⚡ SynapseIQ

Where Data Becomes Decisions

AI Operating System for Executive Decision Making

🏆 Built for Google GenAI Academy Hackathon 2026

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🎥 Watch Demo  ·  🚀 Live App  ·  📄 Presentation  ·  📚 Documentation

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Landing Portal — Drag-and-drop CSV intake with automatic business profiling

⚡ Intelligent Dataset Analysis	🧠 Google Gemini Powered	📊 8 AI-Driven Modules	📑 Automated Executive Reports	☁️ Cloud Run Ready
Profiles industry, KPIs, outliers	Live AI reasoning + offline fallback	End-to-end decision intelligence	Boardroom-ready in one click	Production Docker + Nginx

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📋 Table of Contents

• Overview
• Why SynapseIQ?
• Key Features
• Architecture
• Technology Stack
• Project Structure
• Screenshots
• Demo
• Getting Started
• Environment Variables
• Deployment
• Roadmap
• Team
• License

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🌐 Overview

SynapseIQ is an AI-powered Decision Intelligence Platform that transforms structured business datasets into executive-ready insights, strategic recommendations, interactive business relationship maps, forecasting simulations, and boardroom-ready reports — all powered by Google Gemini.

Unlike traditional BI dashboards that passively display charts, SynapseIQ acts as a living AI operating system that proactively surfaces strategic narratives, detects anomalies, simulates business scenarios, and guides executives toward high-confidence decisions.

"This isn't another analytics tool. This is an AI strategist embedded inside your business data."

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🆚 Why SynapseIQ?

Capability	Traditional Business Intelligence	⚡ SynapseIQ
Output	Static charts and dashboards	Executive decisions and strategic recommendations
Analysis	Shows what happened	Explains why it happened + what to do next
Reporting	Manual, hours-long process	Auto-generated boardroom reports in seconds
AI Integration	Generic chatbot widget	Context-aware strategist with full dataset awareness
Insights	Reactive — discovered after damage	Proactive — AI Initiative Cards surface issues first
Scenarios	Not possible	Live scenario simulation with real-time trade-off analysis
Relationships	Siloed metric views	Interactive correlation graph (Strategy Canvas)
Confidence	No quality signals	Dynamic AI confidence scoring per dataset
Data Limits	Silent failures	Honest AI declarations when data is insufficient
Deployment	Enterprise software license	Open-source, Docker-ready, Cloud Run in minutes

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✨ Key Features

📊 Executive Brief AI-narrated business health summary with today's strategic priorities, top opportunities, critical risks, and dynamic confidence scoring — built for immediate boardroom consumption.	🧠 Strategy Canvas Interactive React Flow relationship graph that maps mathematical correlations between Revenue, Profit, Marketing ROI, Inventory, and Customer Satisfaction. Hover any node for correlation strength and strategic insight.
📡 Business Signals Real-time anomaly telemetry matrix detecting meaningful business events — revenue-profit divergence, satisfaction drops, inventory pressure, and marketing ROI outliers — with McKinsey-style explanations.	🤖 AI Strategist (Decision Copilot) Gemini-powered split-pane consulting interface delivering structured executive responses: Summary → Evidence → Interpretation → Recommendation → Confidence → Follow-up.
📈 Forecast Studio Six-lever scenario simulator — Marketing, Pricing, Inventory, Hiring, Retention, Costs — with real-time AI trade-off analysis and projected revenue, margin, and risk scoring.	📅 Business Timeline Chronological narrative ledger translating raw dataset records into a human-readable business story with category filtering and trend visualization.
📑 Boardroom Report Seven-section auto-generated executive report: Executive Summary · Business Health · Key Opportunities · Critical Risks · Forecast · Strategic Recommendations · 90-Day Action Plan.	📂 Intelligent Dataset Upload Upload any CSV business dataset. SynapseIQ auto-profiles the data: detects industry type, infers key business metrics, identifies missing values and Z-score outliers, and adapts all modules to your context.

