Aegisight AI
One Platform. Zero Surprises.
Project site: mit.aegisight.ai Prototype: aegisight.ai
Our Vision & Mission
Our Vision
To transition the global enterprise from reactive crisis management to Predictive Risk Orchestration. We verify the world's data through a Universal Forensic Pipeline that acts as the central nervous system of your business.
Our Mission
To identify the AI Fingerprints of failure before they manifest. We transform raw signal into Verified Signatures—providing the specific "What, Why, and When" needed to ensure operational resilience.
MIT Professional Certificate Program in Product Management | Build an Action Plan | Group 3
Michaeline Albright, Pramoth Priyadharshan Chandrasekar, Martha Daniela Alvia Martinez, Marek Nerko, and Neelesh Pathak
Decision 1
Strategic Intent for Platform
Decision: New Markets & Revenue Growth
Strategic Rationale
Enter three buying centers (CIO, COO, CFO) via one shared platform—not three products.
80% R&D in Year 1 builds the "Heavy Platform." Marginal cost to enter next market drops ~60%.
"Build the Hub once, stack revenue with every Spoke."
CIO / CTO
Reduce Silent Drift incidents via Vector AI Core
COO / Supply
Decrease Kinetic Friction via Universal Precision Clock
CFO / Audit
Reduce Integrity Drift via Cryptographic Ledger
Business Model: Hub + Spokes
Platform Core (Hub)
Enterprise ARR subscription—billed once regardless of variants
Risk Variants (Spokes)
Usage-based tiered pricing per volume and complexity
Implementation
Non-recurring services via 50+ standard connectors
Decision 2
Market Segment Grid
Decision: Tiered Operational Risk Domains — regulatory complexity drives phased rollout from low to high regulation.
This grid illustrates the strategic positioning of each domain based on regulatory complexity and price point.
Domain A: IT & Digital Ops
Year 1 — Silent Drift
Owner: CIO/CTO. High-volume structured logs train the Vector Core. Low regulatory overhead enables rapid iteration.
Domain B: Supply Chain
Year 2 — Kinetic Friction
Owner: COO. Bridges digital signals to physical world via IoT/GPS. Medium regulatory posture.
Domain C: Financial Integrity
Year 3 — Integrity Drift
Owner: CFO/Audit. High barrier creates defensive moat. SOX and AML compliance via Cryptographic Ledger.
Decision 3
Commonality Impact on Operators
Decision: Divergent Visibility — Internal Efficiency vs. External Experience
color
This Market Segment Grid visually depicts the strategic positioning of each operational domain based on its regulatory complexity and associated price point, aligning with a dark futuristic theme with blue accents.
Internal (Invisible to Customer)
Unified Vector Core codebase. Algorithm optimized for one domain strengthens all others. Learn once, scale everywhere.
External (Visible to Customer)
UPC and Verified Signatures deliver unified outputs. Flexible Edge lets domain experts configure risk thresholds via Symbolic Logic Gate.
"One Engine. Domain-Specific Control. Zero Surprises."
Feature Commonality Matrix
🟢 = Shared Core, 🟨 = Custom Edge, ⚪/🟡 = Phased Scale
Decision 4
Customization & Differentiation
Decision: Bounded Customization — Immutable Core, Flexible Edge
Core AI is standardized across all domains for consistent prediction and capital efficiency. Customers cannot alter core algorithms. Customization lives at the edges.
The level of differentiation and customization that customers expect falls strictly within the following boundaries:
Core Predictive Engine (Unified - Zero Customization)
Standardized Architecture
Vector Core with Multi-Domain Tensor Synthesis is strictly locked. No custom builds or model fine-tuning allowed.
Universal Pattern Recognition
Identically predicts risk patterns (Silent Drift, Kinetic Friction, Integrity Drift) across all domains via the shared Universal Precision Clock.
