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
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
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
Automates data processing workflows, ensuring smooth data flow and execution of AI tasks. Maintains momentum with event-driven logic and business rule enforcement
Coordinates autonomous agents to handle data transformation, labeling, and feedback capture. Drives self-improving AI loops through intelligent agent collaboration
Continuously trains and refines models using real-time data signals. Ensures models evolve automatically with changing inputs and performance feedback
Aggregates all data into a unified, context-rich layer. Enhances AI outputs using metadata, knowledge graphs, and feedback-driven refinement
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
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
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
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
Offers a secure, centralized API layer to manage data sources, transformations, and AI actions. Simplifies integration and enforces policy compliance across the orchestration stack
Orchestrate data pipelines across cloud, on-prem, and hybrid environments. Ensure seamless operations and synchronized model workflows, regardless of where your data lives
Dynamically route queries and data triggers to the most appropriate model or agent. Leverage user context, intent, and historical interactions for smarter decisions
Manage the full lifecycle of models—training, deployment, feedback, and retraining—within a self-sustaining orchestration loop to accelerate continuous improvement
Enable secure execution of multi-agent tasks while maintaining governance and isolation. Ensure policies are enforced at every stage of the data flywheel
Gain full visibility into orchestration processes with real-time dashboards. Monitor, troubleshoot, and optimize your AI workflows with ease and confidence
Enforce data handling policies across all orchestration layers. Automatically classify, audit, and restrict data usage based on compliance requirements and organizational standards—ensuring trust and accountability at scale