The AI Family Office Masterclass

Architect or Reinvent Your Family Office for the AI Era—Faster, Smarter, Sovereign.
Led by Angelo Robles | June 23-24 2025 | New York City 

This is your window. Two days. One decision. A lifetime of advantage.

Angelo Robles’s SFO Continuity Presents

Welcome to Your AI Transformation

Part I: Laying the Sovereign AI Foundation 

(Flow for Day 1)

1. Defining Your AI North Star & Understanding the Landscape: 

* Personalized Deep Dive: We begin by exploring specific motivations, goals, and expectations for integrating AI into your family office.

Implementing Strong Governance

AI governance, in a fluid regulatory environment. We go beyond the policy level and explore how to operationalize governance into how you build and integrating AI solutions in the family office

* Human in Command (Segregation of Duties): Ensuring humans retain final approval for critical actions like wire transfers or significant investment decisions.

* Secure AI Environments (Ring-Fencing): Maintaining separate sandbox and production environment

Section 1(a) Instructor: Bennett B. Borden Esq. (all instructor bios at the end of this web page)

* The Sovereignty Imperative: We’ll establish why local control over data and AI processes is crucial for family offices, focusing on mitigating risks (jurisdictional, vendor-related) and protecting sensitive information.

* AI for Family Offices: An overview of the AI technologies most relevant and transformative for your unique context.

* Current Operations Unpacked: Leveraging the attendee questionnaire, we’ll discuss existing setups – what works, what doesn’t, and where AI can make the most significant impact.

Section 1(b) Instructor: Angelo Robles  

2. Establishing Your Sovereign Compute Environment: 

* The Right Hardware Foundation 

* Our Recommendation: The Apple MacBook Pro 16-inch (M4 Max, 16-core CPU, 40-core GPU, 16-core Neural Engine, 128GB MAXED out memory). We'll discuss why this specific configuration is critical for local AI processing. There are solutions for non Apple users including the Lenovo ThinkPad P16 Gen 2 Intel (16″) Mobile Workstation. You’ll need to max out Processor Power, Memory and Gigabytes (128GB) in your custom order.

If tech savvy and internal IT you should consider the NVIDIA DGX Spark AI Super Computer ‘chip’ you can pre-order on select computers one being Dell, available mid-late summer delivery.

https://www.dell.com/en-us/lp/dell-pro-max-nvidia-ai-dev

* Embracing the "No Touch" Public Cloud Philosophy: Understanding the benefits of keeping your core AI operations and sensitive data within your own secure firewall.

* Unlocking Local LLMs with Ollama: A hands-on introduction to Ollama, enabling you to download, manage, and run powerful Open Source Large Language Models (e.g., Llama 3, Mistral-Medium, DeepSeek-Coder) directly on your laptop, ensuring data privacy.

* How to Harness Multiple LLMs Simultaneously with Hugging Face: Learn to access the vast Hugging Face ecosystem to discover, evaluate, and fine-tune LLMs. We'll cover strategies for using multiple models simultaneously to compare outputs and achieve more targeted results.

* Navigating Prompting: Precision Language as Leverage: LLMs don’t just respond—they reflect. And in your family office, every prompt is a strategic lever.In this session, you’ll learn how to design high-leverage prompts to drive clarity, insight, and speed across legal, investment, and governance workflows

Section 2 Instructor: Angelo Robles 

3. Strategically Integrating Cloud & Hybrid LLM Capabilities: 

* Beyond Local: When External LLMs Add Value: We’ll identify specific scenarios where leveraging leading non-open LLMs like Gemini 2.5 Flash/Pro, Anthropic’s Claude series, or even OpenAI’s ChatGPT for certain deep reasoning tasks can be beneficial. Perplexity Pro (Labs) is a powerful tool for financial research, particularly within the Assets tab for exploring companies and investment themes.

* Secure Hybrid Approaches: Exploring options like Anthropic’s Claude Opus via private-cloud or air-gapped endpoints, offering enhanced capabilities while maintaining a higher degree of control.

* Leveraging AI Within Your Existing Platforms: Maximizing the AI and LLM features already embedded in tools you might use, such as Notion AI or Bloomberg AI, to achieve desired outcomes efficiently.

4. Building Your Family Office's Secure Digital Memory – The Persistence Layer: 

* Organizing Structured Data: The role of PostgreSQL for managing structured holdings data and other relational information critical to your operations.

* Tapping into Unstructured Knowledge: Implementing Vector Databases (e.g., Weaviate, Milvus, pgvector) to store and efficiently query embeddings from your documents, emails, research, and chats – making all your information searchable and usable by AI.

* Ensuring Data Resilience with Immutable Backups: 

* Strategies for an S3-compatible object store within your family‐owned tenancy.

•  The value of local cold storage solutions (e.g., Seagate external drives) for comprehensive backup of your primary machine and data.
•  Discussing the careful, strategic use of commercial clouds (like iCloud) for non-core, non-sensitive data, always with an awareness of potential risks.

