D-Infinite: Interactive Business Plan
D-Infinite Logo

Redefine Productivity.
Eliminate Decision Fatigue.

D-Infinite is an advanced AI that creates a Digital Decision Clone to autonomously handle operational decisions, freeing executives for high-value strategic work.

Value Proposition

Time is Capital

Quantifiable ROI by reclaiming valuable senior management time.

Seed Funding Ask

$5M

For Phase 1 R&D and secure beta deployment.

The Opportunity

High-value professionals are bogged down by repetitive decisions, leading to fatigue and misallocated cognitive resources. This is a significant, quantifiable problem in the enterprise space.

The Daily Decision Drain

Up to 40% of a professional's day is spent on moderate, repetitive decisions.

Total Addressable Market (TAM)

Initial TAM is estimated at $250 Million, targeting decision-makers in Fortune 5000 companies.

The Solution: An Autonomous Clone

D-Infinite is not another suggestion tool. It's an autonomous agent that learns a user's decision-making style with 99% accuracy to act on their behalf, integrated directly into their existing workflow.

📥

1. Data Ingestion

🧠

2. Clone Creation

⚙️

3. Autonomous Action

📈

4. Complex Support

Secure Preference Mapping

D-Infinite performs a secure, encrypted ingestion and analysis of all approved digital communications and files to understand the user's historical decisions and communication style.

Development Roadmap

Phase 1: R&D and Core Model

Timeline: 12 Months

  • Finalize Preference Mapping Engine (PME) security architecture.
  • Develop secure, compliant data ingestion and encryption protocols.
  • Build MVP for basic decision types (Scheduling, Triage).
  • Secure initial Seed Funding ($5M).

Phase 2: Beta & Accuracy Validation

Timeline: 12-18 Months

  • Deploy MVP within 5-10 pilot organizations under strict NDA.
  • Iteratively train model toward 99% accuracy on moderate decisions.
  • Focus on user feedback loop (user override is primary training signal).

Phase 3: Commercial Launch

Timeline: 18-36 Months

  • Full commercial launch with Tiered Subscription Model.
  • Develop robust API for seamless enterprise integration (CRM, ERP).
  • Begin development of "Group Decision Clones".

Business Model

Our strategy is a high-touch, consultative sales approach focused on ROI, supported by a tiered subscription model designed for individuals, teams, and entire enterprises.

Individual

$2,500/user/year

For entrepreneurs & consultants.

  • ✅ Type A Decisions (Basic)
  • ✅ Complex Recommendations
  • ✅ Standard Integration

Most Popular

Professional

$5,000/user/year

For Directors & VPs.

  • ✅ All Individual Features
  • ✅ Type B Decisions (Moderate)
  • ✅ Full Workplace Integration

Enterprise

$10,000+/user/year

For C-Suite & large teams.

  • ✅ All Professional Features
  • ✅ Dedicated Security SLA
  • ✅ Group Decision Cloning

Trust & Governance

The success of D-Infinite hinges entirely on public trust and absolute data integrity. Our architecture is built on a foundation of security, auditability, and ethical governance.

🛡️

Zero-Knowledge Security

Our core models are designed so we can never access a user's raw data. End-to-end encryption and strict compliance (GDPR, CCPA) are non-negotiable.

⚖️

Liability & Auditability

Every autonomous decision is logged for 100% auditability. Clear legal terms and a precise definition of the "99% accuracy" claim ensure transparency.

🌍

Ethical AI Governance

An independent Ethics Board will monitor for bias and ensure the technology is never misused, protecting both our users and the integrity of the system.

The Team

Our founding team combines deep enterprise experience with cutting-edge AI research and a commitment to ethical governance.

Tyler Harron

CEO, Strategy & Sales

Experienced founder in enterprise SaaS with 15+ years scaling B2B platforms.

Priscilia Gough

COO, Operations & Finance

Expert in high-growth operational scalability and financial modeling for startups.

CTO (Recruiting)

PME Development, Security

Immediate priority hire. Must possess a PhD in ML/Differential Privacy and expert knowledge in large-scale secure data systems.