Additional Capabilities:

• 🎬 AI Narrative Engine — Full-screen animated narrative post-analysis guiding executives through key findings
• ✨ Presentation Mode — One-click projector-optimized interface with expanded spacing and focused layouts
• 🧭 Guided Demo Tour — Automated 3-minute walkthrough built for hackathon judges — no setup required
• 🔒 Honest AI Declarations — Clear diagnostic banners when data is insufficient; no hallucinated answers
• 🌐 Intelligence Mesh — Ambient animated particle background responding to data state changes

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🏗 Architecture

System Architecture — End-to-End Data Flow

graph TD
    A["📂 Dataset Upload\nCSV Drag-and-Drop"] --> B["🔬 csvParser.ts\nData Processing Engine"]

    B --> C["📊 Statistical Analysis\nKPIs · Pearson Correlations\nZ-Score Outliers · Missing Values"]
    B --> D["🏭 Auto-Profiling\nIndustry · Metrics · Timeframe"]

    C --> E["🤖 geminiService.ts\nGoogle Gemini API"]
    D --> E

    E --> F["🧠 Decision Intelligence Engine\nlocalAnalysis.ts"]
    F --> G["💾 store.ts\nZustand Global State"]

    G --> H["📋 Executive Brief\nHealth · Priorities · Confidence"]
    G --> I["🕸 Strategy Canvas\nCorrelation Relationship Graph"]
    G --> J["🤖 AI Strategist\nContext Chat · Evidence · Actions"]
    G --> K["📈 Forecast Studio\nScenario Sliders · Trade-offs"]
    G --> L["📑 Boardroom Report\n7-Section Auto-Report"]
    G --> M["📡 Business Signals\nAnomaly Detection Cards"]
    G --> N["📅 Business Timeline\nChronological Narrative"]

    style A fill:#0D1117,stroke:#83D18B,stroke-width:2px,color:#fff
    style E fill:#0D1117,stroke:#4285F4,stroke-width:2px,color:#fff
    style G fill:#0D1117,stroke:#A855F7,stroke-width:2px,color:#fff

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The CSV parser computes Pearson correlations, Z-score outliers (±3σ), and missing value ratios. This statistical profile feeds Google Gemini to generate a context-rich analysis JSON, which hydrates the Zustand global store powering every module simultaneously.

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AI Processing Pipeline — Decision Copilot

sequenceDiagram
    participant E as Executive
    participant SC as Strategy Canvas
    participant S as Zustand Store
    participant G as Google Gemini
    participant L as Local Reasoning Engine

    E->>SC: Hover node (Revenue)
    SC->>E: Show correlated nodes + correlation strength
    E->>SC: Click node (Revenue)
    SC->>S: setActiveNodeId("revenue")
    S->>E: Refresh context panel with node data

    E->>G: "Why did revenue increase?"
    alt Gemini API configured
        G->>E: Summary · Evidence · Recommendation · Confidence
    else No API key / Offline
        L->>E: Dataset-grounded heuristic response
    end
    Note over E,L: Format: Summary → Evidence → Interpretation → Recommendation → Confidence → Follow-up

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Every AI response — whether from Gemini or the local fallback — follows the same structured executive format. The local reasoning engine uses computed KPI stats (mean, max, min, total) from the parsed dataset to provide data-grounded answers without an API key.

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Deployment Architecture — Vercel

graph LR
    Dev["💻 Local Development<br/>React + TypeScript + Vite"] -->|git push| GH["🐙 GitHub Repository<br/>pravalika2307/SynapseIQ"]

    GH -->|Automatic CI/CD| Vercel["▲ Vercel Platform<br/>Build & Deploy"]

    Vercel -->|Production Deployment| Web["🌐 SynapseIQ Web Application<br/>HTTPS · Global CDN"]

    Web -->|API Request| Gemini["🤖 Google Gemini API<br/>AI Decision Intelligence"]

    Gemini -->|AI Responses| Web

    Users["👨‍💼 Executives<br/>📊 Analysts<br/>📈 Managers"] -->|Access via Browser| Web

    style GH fill:#0D1117,stroke:#fff,stroke-width:1px,color:#fff
    style CR fill:#0D1117,stroke:#4285F4,stroke-width:2px,color:#fff

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The multi-stage Dockerfile compiles the React SPA in a Node.js builder container, then serves static assets via a minimal Nginx Alpine image on port 8080 — ideal for Google Cloud Run's serverless container model.