Additional Special Lectures Day 1 Include:

FinTech Solutions for Single Family Offices

•  Explore next-generation, often AI-native FinTech platforms that integrate directly into sovereign internal systems. Learn how these tools complement and amplify the capabilities of a fully AI-native family office infrastructure.

New Era Aggregation and Reporting for Single Family Offices

•  Discover powerful, AI-enhanced aggregation and reporting models purpose-built for single family offices. These solutions enable real-time intelligence, seamless integration, and precision reporting within your internal AI stack.

3X Exit Tech Entrepreneur and Single Family Office Principal

•  Legacy is not a strategy. Learn directly from a 3x tech founder and family office principal who is actively building an AI-native single family office—designed to scale intelligence, compress decision time, and eliminate reliance on outdated models.

Special Guest Announcement: This Is a Rare Opportunity

In addition to our world-class curriculum, I’m thrilled to announce a powerful, one-time-only session with someone who embodies the future of family office intelligence:

👉 A 3x exited tech founder
👉 A current single family office principal
👉 And someone who uses AI every single day to make real decisions, manage risk, and compress time in investing, governance, and operations.

He’s not just talking about theory. He’s living it.

Over two days, he’ll open up his AI playbook—sharing what works, what doesn’t, and what’s coming next. 

💡 Day 1: Practical AI Implementation

He’ll walk us through:

• Why AI is moving faster than Moore’s Law (and what Huang’s Law means for you)
• How he uses AI to analyze 10-Ks, earnings calls, and filings in minutes
• Merging Excel + AI to build dynamic financial models in real time
• Auto-generating investment memos, dashboards, and committee materials
• Prompt engineering techniques that drive better, faster insights
• Building secure AI workspaces and reusable prompt libraries

🔑 Key Takeaways:

• Master 5–7 real-world tools you can use immediately
• Cut research time by 70–80% while improving depth
• Build your own AI-enhanced fundamental + technical methodology
• Generate institutional-grade content in minutes, not days
• Create a secure, compliant AI workflow around your most sensitive work

Part II: Activating & Scaling Your AI-Powered Operations 

(Flow for Day 2) 

Special Guest Returns: This Is a Rare Opportunity

👉 A 3x exited tech founder
👉 A current single family office principal
👉 And someone who uses AI every single day to make real decisions, manage risk, and compress time in investing, governance, and operations.

He’s not just talking about theory. He’s living it.

Over two days, he’ll open up his AI playbook—sharing what works, what doesn’t, and what’s coming next.

⚙️ Day 2: AI Leadership, Security & Long-Term Edge

We’ll go even deeper:

• Building ethical and secure AI governance
• Local AI setups that never leave your desktop
• Autonomous multi-agent frameworks for advanced research and analysis
• Leading AI change across your team—even when there’s resistance
• Understanding the second-order effects: how AI will change deal flow, investment strategy, and entire markets

🧠 BONUS Topics:

• The 7 layers of Agentic AI (from task automation to cognitive partnership)
• How to use LoRA/QLoRA to fine-tune sector-specific agents and build AI with an edge

🔑 Key Takeaways:

• Shift from AI consumer to AI architect
• Design a 5–10 year AI strategy that compounds decision quality
• Build your own “agent stack” to create and protect wealth
• Prepare for the real risks—while capturing the asymmetric upside

5. Orchestrating Intelligence: AI Application Layers & Custom Agents: 

* From Models to Applications: Understanding AI Application Layers and the power of AI Agents. We'll look at out-of-the-box solutions like CrewAI and Mantis as starting points.

* Frameworks for Multi-Agent Coordination: 

The Current Landscape: Open Source vs. Commercial Solutions.

The multi-agent AI ecosystem has exploded in 2024-2025, with both open source frameworks and commercial SaaS platforms offering sophisticated coordination capabilities. Microsoft AutoGen, LangGraph, CrewAI, and newer frameworks like OpenAI's Swarm represent the cutting edge of multi-agent orchestration technology.

* Designing Your Bespoke AI Agent Team (Practical Examples): 

* Research-Analyst Agent: Purpose: Automate comprehensive due diligence research and financial analysis

Core Functions:

• Scrapes SEC EDGAR filings automatically (https://www.sec.gov/edgar)
• Synthesizes 10-K and 10-Q reports into executive summaries
• Analyzes PitchBook data for market comparables (https://pitchbook.com)
• Integrates Tegus expert network insights (https://tegus.com)
• Cross-references Bloomberg Terminal data feeds

Technical Stack:

• LLaMA-3 70B for natural language processing
• RAG implementation using Weaviate vector database
• Beautiful Soup and Scrapy for web scraping (https://scrapy.org)
• pandas for financial data manipulation

Output: Standardized investment memos with risk assessments and peer comparisons

Reference Tools:

• SEC EDGAR API documentation: https://www.sec.gov/edgar/sec-api-documentation
• Financial modeling templates: https://www.wallstreetmojo.com

* Macro-Risk Sentinel: Purpose: Early warning system for macroeconomic and geopolitical risks

Core Functions:

