LuminaIQ is a next-generation "Intelligence Engine" designed to bridge the gap between complex raw data and autonomous action. Unlike traditional ERPs, LuminaIQ uses a proprietary Neural Hub to ingest document, voice, and text data, applying specialized AI models (OCR, NLP, and Predictive Analytics) to automate decision-heavy workflows like candidate screening, invoice processing, and lead nurturing.
Key Functional Modules
- Neural Hub (AI Virtual Assistant): A real-time conversational interface for querying internal data and managing AI-driven tasks.
- Automation Canvas (Workflow Designer): A drag-and-drop environment to build multi-step automation chains (e.g., Scan Invoice → Verify Data → Trigger Payment).
- Document Intelligence (OCR & Extraction): Advanced vision-based engines for high-accuracy data extraction from unstructured documents.
- Predictive Logic (Analytics Dashboard): A forecasting suite that detects anomalies, predicts trends, and flags potential biases in AI decision-making.
Technical Specifications
- Front-End: HReact.js (Utilizing a modern, dark-themed Tailwind CSS framework for high-performance data visualization).
- Back-End: Python (FastAPI) (Optimized for low-latency AI model inference and asynchronous workflow handling).
- AI Stack: Integrated with LLMs (GPT-4o, Llama 3) and Computer Vision libraries for document processing.
Project Objectives
- Autonomous Efficiency: Achieving a target of 75%+ autonomous action ratio, reducing the need for human-in-the-loop intervention.
- Intelligence Centralization: Unifying various AI models into a single "Knowledge Base" that grows smarter with every processed transaction.
- Precision Scaling: Enabling enterprises to scale operations (like hiring or billing) without increasing headcount by leveraging predictive resource allocation.