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🛠️ Technology Stack

Frontend

Technology	Version	Purpose
React	19.x	UI Component Framework
TypeScript	6.x Strict	Type Safety & Developer Experience
Vite	8.x	Build Tool & Dev Server
Tailwind CSS	v4	Utility-first Dark Theme Styling
Framer Motion	12.x	Animations & Page Transitions
React Router	v7	Client-side Hash Routing
Zustand	5.x	Global Application State

AI & Data Intelligence

Technology	Purpose
Google Gemini API	Executive briefs · Copilot chat · Scenario reasoning
Local Reasoning Engine	Offline heuristic analysis grounded in computed dataset statistics
Pearson Correlation Engine	Business metric relationship mapping for Strategy Canvas
Z-Score Outlier Detection	Statistical anomaly identification (±3σ threshold)
Dynamic Confidence Scoring	AI quality index based on dataset completeness and outlier density

Visualization

Technology	Version	Purpose
React Flow (xyflow)	12.x	Interactive Strategy Canvas node graph
Recharts	3.x	Business charts, scatter plots, line charts

Infrastructure

Technology	Purpose
Docker	Multi-stage production container (Node builder → Nginx Alpine)
Nginx	Static SPA serving with hash-router fallback rules
Google Cloud Run	Serverless HTTPS container deployment
Google Cloud Build	CI/CD from GitHub to Artifact Registry

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📁 Project Structure

SynapseIQ/
│
├── Dockerfile                  # Multi-stage production container
├── nginx.conf                  # SPA routing + static serving config
├── package.json                # NPM manifest (v1.0.0)
├── tsconfig.json               # TypeScript strict configuration
├── vite.config.ts              # Vite build configuration
├── CHANGELOG.md                # Version history
├── CONTRIBUTING.md             # Contribution guidelines
├── SECURITY.md                 # Security policy
│
├── docs/
│   └── screenshots/            # README screenshots (7 pages)
│
├── public/
│   └── favicon.svg             # Application icon
│
└── src/
    ├── App.tsx                 # Root HashRouter + route definitions
    ├── main.tsx                # React DOM entry point
    ├── index.css               # Global design tokens + Tailwind
    │
    ├── components/             # Shared UI components
    │   ├── ui/                 # Atomic design system (Button, Card, Badge…)
    │   ├── DecisionGraph.tsx   # React Flow interactive relationship graph
    │   ├── AIMissionControl.tsx    # Animated AI narrative overlay
    │   ├── DemoController.tsx  # Guided demo tour state machine
    │   ├── IntelligenceMesh.tsx    # Ambient animated particle background
    │   ├── LiveInsightStream.tsx   # Live activity ticker sidebar
    │   ├── PresentationToolbar.tsx # Presentation mode toggle
    │   ├── Sidebar.tsx         # Collapsible navigation panel
    │   ├── Topbar.tsx          # Top bar + AI status indicators
    │   └── UploadZone.tsx      # CSV drag-and-drop upload
    │
    ├── features/               # Business logic & AI services
    │   ├── csvParser.ts        # CSV ingestion · profiling · correlation engine
    │   ├── data.ts             # Node context and telemetry data maps
    │   ├── defaultDataset.ts   # Built-in demo dataset (NovaRetail Q2)
    │   ├── demoStore.ts        # Guided tour Zustand state machine
    │   ├── geminiService.ts    # Google Gemini API integration
    │   ├── localAnalysis.ts    # Offline heuristic analysis engine
    │   └── store.ts            # Global application state (Zustand)
    │
    ├── layouts/
    │   └── DashboardLayout.tsx # Sidebar + Topbar shell wrapper
    │
    └── pages/                  # Full-page view components
        ├── Landing.tsx         # Upload portal + AI intake sequence
        ├── ExecutiveBrief.tsx  # Executive summary + health + priorities
        ├── BusinessTimeline.tsx    # Chronological event narrative
        ├── BusinessSignals.tsx # Anomaly telemetry matrix
        ├── StrategyCanvas.tsx  # Strategy graph + scatter analysis
        ├── DecisionCopilot.tsx # AI strategist chat interface
        ├── Forecast.tsx        # Scenario simulator + projections
        ├── Reports.tsx         # Boardroom report generator
        └── DataExplorer.tsx    # Raw dataset exploration viewer

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📸 Screenshots

All screenshots below show SynapseIQ running live with the built-in NovaRetail Q2 demo dataset. No API key is required for the demo experience.