• Monitors NewsAPI feeds for breaking economic news (https://newsapi.org)
• Analyzes Federal Reserve communications and FOMC minutes
• Tracks social sentiment from Twitter/X financial feeds
• Scans for tail-risk indicators (currency volatility, yield curve inversions)
• Correlates news events with portfolio exposure

Technical Stack:

• Hugging Face Transformers for sentiment analysis (https://huggingface.co/transformers)
• Python libraries: tweepy, yfinance, fredapi
• Real-time data streams from Alpha Vantage (https://www.alphavantage.co)
• NewsAPI integration (https://newsapi.org/docs) • Output: Daily risk reports with actionable hedging recommendations • Reference Sources:
• FRED Economic Data API: https://fred.stlouisfed.org/docs/api/
• VIX and volatility indices: https://www.cboe.com/tradable_products/vix/

* Tax-Alpha Optimizer: 

Purpose: Maximize after-tax returns through intelligent tax strategy automation

Core Functions:

• Scans all transactions against Section 475 mark-to-market rules
• Identifies QSBS qualification opportunities (https://www.irs.gov/businesses/small-businesses-self-employed/qualified-small-business-stock)
• Monitors wash-sale rule violations across accounts
• Suggests tax-loss harvesting opportunities
• Tracks holding periods for long-term capital gains optimization

Technical Stack:

• Local LLM (Llama-3 70B) with tax law fine-tuning
• Rules engine using Python's drools-python or pyke
• Integration with portfolio management systems (Addepar, Black Diamond)
• IRS Publication 550 reference database

Output: Weekly tax optimization reports with specific trade recommendations

Reference Resources:

• IRS Section 475 guidance: https://www.irs.gov/businesses/small-businesses-self-employed/section-475-mark-to-market-accounting-method-for-traders-in-securities
• Tax-loss harvesting strategies: https://www.bogleheads.org/wiki/Tax-loss_harvesting

* Concierge Bot: 

Purpose: Comprehensive lifestyle and operational management for family office principals

Core Functions:

• Calendar optimization and meeting scheduling via Google Calendar API
• Travel booking and itinerary management through Amadeus API (https://developers.amadeus.com)
• Asset scheduling (jets, yachts, properties) via Airtable databases
• Vendor management and procurement workflows
• Event planning and coordination with staff
• Real estate portfolio maintenance scheduling

Technical Stack:

• GPT-4o or Gemini 1.5 Pro for natural language interaction
• Airtable API for database management (https://airtable.com/developers)
• Google Calendar and Gmail API integration
• Slack/Teams webhooks for staff notifications
• Zapier automation workflows (https://zapier.com)

Output: Seamless coordination of family operations with minimal human intervention

Integration Platforms:

• Google Workspace APIs: https://developers.google.com/workspace
• Airtable API documentation: https://airtable.com/developers/web/api/introduction
• Calendly for external scheduling

* Sourcing High-Quality Information for Your Agents: Identifying and integrating optimal resources (specialized Reddit communities, news sources, subscriptions, FireCrawl by Perplexity Pro users, especially via Perplexity Labs) to feed your AI systems.

Premium Data Sources for Family Office AI Systems:

Financial & Market Data:

• Bloomberg Terminal API (https://www.bloomberg.com/professional/support/api-library/) • Refinitiv Eikon API (https://developers.refinitiv.com)
• S&P Capital IQ Platform (https://www.spglobal.com/marketintelligence/en/solutions/sp-capital-iq-platform)
• FactSet API (https://developer.factset.com)
• Morningstar Direct API (https://www.morningstar.com/products/direct)

Alternative Data & Research:

• Specialized Reddit communities: r/SecurityAnalysis, r/investing, r/ValueInvesting
• Expert network platforms: Tegus (https://tegus.com), Guidepoint (https://www.guidepoint.com)
• Satellite data providers: Orbital Insight (https://orbitalinsight.com)
• Social sentiment: StockTwits API (https://api.stocktwits.com), Twitter Financial APIs

Regulatory & Compliance:

• SEC EDGAR database (https://www.sec.gov/edgar)
• FINRA BrokerCheck API (https://www.finra.org/investors/have-problem/check-your-investment-professional) • Treasury OFAC sanctions lists (https://www.treasury.gov/ofac)
• Global compliance databases: World-Check (https://www.refinitiv.com/en/products/world-check-kyc-screening)

Web Scraping & Automation:

• FireCrawl for intelligent web scraping (https://firecrawl.dev)
• Apify platform for data extraction (https://apify.com)
• Bright Data proxy services (https://brightdata.com)
• ScrapingBee for JavaScript-heavy sites (https://www.scrapingbee.com)

* The Agent Workflow: Transforming single prompts into effective agent teams:

1. Research → 2. Verify → 3. Summarize → 4. Draft → 5. Push to chosen platform.

Section 5 Instructors

Robert Bjarnason (Remotely) Others

6. Notion and ClickUp as Your Central Hubs: Knowledge Management & Workflow Orchestration 

* Why both ClickUp and Notion Excel for the AI-Integrated Family Office: 

* Unified Interface: A single place for documents, databases, wikis, and project management, simplifying interaction for both humans and AI agents.

