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SentraCore is a local system behavior intelligence platform for Windows that continuously analyzes system telemetry to understand performance behavior, detect anomalies, explain system slowdowns, and estimate future resource pressure before it impacts usability.
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### System Behavior Intelligence Platform
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Unlike traditional monitoring tools that focus on raw snapshots, SentraCore interprets system behavior over time — helping users understand what is happening, why it is happening, and how it may affect overall system responsiveness.
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SentraCore is a local **system behavior intelligence platform** designed to continuously analyze telemetry, understand performance behavior, detect anomalies, explain slowdowns, and estimate future system pressure before it impacts responsiveness.
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Rather than focusing on isolated resource snapshots, SentraCore interprets system activity over time to answer three critical questions:
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**What is happening?**
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**Why is it happening?**
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**What is likely to happen next?**
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Built for intelligent desktop observability and explainable operational insight.
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</div>
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---
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## Current Status
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## Overview
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SentraCore combines telemetry collection, behavioral modeling, anomaly detection, predictive analytics, and explainable diagnostics into a unified local intelligence system.
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The platform continuously learns machine-specific operating patterns and transforms raw system measurements into actionable insights.
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---
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## Current Capabilities
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SentraCore currently includes:
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- Real-time telemetry monitoring
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-Behavioral baseline learning
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-Adaptive behavioral baseline learning
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- Statistical anomaly detection
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- Root cause analysis
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- Predictive risk estimation
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- Historical monitoring (Logbook)
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- Historical monitoring and logbook tracking
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- Flutter desktop dashboard
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-Windows installer and packaging system
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-Desktop packaging and installer workflow
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---
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## Core Features
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### System Stability Index
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Unified system health scoring based on:
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- resource pressure
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- anomaly deviation
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- sustained stress trends
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- predictive degradation risk
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Unified system health scoring generated from:
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- Resource pressure
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- Behavioral deviation
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- Sustained stress trends
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- Predictive degradation indicators
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---
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### Behavioral Intelligence
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Learns normal system behavior per machine, including:
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- CPU usage patterns
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- memory behavior
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- disk activity trends
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- time-of-day workload patterns
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Learns normal operating behavior per machine, including:
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- CPU utilization patterns
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- Memory behavior
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- Disk activity trends
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- Time-based workload characteristics
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The objective is to detect meaningful deviation rather than isolated spikes.
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### Root Cause Analysis
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Analyzes:
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- process activity
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- resource contention
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- event timing
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- system degradation patterns
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Provides ranked likely contributors instead of raw metrics alone.
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Correlates multiple signals to identify likely contributors to degradation.
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Analysis includes:
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- Process activity
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- Resource contention
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- Event timing
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- Performance degradation patterns
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Outputs ranked probable causes instead of raw metric streams.
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### Predictive Forecasting
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Estimates future resource exhaustion using trend analysis:
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- memory saturation forecasting
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Forecasts future pressure using historical and trend-based analysis.
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Includes:
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- Memory saturation estimation
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- CPU trend projection
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-disk pressure estimation
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-ETA-style degradation warnings
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-Disk pressure forecasting
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-Estimated degradation warnings
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### Historical Monitoring
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Automatically records and visualizes:
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Continuously records and visualizes:
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- CPU pressure
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- memory pressure
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- disk pressure
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- long-term behavior trends
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- Memory pressure
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- Disk pressure
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- Long-term behavioral trends
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- Historical intelligence events
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---
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### Alerts & Diagnostics
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Includes:
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- live alerts
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- alert history
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- diagnostics timeline
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- Live alerts
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- Alert history
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- Diagnostics timeline
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- Windows notifications
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-root cause summaries
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-Root cause summaries
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## Architecture
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```text
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Flutter Dashboard
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↕ WebSocket / REST API
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↕
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WebSocket / REST API
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↕
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Python Intelligence Engine
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├── Telemetry Collection
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├── Baseline Learning
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├── Anomaly Detection
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├── Correlation Engine
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├── Prediction Engine
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└── Alert System
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│
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├── Telemetry Collection
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├── Baseline Learning
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├── Anomaly Detection
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├── Correlation Engine
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├── Prediction Engine
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└── Alert System
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```
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@@ -102,78 +142,121 @@ Python Intelligence Engine
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| Layer | Technology |
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|---|---|
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| Engine | Python 3.11, psutil |
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| API | FastAPI, WebSockets |
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| Engine | Python 3.11 · psutil |
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| API | FastAPI · WebSockets |
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| Dashboard | Flutter Desktop |
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| Packaging | PyInstaller, Inno Setup |
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|CI/CD| GitHub Actions |
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| Packaging | PyInstaller · Inno Setup |
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|Automation| GitHub Actions |
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## Getting Started
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### Development
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### Development Environment
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See the setup documentation below for full instructions.
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See project documentation for full setup instructions.
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Start the engine:
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```powershell
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# Start engine
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.venv\Scripts\python -m engine.main
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```
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# Run dashboard
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Launch dashboard:
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```powershell
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cd dashboard
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flutter run -d windows
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```
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###Installer
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## Installer
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Download the latest installer from the [GitHub Releases](https://github.com/AsieduDevelopmentHub/SentraCore/releases) page.
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Download the latest desktop release from:
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The installer:
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- installs SentraCore
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- creates shortcuts
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- configures optional startup launch
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- sets up the monitoring engine automatically
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```text
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GitHub Releases
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```
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Installer capabilities:
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- Installs SentraCore
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- Creates application shortcuts
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- Configures optional startup behavior
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- Deploys the monitoring engine
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- Prepares runtime dependencies
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---
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## Documentation
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| Document | Description |
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|---|---|
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|[Development Setup](docs/setup/development_setup.md)|Full local development setup |
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|[Engine Setup](docs/setup/engine_setup.md)| Engine configuration and setup|
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