ProofHybridIntelligence
Humans where you want them. Tech where you don't.
What it means
Proof Hybrid Intelligence is our proprietary approach to private markets operations. It combines the irreplaceable judgment, relationships, and contextual understanding of experienced professionals with purpose-built technology that handles the repetitive, data-intensive work they shouldn't have to.
Your team focuses on what they do best — sourcing deals, building relationships, and making investment decisions — while our technology handles data ingestion, validation, reconciliation, and reporting at scale. No more spreadsheet gymnastics. No more manual errors.
Faster reporting cycles. Fewer operational errors. Better data quality across every fund in your portfolio. PHI delivers measurable improvements to NAV accuracy, turnaround times, and investor satisfaction — translating directly to stronger fund performance and LP confidence.
Why it matters
The private markets industry manages over $13 trillion in assets, yet the majority of operational workflows still depend on manual processes, disconnected systems, and inherited spreadsheets.
Fund administrators, GPs, and LPs lose thousands of hours annually to tasks that should be automated — not because the technology doesn't exist, but because most solutions force a choice: humans or machines.
PHI rejects that false binary. The future of private markets operations is neither fully automated nor purely manual. It's intelligently hybrid — and that's exactly what we've built.
Examples
Due Diligence
Comprehensive investment analysis powered by human expertise and machine precision working in concert.
- Relationship assessment & management meetings
- Strategic fit evaluation & thesis alignment
- Qualitative risk judgment & negotiation
- Data room document extraction & analysis
- Financial model validation & stress testing
- Comparable deal benchmarking at scale
Portfolio Monitoring
Real-time oversight that blends operational intuition with continuous automated surveillance.
- Investment committee decision-making
- LP communication & relationship management
- Strategic intervention & value creation
- Real-time data aggregation & normalization
- Anomaly detection & early warning signals
- Automated KPI tracking & trend analysis
Fund Administration
Accurate, timely fund operations where automation handles volume and humans ensure precision.
- Complex NAV review & sign-off
- Investor relations & query resolution
- Regulatory interpretation & compliance
- Automated reconciliation & matching
- Capital call & distribution processing
- Fee calculation & waterfall modeling
Investor Reporting
Institutional-grade reporting that combines narrative insight with automated data precision.
- Narrative insights & strategic commentary
- Client-specific customization & context
- Quality assurance & final review
- Automated data compilation & validation
- Template generation & formatting
- Multi-format distribution & scheduling
Risk Assessment
Layered risk analysis where quantitative models inform — but never replace — experienced judgment.
- Qualitative judgment & scenario planning
- Stakeholder impact assessment
- Risk appetite calibration & governance
- Quantitative modeling & simulation
- Cross-portfolio correlation analysis
- Regulatory exposure scanning & alerts
Protocols &
Guiding Principles
Human Authority
Every consequential decision is made or validated by a qualified professional. Technology informs — humans decide.
Transparent Augmentation
When AI or automation is used, it is clearly identified. Clients always know what is human-driven and what is machine-assisted.
Continuous Accountability
Every output — whether generated by a person or a model — is subject to review, audit, and correction. No black boxes.
We will never replace human judgment with unsupervised automation on matters of material consequence.
User ControlWe will disclose to clients when AI-generated outputs are used in deliverables or recommendations.
TransparencyWe will maintain full audit trails for every data transformation, model output, and automated decision.
TransparencyWe will test all models against bias, drift, and error before deployment — and continuously after.
AccuracyWe will not train proprietary models on client data without explicit, informed consent.
PrivacyWe will ensure every client retains full ownership and portability of their data at all times.
User ControlWe will design systems that degrade gracefully — if the technology fails, operations continue.
SandboxingWe will invest in the ongoing education of our team to understand, question, and govern AI tools.
TransparencyWe will publish our methodologies and invite scrutiny from clients, regulators, and peers.
TransparencyWe will refuse to deploy technology that we cannot explain, defend, or audit.
Accuracy