* Developer-Friendly API: Enabling seamless read/write access for your AI agents.

* Human-Centric Design: An intuitive platform that principals and staff can easily adopt.

* Precision Access Control: Ensuring data security and appropriate visibility for different stakeholders.

In Practice: 

* Master Knowledge Graph: Centralizing SOPs, org charts, trust documents, and vendor lists.

* Dynamic Project Workspaces: Tracking diligence processes, estate planning initiatives, and other projects with all related tasks, documents, and communication history.

* The API as a Bridge: Agents autonomously creating and updating ClickUp and Notion pages; web-hooks triggering notifications in Slack/Teams.

•  A "single pane of glass" for principals to get status updates and insights.

Section 6(a) Instructor: Greg Silverman

* Weaviate Enterprise for Advanced Knowledge Retrieval:

Document Vectorization Process

• Content Ingestion:
• Automated processing of PDFs, Word documents, emails, and web content
• OCR capabilities for scanned documents and images
• Integration with Google Drive, Dropbox, and SharePoint (https://weaviate.io/developers/weaviate/modules/retriever-vectorizer-modules)
• Semantic Understanding:
• Advanced embedding models that understand financial terminology and context
• Multi-language support for international family office operations
• Entity recognition for people, companies, and financial instruments
• Reference: Weaviate Documentation (https://weaviate.io/developers/weaviate)

Retrieval-Augmented Generation (RAG) Implementation

• Intelligent Search:
• Natural language queries that return relevant documents with precise citations
• Contextual understanding that goes beyond simple keyword matching
• Ability to synthesize information across multiple documents and data sources
• Accuracy and Verification:
• Direct citations to source documents prevent AI hallucinations
• Confidence scoring for retrieved information
• Version control and document lineage tracking
• Integration Points:
• Seamless connection with Ollama local models for private processing
• API endpoints for custom family office applications
• Real-time updates as new documents are added to the knowledge base
• Reference: RAG Implementation Guide (https://weaviate.io/blog/what-is-rag)

7. Architecting for Seamless Integration, API Management & Robust Governance:

Building a Cohesive Integration Layer:

FastAPI Micro-Gateway

Purpose: Central routing and management hub for all AI model interactions

Key Features:

• Single secure internal endpoint (e.g., https://ai-gateway.familyoffice.local/api/v1/)
• Route abstraction: /llm/chat, /agent/diligence, /analysis/portfolio
• Vendor-agnostic interface supporting Ollama, OpenAI, Anthropic, and Google APIs
• Request/response logging for compliance and debugging
• Rate limiting and authentication middleware

Technical Implementation:

• Built on FastAPI framework (https://fastapi.tiangolo.com)
• Async/await support for high-performance concurrent processing
• Automatic API documentation generation via OpenAPI/Swagger
• Integration with Pydantic for request/response validation

Security Features:

• JWT token authentication with role-based access control
• Request sanitization and input validation
• API key rotation and management
• SSL/TLS termination and certificate management

Reference Documentation: FastAPI Security Best Practices (https://fastapi.tiangolo.com/tutorial/security/)

HashiCorp Vault Integration  

Secrets Management Strategy:

• Centralized storage for all API keys, database credentials, and certificates
• Dynamic secrets generation for database connections
• Automatic credential rotation policies (90-day cycles for high-risk credentials)
• Encryption at rest and in transit using AES-256 and TLS 1.3

Implementation Details:

• Vault Agent for seamless application integration
• AppRole authentication for service-to-service communication
• Policy-based access control with least-privilege principles
• Audit logging for all secret access and modifications

High Availability Setup:

• Multi-node Vault cluster with Raft consensus
• Auto-unsealing using cloud KMS or HSM integration
• Backup and disaster recovery procedures

Reference: HashiCorp Vault Documentation (https://www.vaultproject.io/docs)

Security Compliance: FIPS 140-2 Level 2 certification for cryptographic operations

EventBridge Orchestration (AWS Integration)

Event-Driven Architecture:

• Decoupled system components communicating via events
• Custom event schemas for family office business processes
• Dead letter queues for failed event processing
• Event replay capabilities for system recovery

Integration Patterns:

• Email triggers from family office inbox → Deal intake workflow
• Market data updates → Portfolio rebalancing alerts
• Calendar events → Travel booking automation
• Document uploads → AI analysis and categorization

Monitoring and Observability:

• CloudWatch metrics and alarms for event processing
• Distributed tracing using AWS X-Ray
• Custom dashboards for business process monitoring

Cost Optimization:

• Event filtering to reduce unnecessary processing
• Batch processing for bulk operations
• Reserved capacity for predictable workloads

Reference: AWS EventBridge Best Practices (https://docs.aws.amazon.com/eventbridge/latest/userguide/eb-best-practices.html)

Detailed "Diligence Burst" Workflow Implementation:

1. Ingestion & Trigger Processing

Email Processing System:

• Microsoft Graph API integration for Outlook (https://docs.microsoft.com/en-us/graph/api/overview)
• Gmail API for Google Workspace environments (https://developers.google.com/gmail/api)
• Intelligent email classification using fine-tuned BERT models
• Attachment extraction and virus scanning via ClamAV

