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Multi-Model AI
Architecture

445 specialized AI models across 16 Platforms coordinated through our proprietary Intelligence Bus to deliver superior business intelligence

445 Total AI Models Across 16 Platforms

Each platform has its own specialized AI models tailored to specific business domains, all coordinated through the Intelligence Bus

20

Commerce Models

BrainPredict Commerce

  • • Demand Forecasting AI
  • • Dynamic Pricing Optimizer
  • • Inventory Management AI
  • • Customer Segmentation
  • • Product Recommendation Engine
  • • Fraud Detection AI
  • • + 14 more specialized models
22

Supply Models

BrainPredict Supply

  • • Supply Chain Optimizer
  • • Demand Planning AI
  • • Supplier Risk Assessment
  • • Logistics Optimization
  • • Quality Prediction AI
  • • Procurement Intelligence
  • • + 16 more specialized models
27

People Models

BrainPredict People (CubAI)

  • • Talent Acquisition AI
  • • Performance Prediction
  • • Attrition Risk Analysis
  • • Skills Gap Analyzer
  • • Compensation Optimizer
  • • Employee Engagement AI
  • • + 21 more specialized models
26

Sales Models

BrainPredict Sales

  • • Lead Scoring AI
  • • Deal Probability Predictor
  • • Sales Forecasting
  • • Territory Optimization
  • • Next Best Action AI
  • • Competitive Intelligence
  • • + 20 more specialized models
26

Marketing Models

BrainPredict Marketing

  • • Campaign Performance Predictor
  • • Customer Acquisition Optimizer
  • • Content Performance AI
  • • Attribution Model AI
  • • Churn Prevention AI
  • • Personalization Engine
  • • + 20 more specialized models
31

Legal Models

BrainPredict Legal

  • • Contract Analysis AI
  • • Compliance Monitor
  • • Litigation Risk Predictor
  • • Regulatory Intelligence
  • • IP Protection AI
  • • Legal Research Assistant
  • • + 25 more specialized models
25

Risk Models

BrainPredict Risk

  • • Cyber Risk Intelligence
  • • Financial Risk Predictor
  • • Operational Risk Analyzer
  • • Compliance Risk Monitor
  • • Strategic Risk Advisor
  • • ESG Risk Analyzer
  • • + 19 more specialized models
35

Finance Models

BrainPredict Finance

  • • GL Automation AI
  • • Cash Flow Forecaster
  • • AP/AR Intelligence
  • • Budget Optimizer
  • • Revenue Recognition AI
  • • Financial Close Accelerator
  • • + 29 more specialized models
28

Innovation Models

BrainPredict Innovation

  • • Idea Scoring AI
  • • Patent Analysis
  • • Market Opportunity Finder
  • • R&D Portfolio Optimizer
  • • Innovation Trend Predictor
  • • Technology Readiness Assessor
  • • + 22 more specialized models
32

Controlling Models

BrainPredict Controlling

  • • KPI Monitor AI
  • • Variance Analysis
  • • Cost Intelligence
  • • Performance Predictor
  • • Planning Optimizer
  • • Profitability Analyzer
  • • + 26 more specialized models
30

Communications Models

BrainPredict Communications

  • • Truth Verification AI
  • • Brand Monitor
  • • Message Optimizer
  • • Crisis Predictor
  • • Stakeholder Analyzer
  • • Reputation Intelligence
  • • + 24 more specialized models
29

Data Models

BrainPredict Data

  • • Data Quality Scorer
  • • PII Detector
  • • Data Anonymizer
  • • AI Readiness Assessor
  • • Duplicate Detector
  • • Data Profiler
  • • + 23 more specialized models
28

Strategy, Sourcing, Operations, Customer Models

BrainPredict Strategy, Sourcing, Operations, Customer

  • • Strategic Planning AI
  • • Competitive Intelligence
  • • Market Opportunity Analyzer
  • • Business Model Optimizer
  • • M&A Target Identifier
  • • Portfolio Strategy, Sourcing, Operations, Customer Advisor
  • • + 22 more specialized models
445

Total AI Models

Across All Platforms

Platforms16
Connectors321
Intelligence Bus Events570+
Intelligence Bus

How Platform Models Work Together

Each platform's AI models are specialized for their domain, but they share insights through the Intelligence Bus. For example, Commerce models can inform Marketing campaigns, Supply models can optimize Sales forecasts, Strategy, Sourcing, Operations, Customer models can guide long-term planning, and People models can enhance customer service quality.

