Opinova
AI-Powered Decision Intelligence Platform
Turning collective opinions into intelligent decisions.
Developed by CarbonIt Labs
Created by Edwin Sam K Reju
Opinova is an AI-powered decision intelligence platform that transforms thousands of opinions, complaints, and suggestions into clear priorities and actionable insights.
Organizations receive large amounts of feedback every day, but the real challenge is:
"What matters most, and what should be done first?"
Opinova helps institutions understand collective voices, identify critical concerns, and convert feedback into meaningful actions using local-first intelligence.
🌟 Vision
Opinova aims to build a smarter bridge between human voices and institutional decisions.
Every opinion contains a signal. Opinova helps discover:
- What people are saying (Feedback clustering & pattern recognition)
- Why it matters (Impact, criticality, and urgency evaluation)
- What actions should be considered (Actionable recommendations & explainable insights)
⚡ Key Capabilities
🧠 Intelligent Feedback Understanding
Analyzes textual feedback beyond simple keyword counting by identifying deep semantic patterns, concerns, and recurring themes.
🎯 Priority-Based Decision Support
Evaluates civic and organizational issues using a multi-factor priority engine:
- Criticality & Urgency
- Impact & Volume of People Affected
- Overall Importance Scoring
Helping organizations focus resources on what matters most.
🔍 Explainable Insights
Provides clear, human-understandable reasoning behind its automated analysis:
- Rationale for issue prioritization
- Key quotes and feedback indices
- Specific, recommended next steps
📊 Decision Intelligence Dashboard
An intuitive, responsive interface providing:
- Real-time issue distribution & category charts
- Action Item management (Pending/Solved status tracking)
- Flexible CSV / PDF report export capabilities
- Activity logs and offline database management
🏫 Use Cases
Organizations & Municipalities
- Employee and citizen feedback intelligence
- Public service complaint resolution (Water, Drainage, Transport, Lighting)
- Supporting data-driven administrative decisions
Educational Institutions
- Student feedback analysis
- Campus infrastructure improvement
- Identifying urgent academic & facility concerns
Communities
- Understanding public opinion across geographical/ward divisions
- Structuring raw feedback into actionable civic projects
🛠️ Technical Architecture & Requirements
Opinova is designed as a local-first desktop application prioritizing data privacy and fast offline capabilities.
Dependencies & Requirements
All project requirements are specified in requirements.txt:
pywebview: Native desktop UI containerpandas: High-performance data manipulation & CSV handlinggoogle-genai: Google Generative AI integration for intelligent summariespython-dotenv: Environment variable managementpydantic: Data validation & schema enforcementscikit-learn: Machine learning utilities & vector embeddingsnltk/spacy: Natural Language Processing pipelinesrapidfuzz: Fast fuzzy text deduplication & string matchinglangdetect: Automatic language identificationreportlab: PDF report generation engine
To install all requirements:
pip install -r requirements.txt
Complete Repository Structure
OPINOVA/
├── backend/
│ ├── main.py # API controller, PyWebView window initialization & event routing
│ ├── database.py # SQLite schema, query helpers, and feedback cache management
│ ├── ai_engine.py # LLM generation and decision intelligence pipeline
│ ├── preprocessing.py # Text cleaning, normalization, and token filtering
│ ├── clustering.py # Feedback grouping and semantic cluster creation
│ ├── scoring.py # Priority scoring based on urgency, impact, and criticality
│ ├── deduplication.py # Rapid fuzzy text matching and duplicate removal
│ ├── reports.py # Automated PDF and CSV report builder
│ ├── batching.py # Efficient batch processing for large feedback datasets
│ ├── data_loader.py # CSV parsing and data ingestion module
│ └── config.py # Backend configuration constants and settings
├── frontend/
│ ├── index.html # Main interactive dashboard view
│ ├── signinlogin.html # Login interface
│ ├── privacy.html # Privacy Policy disclosure
│ └── terms.html # Acceptable Use Policy disclosure
├── data/ # Auto-created directory for SQLite database & uploaded datasets
├── .env # Configuration
├── startapp.py # Main application launcher
├── logo.png # Main branding logo
├── logo.ico # Converted Windows icon asset
├── LICENSE # Apache License 2.0 file
├── requirements.txt # Project dependencies
├── README.md # Technical overview & platform documentation
└── guide.md # User manual and deployment guide
🚀 Getting Started
Quick Start
- Clone or download the repository to your local machine.
- Install the required dependencies:
pip install -r requirements.txt
- Run the application launcher:
python startapp.py
Default Credentials
On initial startup, default administrator credentials are automatically initialized:
- User ID:
admin - Password:
admin123
(Credentials can be updated anytime inside the Dashboard's Settings panel.)
🔮 Future Roadmap
- Real-time feedback streaming & live intelligence
- Enterprise-grade cloud deployment option
- Multi-language advanced sentiment & dialect analysis
- Custom institutional integrations & API webhooks
- Predictive decision-support models
👨💻 Creator
Edwin Sam K Reju
Founder / Developer at CarbonIt Labs
📜 License
This project is licensed under the Apache License 2.0.
The Apache License 2.0 allows:
- Commercial use
- Modification
- Distribution
- Private use
while providing attribution requirements and contributor protections. See the LICENSE file for full terms.
© 2026 Edwin Sam K Reju — CarbonIt Labs
Millions of opinions.
One intelligent direction.
Metadata
Release files for opinova 0.1.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| opinova-0.1.0.tar.gz | 1.6 MB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| opinova-0.1.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 3.2 MB
Release files / opinova-0.1.0.tar.gz
| Download URL | opinova-0.1.0.tar.gz |
|---|---|
| Size | 1.6 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
588c1cdfef1b90a81e91153f91ec9ce6bb760170253cf9de074bd813147cd25e
|
|
BLAKE2b-256 checksum How to use checksums |
93482be4daf8b88fe274c9b745a05550c3858c762e95e83f471f61a30608cb3d
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.13.5
|
Release files / opinova-0.1.0-py3-none-any.whl
| Download URL | opinova-0.1.0-py3-none-any.whl |
|---|---|
| Size | 1.6 MB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
d7db1e8d0acd11c26052fc9a1696a31453cd7297724bf104c1dbaf8b1e3e24d4
|
|
BLAKE2b-256 checksum How to use checksums |
7221de789da261be83ba9b1dd69d4d3dba8f2e009d4651e22c313f7addb8c32c
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.13.5
|
Security for opinova 0.1.0
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.