Webhook Management:

• Preqin data feeds integration (https://www.preqin.com/our-products/preqin-anywhere)
• PitchBook data feeds integration
• Custom webhook validation and replay mechanisms
• Rate limiting and backpressure handling

Metadata Extraction:

• Company name, sector, deal size, and contact information parsing
• Document type classification (deck, financials, legal docs)
• Sentiment analysis of initial communications
• Automatic Notion database population with structured data

Reference Tools:

• spaCy for named entity recognition (https://spacy.io)
• Apache Tika for document text extraction (https://tika.apache.org)

2. Agent Activation & Coordination

AutoGen Multi-Agent Framework:

• Research Agent: Specialized in financial analysis and market research
• Compliance Agent: Focused on regulatory requirements and risk assessment
• Sentiment Agent: Analyzes management quality and market sentiment
• Meta-Analyst Agent: Synthesizes findings from all specialized agents

Agent Communication Protocol:

• Structured message passing using JSON schemas
• Conversation history preservation for audit trails
• Conflict resolution mechanisms for contradictory findings
• Progress tracking and status reporting to human supervisors

Resource Allocation:

• Dynamic scaling based on deal complexity and urgency
• GPU allocation management for compute-intensive analysis
• Timeout handling and graceful degradation

Reference: Microsoft AutoGen Documentation (https://microsoft.github.io/autogen/)

3. Contextual Retrieval & Knowledge Integration

Vector Database Queries:

• Semantic search across historical deal documents
• Similarity matching with previous investment decisions
• Industry report and research note retrieval
• Regulatory filing analysis for comparable companies

External Data Integration:

• Real-time market data from Bloomberg/Refinitiv APIs
• Social media sentiment from specialized financial platforms
• News article analysis using NewsAPI and Alpha Vantage
• Patent and intellectual property searches via USPTO APIs

Knowledge Graph Construction:

• Entity relationship mapping (companies, executives, investors)
• Network analysis for finding connections and potential conflicts
• Timeline construction for corporate events and market cycles

Reference:

• Weaviate Vector Search (https://weaviate.io/developers/weaviate/search)
• Knowledge Graph construction tools (https://neo4j.com/developer/graph-data-science/)

4. Intelligent Synthesis & Report Generation

AI-Powered Analysis:

• Financial model validation and sensitivity analysis
• Competitive positioning assessment using Porter's Five Forces
• Management team evaluation based on track record analysis
• Risk factor identification and quantification

Document Generation:

• Standardized investment memo templates in Notion
• Executive summary with key findings and recommendations
• Detailed appendices with supporting data and calculations
• Risk assessment matrix with mitigation strategies

Citation and Source Management:

• Automatic footnote generation with source document references
• Hyperlinks to original documents in the knowledge base
• Version control for iterative analysis improvements
• Confidence scoring for each analysis component

Quality Assurance:

• Cross-validation between multiple AI models
• Fact-checking against authoritative data sources
• Bias detection and correction mechanisms

Reference: Notion API for automated content creation (https://developers.notion.com/reference/post-page)

5. Human Oversight & Decision Framework

Review Interface Design:

• Executive dashboard with key metrics and alerts
• Side-by-side comparison with similar historical deals
• Interactive charts and visualizations for financial projections
• Comment and annotation system for collaborative review

Decision Support Tools:

• Scenario analysis with multiple outcome projections
• Monte Carlo simulations for risk assessment
• Benchmarking against portfolio allocation targets
• Impact analysis on overall family office strategy

Workflow Management:

• Approval routing based on deal size and risk profile
• Time-bounded decision windows with escalation procedures
• Integration with family office investment committee calendar
• Automated follow-up reminders and status updates

Reference:

• Tableau for data visualization (https://www.tableau.com/developer)
• Power BI integration options (https://docs.microsoft.com/en-us/power-bi/developer/)

6. Audit Trail & Compliance Infrastructure

Comprehensive Logging System:

• Immutable audit trail using blockchain or distributed ledger technology
• JSON-formatted logs with standardized schema
• Real-time log aggregation using ELK Stack (Elasticsearch, Logstash, Kibana)
• Automated log rotation and archival policies

Regulatory Compliance Features:

• SEC recordkeeping requirements for family office exemption
• GDPR compliance for EU family office operations
• SOX-style controls for internal audit processes
• Regular compliance reporting and attestation

Data Governance:

• Classification and labeling of sensitive information
• Access control logging and privilege escalation tracking
• Data retention policies aligned with regulatory requirements
• Secure deletion and right-to-be-forgotten implementation

Monitoring and Alerting:

• Real-time anomaly detection for unusual access patterns
• Failed authentication and authorization attempt tracking
• Performance monitoring and capacity planning
• Business continuity and disaster recovery procedures

Reference:

• ELK Stack documentation (https://www.elastic.co/guide/index.html)
• SEC family office regulation guidance (https://www.sec.gov/investment/im-guidance-2011-01.pdf)

Advanced Audit Trail Implementation

Real-World Immutable Record-Keeping Solutions

Modern family offices require enterprise-grade audit trail systems that satisfy regulatory requirements while providing complete data integrity. The following represents a comprehensive toolkit of proven technologies and platforms currently deployed in production environments.

