four-agent committee (Signal, Risk, Macro, Momentum)
- • Committee Decision Timeline & Capital Allocation Curve
- • Paper trading and backtest mode
- • Live execution with configurable risk limits
- • API for proposal and vote streaming
- • Custom agent plugins and thresholds
- • Multiple committee instances and strategies
- • Governance over threshold and agent parameters
- • Institutional reporting and compliance hooks
- • Additional specialized agents (liquidity, sentiment, cross-asset)
- • Research layer for hypothesis testing and attribution
- • White-label and partner deployments
Risk Disclosure
Consensus Capital is an experimental AI investment system. This whitepaper does not constitute financial, legal, or investment advice. Use of the system may involve significant risk. Consider the following:
- • AI agents can make errors; past consensus or backtests do not guarantee future results
- • Execution, slippage, and market impact may differ from model outputs
- • Regulatory treatment of automated trading and AI is evolving
- • System dependency on infrastructure, data, and models creates operational and counterparty risk
- • Capital can be lost in full; only allocate what you can afford to lose
Always conduct your own research (DYOR) and seek independent advice where appropriate.
Consensus Capital
Autonomous capital allocation powered by AI consensus. Propose, debate, vote, execute.