Landing Portal — Intelligent Dataset Intake

Drag-and-drop CSV upload · Auto-profiling · Industry detection · Validation feedback

Executive Brief — AI-Narrated Business Summary

Business Health Score 90/100 · Decision Readiness 87/100 · AI Confidence 95% · Strategic Priorities · Live Telemetry

Strategy Canvas — Interactive Business Relationship Graph

Pearson correlation mapping · Revenue $246.78M · Node relationship tooltips · Animated edges

AI Strategist — Context-Aware Decision Copilot

Gemini-powered executive chat · Dataset Profile panel · McKinsey response format · Confidence scoring

Forecast Studio — Live Scenario Simulator

Six business levers · Projected Revenue $49.6M · Gross Margin 45.7% · Real-time AI trade-off analysis

Business Timeline — Chronological Narrative Ledger

Event-driven business story · Category filter chips · Trend visualization · Seasonal dynamics

Boardroom Report — Auto-Generated Executive Report

7-section executive brief · Strategic Planning dossier · Investor-ready format

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🎬 Demo

Resource	Link
🎥 Demo Video	Coming Soon — Upload to YouTube
🚀 Live Deployment	Deploy to Vercel — see instructions below
📄 Presentation Deck	Google Slides presentation link

▶️ Guided Demo Experience — For Hackathon Judges

SynapseIQ includes a built-in Guided Demo Tour that requires zero configuration.

1. Open the application — the built-in NovaRetail Q2 dataset loads automatically
2. Click Start Guided Demo on the landing screen
3. The system auto-navigates through all 8 key features with spotlights and narration
4. Completes in under 3 minutes

No Gemini API key required. The guided demo uses an intelligent offline reasoning engine backed by pre-computed statistical analysis of the bundled dataset.

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🚀 Getting Started

Prerequisites

Requirement	Version
Node.js	≥ 20.x
npm	≥ 10.x
Gemini API Key	Optional

Installation

# 1. Clone the repository
git clone https://github.com/pravalika2307/SynapseIQ.git
cd SynapseIQ

# 2. Install dependencies
npm install

# 3. Start the development server
npm run dev

Open https://synapseiq-ai.vercel.app/ in your browser.

Other Commands

# Type-check + compile production bundle
npm run build

# Preview the production build locally
npm run preview

# Run ESLint code quality checks
npm run lint

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🔐 Environment Variables

SynapseIQ works fully offline with its built-in reasoning engine. A Gemini API key unlocks live AI capabilities.

Variable	Required	Description
GEMINI_API_KEY	Optional	Google Gemini API key for live executive briefs and copilot chat

How to configure: No .env file is required. Enter your Gemini API key directly in the app UI at the landing screen. The key is stored in browser session memory only and is never persisted or transmitted to any external server other than the Google Gemini API.

Privacy: All data processing happens client-side in your browser. No dataset or business data leaves your device unless you explicitly enable Gemini API integration.

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☁️ Deployment

SynapseIQ is deployed on Vercel with automatic CI/CD integration.

Production Deployment

# Install Vercel CLI
npm install -g vercel

# Login
vercel login

# Deploy
vercel --prod

Continuous Deployment

Every push to the main branch automatically:

• Builds the React + Vite application
• Optimizes production assets
• Deploys to Vercel's global CDN
• Generates a secure HTTPS production URL

Docker (Local)

docker build -t synapseiq:latest .
docker run -p 8080:8080 synapseiq:latest

Open http://localhost:8080

Static Hosting (Vercel / Netlify)

npm run build
# Deploy the dist/ directory — no server-side requirements

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🔮 Roadmap

Status	Version	Milestone
✅ Complete	v1.0.0	Hackathon Prototype — Full AI decision platform with Gemini
🔄 In Progress	v1.1	Real-time analytics via WebSocket streaming
📅 Planned	v1.2	Multi-user collaborative workspaces with role-based access
📅 Planned	v1.3	ERP connectors — SAP, Oracle NetSuite, Microsoft Dynamics
📅 Planned	v1.4	CRM connectors — Salesforce, HubSpot, Pipedrive
📅 Planned	v2.0	Explainable AI with full causal reasoning chains
📅 Planned	v2.1	Enterprise SSO — Google Workspace, Okta, Azure AD
📅 Planned	v2.2	One-click PowerPoint and PDF boardroom export
🌟 Vision	v3.0	Google Vertex AI integration with custom fine-tuned models

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👤 Team

Pravalika Palle

Lead Engineer · Product Designer · AI Architect

MCA Graduate · AI & Data Enthusiast · Builder of SynapseIQ

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📄 License

This project is licensed under the MIT License — see the LICENSE file for details.

Copyright © 2026 Pravalika Palle

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⚡ SynapseIQ

Where Data Becomes Decisions

AI Operating System for Executive Decision Making

Powered by Google Gemini · Built for Google GenAI Academy Hackathon 2026

If you found this project interesting, please consider giving it a ⭐ on GitHub.

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