Blockchain Integration Platforms:

Trail Ledger (Enterprise Blockchain Audit Trail)

Overview: De facto standard for blockchain-based audit trail serving as the enterprise solution for compliance-related operations that can be codified and automated on blockchain

Key Features:

• Tamper-proof exact audit trails enabling auditors and regulators to audit infrastructure
• Proof of appropriate controls for securing personal, sensitive, and proprietary data
• Cross-chain implementation supporting Hyperledger Fabric, Ethereum (Polygon), and Solana
• Open-source standards (Cloud Native) for interoperability and future-proofing

Enterprise Benefits: Streamlined workflow for organizing audits and mitigating IT infrastructure risks with short-lived tokens providing day-accurate dataflow views

Implementation: Available as SaaS model extendable with on-premises infrastructure, designed from scratch with hybrid deployment requirements

Website: https://trailledger.com/

Security: Multiple independent security audits with enterprise-level hybrid cloud capabilities

Hyperledger Fabric Enterprise Implementation

Technical Foundation: Open-source, modular blockchain framework maintained by the Linux Foundation with over 120,000 organizations and 15,000 engineers collaborating

Enterprise Adoption: IBM Blockchain Platform provides SLAs and 24x7 enterprise support for Hyperledger Fabric implementations

Real-World Examples:

• Medical Records Management: Proof-of-concept applications managing medical record storage with patients using private keys to access portals and grant/revoke doctor access
• Supply Chain Tracking: Tamper-proof audit trails for supply chain transparency and authenticity verification
• Financial Services: Home Depot implements IBM Blockchain technology to resolve vendor disputes and improve supply chain efficiency

Key Capabilities:

• Private and confidential blockchain framework with permissioned networks
• Smart contracts (chaincode) for automated business logic execution
• Advanced privacy controls sharing only desired data among known network participants

Developer Resources:

• Official documentation: https://hyperledger-fabric.readthedocs.io/
• Hyperledger Fabric Certified Practitioner (HFCP) certification available
• Blockchain Verifier tools for checking blockchain ledger integrity: https://github.com/shimos/bcverifier

Enterprise Quorum Implementation (JP Morgan/ConsenSys)

Architecture: Fork of Ethereum optimized for enterprise use with enhanced privacy, robustness, scalability, and performance

Key Advantages:

• Simplicity and high maturity reusing existing Ethereum technology
• Maintains synchronization with upcoming public Ethereum versions
• Operates without cryptocurrency requirements for pure audit trail applications
• RAFT consensus algorithm for increased scalability and participant management

Security Features:

• Permissioned network where only authorized nodes can participate, verify transactions, and maintain ledger state
• All incoming and outgoing communications encrypted with access control for recorded data
• Smart contracts provide advanced audit trail functionality

Implementation Guide: Detailed implementation research available at https://www.researchgate.net/publication/356610206_A_Blockchain-Based_Audit_Trail_Mechanism_Design_and_Implementation

Comprehensive Log Management Infrastructure:

ELK Stack Enterprise Deployment (Elasticsearch, Logstash, Kibana)

Industry Standard 

Building a Cohesive Integration Layer: 

* FastAPI Micro-Gateway: Creating a single, secure internal URL (e.g., /llm/chat, /agent/diligence) for all AI model interactions, abstracting away vendor-specific endpoints.

* HashiCorp Vault: Implementing best practices for secrets management (API keys, credentials) with rotation.

* EventBridge (if using AWS components): For orchestrating cross-system triggers and workflows.

* Illustrative Workflow – The "Diligence Burst”:

1. Ingestion (Trigger): An email or webhook (e.g., from Preqin) is parsed by FastAPI and relevant metadata is logged in a Notion "Deal Intake" database.

2. Agent Activation (Spin-Up): AutoGen initiates specialized agents (Research, Compliance, Sentiment).

3. Contextual Retrieval (RAG): Each agent queries your Vector DB (via Weaviate/PGVector) for existing relevant information.

4. Intelligent Synthesis: A Meta-Analyst Agent compiles findings into a concise 1-page memo in Notion, complete with supporting citations.

5. Human Oversight (Loop): The CIO reviews the memo within Notion, provides feedback, and makes a decision (Accept/Reject), potentially triggering further automated processes.

6. Audit & Compliance (Governance): All agent calls and actions are logged via FastAPI, with hashes potentially written to a private ledger for immutable record-keeping.

* The Immutable Audit Trail: The importance of time-stamped JSON logs for every AI-driven action, satisfying regulatory requirements (e.g., SEC family-office exemption).

Section 7 Instructor: Georgy Marrero, Technologist

8. Managing Risk & Phasing Your AI Rollout: 

Essential Governance and Risk Controls 

* Comprehensive Privacy Regime: Implementing a zero-trust network architecture, utilizing hardware security keys (e.g., YubiKey), and enabling token-level logging for AI interactions.

