KARISSARUTHERFORD

Crafted by Karissa Rutherford, this groundbreaking estate planning platform reimagines legacy management for the digital age, addressing 2025’s complexities—quantum computing risks, AI-governed inheritances, and cross-jurisdictional asset ownership. Combining legaltech automation, behavioral psychology insights, and cryptographic security, the tool empowers families to protect multigenerational wealth while minimizing familial conflicts and tax inefficiencies.

Core Innovations & Methodologies

1. Holistic Asset Mapping with AI Synthesis

  • Omnichannel Integration: Syncs traditional assets (real estate, stocks) with digital holdings (NFTs, DeFi portfolios, metaverse land) and AI-managed accounts (robo-advisor trusts).

  • Dynamic Will Updates: AI monitors life events (e.g., divorce filings, childbirth) and regulatory shifts (2025’s updated U.S. SEC crypto-inheritance rules) to trigger real-time adjustments.

  • Conflict Prediction Algorithms: Analyzes family communication patterns to flag potential disputes over sentimental assets (e.g., heirlooms, generative art collections).

2. Quantum-Secured Legacy Protocols

  • Post-Quantum Encryption: Protects sensitive documents against 2030-era quantum decryption threats using lattice-based cryptography.

  • Biometric Multi-Signature Wallets: Requires familial consensus (e.g., retina scans + voiceprints) to release high-value assets, preventing unilateral misuse.

3. Tax Optimization Across Borders

  • AI Jurisdiction Arbitrage: Simulates inheritance outcomes under 2025’s EU Digital Inheritance Act, U.S. STEP Act revisions, and Asian crypto probate laws.

  • Charitable Trust Automation: Allocates assets to ESG-aligned DAOs (Decentralized Autonomous Organizations) while maximizing tax deductions.

2025-Specific Applications

  • AI-Generated Executors: Deploys GPT-6-enabled virtual executors to enforceterms, resolving ambiguities in real-time (e.g., interpreting “equal shares” in fluctuating crypto portfolios).

  • Metaverse Legacy Preservation: Converts 2D wills into interactive 3D holograms, allowing testators to verbally explain asset distributions via AI avatars.

  • Genetic Data Governance: Integrates with bio-banking services to manage posthumous access to DNA records under 2025’s Global Bioprivacy Accord.

User Impact & Validation

  • Case Study 1: A multinational family reduced probate costs by 52% using cross-border tax simulations, avoiding double taxation on Singaporean REITs and German bond holdings.

  • Case Study 2: Resolved a $12M NFT inheritance dispute preemptively via AI-mediated “virtual family mediation rooms,” preserving relationships.

  • Enterprise Adoption: Trusts like UBS and Fidelity now embed the tool to automate RMDs (Required Minimum Distributions) for 10,000+ retirement accounts.

Ethical & Inclusive Design

  • Bias-Free AI Training: Models are audited for fairness across genders, cultures, and LGBTQ+ family structures (e.g., non-binary inheritance rights).

  • Low-Income Accessibility: Offers sliding-scale pricing and pro bono workshops on “Digital Legacy Essentials” for underserved communities.

  • Eco-Conscious Legacy Options: Matches asset allocations to users’ sustainability values (e.g., converting inheritance funds into carbon-offset trusts).

This study aims to explore how to utilize OpenAI's API to develop an intelligent legacy planning assistant system capable of understanding complex legal terminology, family relationships, and financial information to provide personalized estate distribution recommendations. Core research questions include: 1) How can large language models accurately interpret inheritance laws across different jurisdictions? 2) When dealing with sensitive family relationships and financial information, how can AI systems balance professional advice with ethical considerations? 3) How do user interaction patterns with AI legacy planning systems affect final decision quality? 4) How can model fine-tuning adapt systems to legacy planning customs across different cultural backgrounds? Investigating these questions will help understand the application boundaries and optimization pathways for AI in legal services.