Overview
AI Orchestration for Data Flywheel
Streamline your data lifecycle from ingestion to insight with intelligent AI orchestration. Nexa's data flywheel blueprint automates workflows, boosts agility, and drives continuous value from data at every stage
Automate Data-to-Decision Workflows
Real-Time Analytics with Scalable Infrastructure
Continuously Learn and Optimize with Feedback Loops
What help you get to reinvent
Streamline how data is collected, processed, and applied. Enable AI-driven orchestration to unlock value at every stage of the data lifecycle
Deploy edge-ready AI systems that continuously learn and adapt, driving faster decisions closer to the data source
Leverage pre-built connectors and modular workflows to fit your business use cases without disrupting existing systems
Combine visual intelligence with orchestrated data to build self-operating agents that make context-rich decisions on the fly
Architecture Overview
User Access for Flywheel Control
Provides a secure, intuitive interface for users to launch, manage, and monitor data flywheel operations. Built with modern frontends and SSO integration for seamless access
Workflow Automation Engine
Automates data processing workflows, ensuring smooth data flow and execution of AI tasks. Maintains momentum with event-driven logic and business rule enforcement
Agent-Based Orchestration
Coordinates autonomous agents to handle data transformation, labeling, and feedback capture. Drives self-improving AI loops through intelligent agent collaboration
AI Model Loop Management
Continuously trains and refines models using real-time data signals. Ensures models evolve automatically with changing inputs and performance feedback
Data & Knowledge Hub
Aggregates all data into a unified, context-rich layer. Enhances AI outputs using metadata, knowledge graphs, and feedback-driven refinement
Core Components
Orchestrator
Intelligent Data Orchestration Hub
Coordinates the entire data flywheel lifecycle—from ingestion to enrichment—by intelligently routing data and triggers across models, tools, and agents. It ensures seamless data flow and optimizes every stage of the AI pipeline
Prompt Router
Dynamic Query Routing for Contextual Relevance
Continuously refines prompt pathways and inference triggers based on evolving data contexts. Enables smarter routing of tasks to the right models or workflows, increasing precision in downstream insights
Monitoring
Real-time Visibility and Optimization Loops
Continuously tracks data throughput and AI performance, enabling proactive issue detection and intelligent feedback loops. Maintains data freshness and model reliability across the flywheel.
Dynamically allocates compute, storage, and bandwidth based on workload demands. Optimizes system efficiency while maintaining peak AI performance under varying operational conditions
Knowledge
Semantic Layer for Learning and Discovery
Maps live data into an evolving knowledge graph, linking structured and unstructured sources. Helps AI systems learn iteratively, recommend actions, and fuel ongoing refinement in the data flywheel
API Development
Unified Interface for Data Flow and Governance
Offers a secure, centralized API layer to manage data sources, transformations, and AI actions. Simplifies integration and enforces policy compliance across the orchestration stack
Featured Blogs
Compliance and Privacy - AI Orchestration for Data Flywheel
Secure Data Flow
Data Integrity with Agents
All data pipelines are encrypted and monitored to ensure integrity
Regulatory Compliance
Ensure Compliance with AI Agent
Orchestration aligns with GDPR, HIPAA, and global data protection standards
Controlled Access
Authorized Access with AI Agent
Role-based permissions manage who can view, process, or orchestrate data
Privacy-First Automation
Protect Data with Agents
AI workflows minimize exposure of sensitive information during collection and use