VectraFlow: An AI-Augmented Data-Flow System
Date: at Brandeis University
Abstract
VectraFlow is a data-flow system designed to seamlessly integrate modern ML models with an extended relational framework. It provides advanced semantic operators for unstructured and multi-modal data processing, supporting both real-time streaming and batch processing through its unified execution engine.
Overview
Traditional database systems excel at structured data processing but struggle with unstructured data and AI operations. Meanwhile, AI systems often lack the robust data management capabilities of databases. VectraFlow addresses this divide by extending the relational model with advanced semantic operations powered by vectors, LLM prompts, and ML models.
Key Features
- Unified Execution Model: Supports both real-time streaming and batch processing
- Advanced Semantic Operations: Seamlessly integrates ML models with data processing
- Reliability & Security: Built-in guardrails and access control mechanisms
- Multi-modal Support: Handles diverse data types and AI-driven applications
Demo
Join us for a live demo and detailed discussion of the system architecture and its applications. 
VectraFlow’s intuitive pipeline interface for processing medical records