Domain-Specific Customization (The Flexible Edge)
Customers have total control over the surrounding architecture:
Ingestion Edge
Configure Universal Forensic Pipeline to connect ERP (SAP), monitoring tools (Splunk), or IoT sensors.
Contextualization
Adjust platform focus to specific risk indicators (latency, wear, transaction anomalies).
Output Edge
Set risk tolerance levels and alert thresholds via Symbolic Logic Gate.
Decision 5
Cost Structure
Decision: High Upfront Platform CapEx / Compounding Operating Leverage
"Build the Hub once, stack revenue with every Spoke." Heavy Year 1 investment transitions to 80%+ gross margins by Year 3 as the marginal cost of new domains approaches zero.
Year 1: Build
80%+ budget to R&D. Build Immutable Core, UPC, initial training. High CAC educating the market.
Year 2: Scale
R&D shifts to connectors. "Land & Expand" lowers CAC. Training costs drop; implementation standardized.
Year 3: Leverage
Core fully mature. Cross-sell Finance at high premium. 80%+ gross margins. Operating leverage maximized.
Three Financial Moats
1
Zero Bespoke Engineering
Immutable Core eliminates NRE costs. COGS limited to cloud compute. 80%+ software margins.
2
Deflationary CAC
Shared UPC means IT risk events prove value to Supply Chain and Finance teams automatically.
3
Usage-Based Passthrough
Tiered pricing scales revenue in lockstep with client data volume growth.
Decision 6
Market Variant Plan & Volumes
Decision: Phased "Spoke" Expansion with Value-Inverted Scaling — volume decreases while contract value increases across years.
Year 1: Digital Resilience (A)
Buyer: CIO / CTO
Data Volume: Massive
Customer Volume: High (Beachhead)
ACV: Standard SaaS Baseline
Year 2: Kinetic Optimization (B)
Buyer: COO / Supply
Data Volume: Moderate
Customer Volume: Moderate (Expand)
ACV: High Cross-Sell Premium
Year 3: Capital Integrity (C)
Buyer: CFO / Audit
Data Volume: Low / Curated
Customer Volume: Low (Fortune 500)
ACV: Maximum 7-Figure Premium
Operationalizing Volume Strategy
Year 1 pushes massive IT data through Multi-Domain Tensor Synthesis to mature pattern recognition.
Years 2–3 shift focus from high-volume noise to low-volume, high-impact Verified Signatures. A single Integrity Drift signature may process megabytes but prevent multi-million-dollar fines.
"Trade raw data volume for exponential commercial value up the C-suite."
Decision 7
Planning Horizon & Architecture Stability
Decision: Long-Term Core Stability with Dual-Speed Evolution — 36-to-60-month planning horizon for foundational architecture.
The "Latent" Moat
Cryptographic Ledger built in Year 1 though not primary selling point. By Year 3 it has multi-year verified stability trusted by CFOs.
Slow, Stable Core
Vector Core, Symbolic Logic Gate, and UPC under heavy governance. AI improves via continuous data learning—not codebase rewrites.
Fast, Agile Edge
Forensic Pipeline connectors on rapid async sprints. Update a ServiceNow connector in hours without touching the AI Core.
"Mathematical consistency for the auditor. API speed for the engineer."
Decision 8
Define Sharing Strategy
Decision: Federated Intelligence with Strict Data Isolation — the "Zero-Exfiltration" Model
The Vector Core must learn globally while respecting SOX and AML compliance. Raw data pooling is a non-starter. Solution: share anonymized math, never raw data.
Data Sharing
Strict isolation. Raw data never leaves the customer's VPC or on-prem environment. Zero co-mingling.
Model Sharing
Federated global intelligence. Only anonymized "AI Fingerprint" weights shared. Network effect protects all customers.
Cross-Domain Sharing
Internal to customer. UPC translates Verified Signatures across departments on a single timeline.
"Global AI network power, secured by zero-exfiltration data sovereignty."