Learn more about cross-platform intelligence

Intelligence Bus Architecture

The central coordination layer that orchestrates all 445 AI Models across 16 Platforms for optimal performance and cross-platform intelligence sharing

How It Works

1

Request Reception

Intelligence Bus receives incoming requests and analyzes requirements

2

Model Selection

Determines which AI models are needed and in what sequence

3

Orchestration

Coordinates model execution, manages data flow, and handles dependencies

4

Optimization

Monitors performance, balances workload, and optimizes resource allocation

5

Response Delivery

Aggregates results from all models and delivers unified response

Key Benefits

Intelligent Orchestration

Automatically coordinates multiple AI models for complex tasks

Performance Optimization

Real-time monitoring and optimization of model performance

Cross-Model Learning

Enables models to learn from each other and improve over time

Fault Tolerance

Automatic failover and recovery for uninterrupted service

Technical Specifications

99.99%
Uptime SLA
< 10ms
Orchestration Latency
100K+
Requests/Second
Auto
Scaling

Phase 4.5: Predictive Intelligence Engine

9-model ensemble AI that predicts business events before they happen with 94-97% accuracy

150

Prediction Types

Across All 16 Platforms

  • • Demand spikes & inventory shortages
  • • Employee turnover & burnout
  • • Deal closures & pipeline risks
  • • Campaign failures & budget overruns
  • • Compliance violations & litigation
  • • Fraud patterns & security breaches
  • • + 144 more prediction types
9

AI Models

Ensemble Architecture

  • • LSTM (20% weight)
  • • ARIMA (10% weight)
  • • Prophet (10% weight)
  • • NeuralProphet (14% weight)
  • • NeuralProphet AR (12% weight)
  • • XGBoost (14% weight)
  • • Random Forest (10% weight)
  • • Extra Trees (8% weight)
  • • Gradient Boosting (2% weight)
6

Time Horizons

Multi-Step Predictions

  • • 1 Day (immediate actions)
  • • 7 Days (weekly planning)
  • • 30 Days (monthly planning)
  • • 90 Days (quarterly planning)
  • • 180 Days (semi-annual planning)
  • • 365 Days (annual planning)

Advanced Features

Truth Verification

Random Forest classifier validates predictions

Prediction Intervals

95% confidence bands for uncertainty quantification

Multi-Step Ahead

Predictions for 6 different time horizons

94-97% Accuracy

Ensemble voting for superior predictions

Integrations

Intelligence Bus

All predictions published as Level 3 events

AI Calendar

Automatic scheduling of preventive actions

AI Orchestrator

BERT-powered intelligent coordination

Cross-Platform

Subscription-based filtering for all platforms

Phase 4.5 v5.0.0 represents a 200% increase in prediction capabilities with 150 prediction types (up from 34 in v1.0.0)

Enterprise-Grade System Architecture

Built for security, scalability, and compliance from the ground up

Two-Backend Deployment Architecture

Production Server

Hetzner Cloud (Germany)

Website Backend

Payments, subscriptions, 3 AI models

License API

License validation with mTLS

Frontend

Next.js website UI

Customer Premises

On-Premises Installation

Platform Backend

16 platforms, 20-445 AI models

Intelligence Bus

570 cross-platform events

Customer Data

Never leaves premises

Data Sovereignty: Customer data stays on-premises. Only encrypted model updates sent to cloud for federated learning.

Security Features

  • End-to-end encryption (AES-256)
  • Multi-factor authentication (MFA)
  • Role-based access control (RBAC)
  • API key management and rotation
  • Audit logging and monitoring
  • DDoS protection and rate limiting
  • Regular security audits and penetration testing
  • Data anonymization and pseudonymization

Scalability

  • Horizontal auto-scaling based on demand
  • Load balancing across multiple regions
  • CDN integration for global performance
  • Database sharding and replication
  • Caching layers (Redis, CDN)
  • Microservices architecture
  • Containerized deployment (Kubernetes)
  • Support for millions of concurrent users
R&DPrioritizer AI (92.3% accuracy)

Technology Investment Roadmap

Our AI-driven R&D prioritization focuses on maximizing customer value and competitive differentiation

Model Accuracy

High
Current94-97%
Target96-98%
TimelineOngoing

Training Speed

Medium
CurrentHours
TargetMinutes
TimelineQ2 2026

Explainability

High
CurrentBasic
TargetAdvanced (SHAP, LIME)
TimelineQ2 2026

Multi-language NLP

Medium
Current5 languages
Target20 languages
TimelineQ3 2026

Computer Vision

Low
CurrentLimited
TargetFull suite
TimelineQ4 2026

Reinforcement Learning

Low
CurrentNone
TargetBasic
Timeline2027

Compliance Standards

Fully compliant with international data protection and AI regulations

GDPR
EU General Data Protection Regulation
Full compliance with data privacy and protection requirements
CCPA
California Consumer Privacy Act
Consumer data rights and privacy protection
SOC 2
Service Organization Control 2
Security, availability, and confidentiality controls
EU AI Act
European Union AI Regulation
Responsible AI development and deployment