* Automated Regulatory Technology (Reg-Tech): Using AI to auto-generate drafts for Form PF/CRS and flag potential Section 13 filing requirements.

Your Strategic Implementation Roadmap: Iterate → Scale → Compound: 

1. Pilot Phase (e.g., Days 0-90): Focus on one high-value, measurable workflow (like an auto-composed weekly macro brief). Aim to quantify time saved and decision quality improvement.

2. Rollout Phase (e.g., Quarters 2-3): Systematically extend AI agents and workflows to other key areas such as PE deal flow analysis, legal clause extraction, or lifestyle operations.

3. Compound Growth Phase (e.g., Year 1+): Advance to more sophisticated techniques like ensemble models, multi-agent debate frameworks, and incorporating reinforcement learning from human feedback (RLHF) to embed AI deep within your family’s investing DNA.

Your Quick-Start Checklist for Success:

1. Establish a "privacy-first" AI policy as your foundational document.
2. Allocate a realistic budget
3. Select a single, impactful workflow for your initial automation project; set a clear goal
4. Mandate an AI literacy "sprint" (e.g., 6-week micro-learning program) for principals and key staff.
5. Schedule regular (e.g., bi-monthly) "Agent Council" meetings where humans and AI agents collaboratively review outputs and refine processes.

9. Distilling Key Lessons & Embracing the Future: 

Core Principles for Building Your AI Family Office 

1. Start Small, Containerize: Begin with a manageable scope (e.g., one GPU box, Dockerized Ollama, FastAPI). Prove ROI on a single use-case, then expand.

2. Secure Your Secrets: Never hard-code API keys; use tools like Vault for secure token management.

3. Treat Prompts as Code: Implement version control (e.g., Git) for your prompts to manage drift and ensure consistency.

4. Optimize Human Involvement: Design agents to handle ~90% of a task, with humans providing critical decision-making at key junctures.

5. Own Your Core Assets: While leveraging SaaS for UI or peripheral functions is fine, keep your models, data, and embeddings on hardware you control.

Pivotal Takeaways from Our Journey:

* Sovereignty with Strategic Cloud Use: You can maintain core cognitive functions on-premise while selectively tapping best-in-class cloud APIs for specialized, non-core tasks.

* The Compounding Advantage: Every day your AI models train on your proprietary data and decisions, your competitive moat widens.

* Culture is Key: Success is as much about fostering a culture of curiosity, eliminating drudgery, and celebrating machine-augmented achievements as it is about technology.

* The Vision Realized: By building it right, your "AI Family Office" evolves into a 24/7 intelligent entity—continuously scanning, reasoning, and compounding insights, long after your human teams have logged off. This isn't just "using AI"; it's operating a private intelligence factory where software, models, and humans collaborate as one, defining the competitive edge for the next decade.

Logistics

📍 Location: New York City
🗓 Dates: June 23-24, 2025
👥 Seats: 10 Families Only
💵 Investment: $15,000 

🔹 Includes: 

•  Full Intelligence Stack Blueprint
•  Private Resource Guide (engineers, AI builders, machine learning talent)
•  Customized 90-Day Launch Plan for Building Your AI Family Office
•  Private Cognitive Investing Dinner Experience

Tradition Won't Save You. Velocity, Vision, and Intelligent Design Will. 

The future doesn’t reward tradition.
It rewards velocity—how fast you learn, adapt, and act.
It rewards vision—the clarity to see shifts before they’re obvious.
It rewards design—how intelligently you build systems that scale beyond human limits.

In this new era, elite humans coordinated with private AI and autonomous agent networks will radically outperform traditional teams—
Not by working harder, but by thinking faster, seeing deeper, and executing with machine precision.

Legacy family office structures weren’t built for this.
They were designed for stability, compliance, and slow-cycle administration.
They are artifacts of a different world—a world that no longer exists.

The winners will not be the ones who inherit the best playbooks.
They will be the ones who build better engines. 

The future belongs to the family offices that become sovereign systems of intelligence—designed for acceleration, resilience, and exponential cognition.

Secure Your Future Before the Window Closes!

Let Me Be Very Clear:

•  Most family offices will not survive the AI transition intact. 
•  You have 12–24 months to get ahead—or be overtaken. 
•  If you wait for "case studies" and "industry norms," you will have already lost the edge. 

The future will belong to those who think faster, move earlier, and architect sovereignty now. The families who join this Masterclass will lead in the next era. Those who hesitate will spend a decade trying — and failing — to catch up.

This is your chance.
2 days.
10 families.
A lifetime of asymmetric advantage. 

IF YOU HAVEN'T YET:

Secure your seat. Shape the future. Own the edge.

👉 Click Here to RSVP and Pay to Secure Your Spot 

Guest Lecturers — Some In Person, Some Digital:

Bennett B. Borden

Founder & CEO, Clarion AI Partners | AI Governance & Algorithmic Bias Expert

Bennett B. Borden is a globally recognized expert in AI governance, algorithmic bias, and the intersection of law, policy, and advanced technology. As both a seasoned lawyer and data scientist, he has advised leading generative AI companies and Fortune 500 clients—including OpenAI, Microsoft, Anthropic, and Amazon—on the legal, ethical, and strategic deployment of AI systems.

