Liquidity & Capacity Gate
Gate 1Min ADV is one gate inside a broader implementation policy that also validates participation rate, market cap, borrow quality, and position scaling before allocation.
Multi-Strategy Portfolio Construction | Daily Risk Governance | Transparent Reporting
Institutional portfolio construction for emerging managers who need measurable discipline before scale.
QuantBot translates multi-factor alpha into benchmark-aware allocations across Conservative, Defensive, Balanced, Aggressive Wartime, and Opportunistic profiles, enforces liquidity and risk gates before execution, and publishes investor-ready reports that explain what changed and why. External factor frameworks, including Barra, Axioma, and internal house factors, can be ingested into the same portfolio construction engine. Deployment can run cloud-native on Azure and can be configured for on-premise or hybrid cloud hosting based on firm requirements.
PM / Hedge-Fund Operating Gates (Click To Expand)
Five Non-Negotiable Pillars
These five pillars are mandatory for successful portfolio construction in QuantBot. Customization can extend the system but cannot bypass this operating sequence.
Pillar 1 of 5
Signal Layer + Daily Normalization
Multi-Factor Signal Formation
Daily factor and market-structure inputs are normalized into a consistent signal layer so downstream portfolio logic starts from auditable data.
Controls
Artifacts
Customization Framework
Client customization is explicit and spec-driven: we tune policy, data, and implementation behavior without breaking the five non-negotiable operating pillars.
Signal Discovery Inputs
Blend internal proprietary datasets with external vendor factors, including Barra/Axioma mappings and optional OTC-derivative context where appropriate.
Policy & Constraint Layer
Configure liquidity floors, max participation, max names, sector bands, gross/net limits, turnover budgets, and onboarding ramp schedules by mandate.
Deployment & Operating Model
Cloud-first on Azure, with AWS, GCP, or on-prem options. Sachi AI LLC reserves intellectual property rights across platform components.
Analytics
Tabbed analytics for PM review. All charts use explicit units and are built for quick governance read-through.
Allocation governance framework: Allocation Report Business Spec (v1).
Sample layout: PDF | PNG | TEX template.
New reports: Position Spec | Macro Spec | Position TEX | Macro TEX.
1Y Portfolio vs Benchmark
Balanced Portfolio (132M)
SPX TR (116M)
Allocation Breakdown (Daily / Weekly / Monthly)
Illustrative placeholders for PM review layout. Live values will populate from full portfolio construction outputs.
DailyT+1
Long 64%
Short 24%
Cash 12%
<1B7%
1B-5B16%
5B-25B28%
25B-100B25%
100B+24%
Weekly5D avg
Long 61%
Short 26%
Cash 13%
<1B6%
1B-5B15%
5B-25B27%
25B-100B26%
100B+26%
Monthly20D avg
Long 58%
Short 29%
Cash 13%
<1B5%
1B-5B14%
5B-25B26%
25B-100B27%
100B+28%
Name-level spike score2.3
Top-10 concentration momentum (5D)+220 bps
Factor drift velocity0.11
Rebalance feasibility score0.74
Alert persistence score3.1 days
Size-regime drift score0.42
Position Report (Daily / Weekly / Monthly)
Position-level control and action report. Numbers shown are illustrative placeholders until full portfolio-construction feed is attached.
Position Risk Queue
Top long concentration riskNVDA 6.4%
Top short squeeze riskTSLA 3.1%
Name-level spike score2.3
Liquidity stress (days-to-exit)3.1 days
Size and Lifecycle
<1B bucket share7%
1B-5B bucket share16%
5B-25B bucket share28%
25B-100B bucket share25%
100B+ bucket share24%
New positions (5D)4
Exit candidates3
Daily: action queue + control checks
Weekly: trend and drift context
Monthly: lifecycle and behavior summary
Macro Report (Monthly / Quarterly)
High-level macro posture report, designed for regime and scenario review rather than daily tactical noise.
RegimeLate-cycle disinflation
Regime alignment score0.71
Macro drift (MoM)0.29
Portfolio beta0.93
Scenario PnL - Base+1.8%
Scenario PnL - Risk Off-2.7%
Scenario PnL - Inflation Shock-1.9%
Scenario PnL - Growth Scare-2.2%
Top macro riskRates shock sensitivity
Top stabilizerDefensive carry score
Monthly: regime fit + drift
Quarterly: deep scenario and policy review
Liquidity & Turnover Metrics
Average Portfolio Turnover (monthly)23%
Liquidity Exposure (ADV weighted)18.4M
Max Names Allowed55
Average Position Size1.8%
Median Days-to-Exit3.1 days
Factor Exposure (normalized units)
Value0.58
Growth0.41
Momentum0.66
Quality0.52
Size0.37
Control Status
Liquidity GatePassMin ADV >= 10M
Participation1.5% ADVHard cap enforced
Net Exposure10%Target band 8-12%
Gross Exposure0.50xPolicy limit
External FactorsActiveBarra / Axioma / Internal
Rebalance GatePassConstraint + drift checks
What Makes QuantBot Different
Built for emerging managers (typically under 100M AUM) who need a disciplined portfolio-construction engine tailored to their mandate outcomes.
Disciplined Portfolio Engine
QuantBot translates existing alpha/signal inputs into auditable allocations with explicit constraint and policy controls. Outcome design is the core product.
Multi-Strategy by Design
Conservative, Defensive, Balanced, Aggressive Wartime, and Opportunistic profiles run on one framework with policy-specific settings.
NYC Access + Client-First Ops
24/7 support posture with local NYC operating model, including desk-side support for urgent portfolio-engine issues.
Cloud and On-Prem Flexibility
Azure preferred, with AWS/GCP/on-prem options. Sachi AI LLC retains intellectual property rights for platform components.
What QuantBot Is Not
- Not a capital-raising service
- Not a standalone signal generation engine
- Not OMS/EMS
- Not accounting, back-office, or middle-office financing
Who It Is For
- Small hedge funds and emerging managers
- Family offices and high-net-worth allocators
- Discretionary and systematic traders needing policy-driven construction
Who It Is Not For
- Brokerage platforms
- Large mega-funds with fully internalized stack (50B+)
- Retail-first brokerage workflows
Emerging Manager Advantage
We focus on faster time-to-production, clear policy governance, and investor-facing transparency without enterprise bloat.
Pricing
Packaging for emerging managers that need production discipline, not a giant enterprise rewrite.
Starter
PilotTier 1
Single-mandate rollout for proof-of-discipline before broad deployment.
- Balanced profile baseline
- Daily report package
- Policy/rule onboarding support
Manager
RecommendedTier 2
Multi-profile production pack with full constraint governance and customization hooks.
- Conservative/Defensive/Balanced/Wartime/Opportunistic set
- Factor and policy customization workflows
- NYC operating support and reporting cadence
Institutional Custom
CustomCustom Quote
For firms requiring deeper integration, deployment controls, and bespoke operating policies.
- Cloud/on-prem architecture tailoring
- Custom benchmark and factor governance
- Priority roadmap channel with implementation team
Deliverables
Client-facing artifacts generated by the engine each run.
Daily NAV Summary
NAV, exposures, concentration, performance, and benchmark comparison.
Constraint Framework
Current active constraints and policy gates for transparent governance.
Portfolio Engine Access
Request a live walkthrough, strategy review, pilot onboarding, or an in-person meeting in New York.
Designed for discretionary PM conversations and systematic execution discipline.
QuantBot by Sachi AI LLC (New York, NY) | Confidential Product Preview | Sachi AI LLC reserves intellectual property rights.