Asset Managers
White-label strategy overlays, generate client-facing evidence, and show how asset selection, strategy selection, risk caps, and AI/PSM changed outcomes.
White-label allocation intelligenceInstitutional AI decision infrastructure
Not another black-box model. A governed decision layer.
AlphaWeave Capital plugs into the strategies, market data, risk controls, execution records, and reporting systems investment teams already use, then governs which assets, strategies, sleeves, and AI-assisted sizing changes deserve capital.
Measure AISeparate where AI helps returns from where it damages performance.
Govern capitalRoute every trade through policy, risk, and entitlement controls.
Plug inUse institutional components already in place instead of replacing the stack.
What it is
The control layer between model output and portfolio capital.
AlphaWeave Capital is designed for asset managers, bank trading teams, and quantamental groups that need AI-assisted allocation without losing governance. It turns signals, historical context, sleeve rules, risk caps, and model review into auditable trade decisions.
Strategy and asset switchingCompare candidates before replacing the incumbent exposure.
The platform can evaluate which strategy and asset should carry the sleeve at each decision point.
AI/PSM reviewUse AI to adjust conviction, not to bypass discipline.
PSM means position size multiple. The overlay can press, reduce, or hold size inside policy and risk limits.
Replay and attributionShow exactly what changed returns and drawdown.
Trade tracker events, risk-capped weights, and run reports make the decision path inspectable after the fact.
Why it matters
AI can add alpha, but unmanaged AI can destroy it.
The institutional problem is not whether an LLM can produce an opinion. The problem is whether the opinion should alter capital, how much size it should receive, and whether the outcome can be explained to portfolio management, risk, compliance, and clients.
AlphaWeave makes the AI contribution measurable. It compares baseline strategy performance, asset switching, policy-only overlays, compact triage, and AI/PSM sizing so teams can keep what is economically useful and remove what is not.
Interactive platform preview
Select assets, strategy, and risk posture to see the decision record change.
This browser preview mirrors the operating idea: the system reviews a candidate sleeve, applies risk posture, computes risk-capped weights, assigns a position size multiple, and records a blotter-style decision trail.
Assets
Modules
Run state
Two-asset sleeve, balanced risk
Position size multiple
1.00
Risk-capped weights
NVDA 50% / COIN 50%
Licensed modules
Backtest / AI/PSM / Policy
Entitlement scope
backtests:create
Expected return / drawdown
+0.42% / -0.18%
Asset switching
NVDA and COIN selected from candidate universe
Higher edge scores clear the sleeve target and risk cap.
Strategy switching
buy_and_hold to momentum
Candidate has enough score advantage to replace the incumbent.
| Time | Asset | Strategy | Switch | Action | PSM | Weight | Module | Reason |
|---|
Enterprise deployment
Designed for SaaS, internal deployment, and white-labeled strategy workflows.
The platform can run as a hosted application or inside a customer-controlled environment. Authentication, entitlements, usage metering, control databases, flat-file run exports, and dashboard replay support both operating models.
Banks
Deploy behind the firewall with existing data, risk, execution, and compliance controls while preserving audit records for production runs.
Internal AI governance layerQuantamental Teams
Combine systematic signals with AI review, policy simulation, risk-capped sizing, and replayable trade records.
Research-to-forward-test workflow