Founder and CEO of Clarion AI Partners, Bennett has helped shape AI governance frameworks across sectors including finance, healthcare, retail, manufacturing, and government. His background in U.S. Intelligence, prior role as Chief Data Scientist and Partner at DLA Piper, and leadership at the Information Governance Initiative give him rare insight into how AI reflects—and amplifies—human behavior.

Michael Sikorsky

Founder, & CIO of his Family’s Single Family Office, Founder Copia Wealth Studios. EY Entrepreneur of the Year Winner, Deloitte Fast 500 Recipient, and serial innovator - he sold his first company to ThoughtWorks at age 28.  Michael is passionate about education and has guest lectured at Harvard Business School, Stanford, MIT, Columbia Business School, and the World Economic Forum. His insights, products, and ideas are featured in Wired, Financial Times.

Mark Madsen

Multi-Sector AI & Infrastructure Expert | Chief Technology Officer, Copia Wealth Studios. Mark Madsen is a seasoned technology executive with over 25 years of experience across fintech, ed-tech, commerce, and healthcare. As CTO of Copia Wealth Studios, he leads cutting-edge development at the intersection of finance and innovation.

Mark began his career in industrial automation, pioneering AI-driven machine vision systems before the iPhone era. He has since held multiple CTO roles in ed-tech and fintech, and led a boutique consultancy serving clients from airlines to banks to governments. With degrees in Physics and Computer Science from the University of Alberta.

Greg Silverman

Technology Integration Strategies for Family Offices. Greg Silverman is a technologist with over two decades of experience in family office and private wealth management. He brings deep expertise in investment operations and infrastructure and has led complex initiatives across leading firms, including eight years at Geller Advisors (now part of Corient). Greg is the founder of ClarityEdge, a consultancy focused on helping family offices take control of their data, modernize workflows, and implement best-of-breed systems. His approach is hands-on and pragmatic, with a focus on flexibility, control, and lasting value.

Robert Bjarnason

President, CTO & co-founder of Evoly. Robert, an entrepreneur, founded the first internet companies in Iceland in 1993 and Denmark in 1995. He developed the first mobile version of The Sims, created Agent Ruby, an AI chatbot, in 2001, and won two BAFTAs. Between 2006 and 2016 he developed AI solutions for hedge funds, and in 2008, he co-founded the Citizens Foundation to improve public decision-making with collective and artificial intelligence.

Ian Palmer Cook, PhD

AI and machine learning executive with over 15 years of experience transforming algorithms into business outcomes across healthcare, defense, and fintech. Currently SVP of AI at Qloo, he has built enterprise-scale LLM platforms processing thousands of documents daily, developed electricity price forecasting systems with sub-cent accuracy, and architected ML analytics platforms processing terabytes of Department of Defense procurement data. From his early work at kWantera and Govini to his current role pioneering Model Context Protocol servers and provider-agnostic multi-LLM infrastructure, Ian bridges the gap between technical innovation and strategic business value, consistently building solutions that transform how organizations operate in an AI-driven marketplace.

Georgy Marrero

Technologist who for over two decades has been at the frontier of deep tech & AI. Georgy engineered mission-critical computer vision, AR, and language models now used by 100 million+ users every day. After seven years in Big Tech (Meta GenAI, Facebook Reality Labs, Amazon Alexa), two years as a VC-backed founder at the blockchain-AI intersection, and two years researching computer vision & machine learning (CVML) at the University of California—Berkeley, he has built deep expertise in scaling both code and companies, taking products from zero to one, and turning research into execution. Today he channels that expertise as a fractional CTO and advisor to select high-growth startups and organizations.

Angelo Robles 

A global authority on family offices, renowned for his bold vision, first-principles thinking, and relentless push toward future-proofed wealth structures. As a founder, educator, and innovator, Angelo has spent over 20 years helping the world’s most successful families architect sovereign, resilient, and intelligent family offices.

Angelo is not just an advisor—he is a principal.
He founded and actively operates his own Wyoming-based Single Family Office and HoldCo, giving him firsthand insight into the real-world demands of running capital, governance, and legacy in an era of exponential change.

As the creator of SFO Continuity, and now the architect of the AI Family Office movement, Angelo empowers families to break free from outdated, administrative-era structures—and build cognitive, AI-native systems designed to thrive in the age of machine intelligence.

He is one of the few voices in the industry willing to challenge legacy models—and replace “best practices” with first principles, strategic clarity, and sovereign control.

"The majority of family offices today are built for a pre-AI world.
The future demands new intelligence, new structures—and new leaders."
— Angelo Robles

Founder. Principal. Futurist. Architect of the AI Family Office.

IF YOU HAVEN'T YET REGISTERED...

Click Here to RSVP and Pay to Secure Your Spot 

Click Here to Schedule a Call With Angelo Robles. 

Your future begins here. Don’t let this opportunity pass you by.