Deploy intelligent visual systems powered by AI for object detection, activity monitoring, and quality inspection. Nexa’s Vision AI blueprint enables fast implementation across security, manufacturing, retail, and logistics
Scalable Edge-to-Cloud Inference
Built-In Compliance and Governance
Pre-Trained Models for Visual Intelligence
Coordinate multiple Vision AI agents to handle tasks like detection, classification, and monitoring in a unified flow
Allow agents to refine models with feedback, improving recognition accuracy and adaptability over time
Build trust with governance, audit trails, and policy-driven controls embedded into every Vision AI deployment
From manufacturing to healthcare, deploy scalable Vision AI agents that adapt quickly to sector-specific needs
Captures and processes inputs from diverse sources such as cameras, sensors, and image repositories. This layer supports streaming and batch data, enabling real-time detection, monitoring, and analysis across various environments — from industrial inspection to retail analytics
Transforms raw visual data into usable formats. It performs essential tasks such as normalization, denoising, image segmentation, and metadata tagging. This layer ensures consistency and quality for downstream model inference and analytics
Runs pre-trained or fine-tuned computer vision models for tasks like object detection, image classification, face recognition, anomaly detection, and scene understanding. It supports edge and cloud deployment, allowing for both low-latency and high-scale use cases
Connects visual insights to business logic. This layer enables automated decisions — such as triggering alerts, updating dashboards, or initiating workflows — based on visual outcomes. It integrates with APIs, rules engines, and agent systems for operational impact
Feeds annotated results, user feedback, and system logs back into training pipelines. This layer supports continuous model improvement, bias mitigation, and performance monitoring. It leverages visual embeddings and feedback to enhance future recognition tasks
The orchestration layer coordinates intelligent visual workflows by assigning tasks to the right AI agents—whether for anomaly detection, event triggers, or real-time video summarization—ensuring timely and relevant system responses
Processes incoming visual data with contextual filters and routes it to the appropriate Vision AI pipeline. It supports adaptive filtering based on patterns, location, and behavior—enabling personalized and situationally aware outputs
Continuously tracks performance metrics of deployed Vision AI agents at the edge. This enables predictive maintenance, efficiency scoring, and automated improvement cycles—especially in real-time, mission-critical settings.
Constantly monitors edge-deployed Vision AI agents to assess performance. Supports predictive upkeep, operational scoring, and self-optimizing loops for high-stakes, real-time environments
Connects visual data streams with structured knowledge—like digital twins, manuals, or support content—to enrich insights. Agents can reference visual cues and retrieve real-time guidance, aiding decision-making and automation
Enables secure communication between Vision AI modules and enterprise systems. It manages token-based access, rate-limiting, and encrypted data exchange to ensure governance, compliance, and resource control
Access visual insights securely from any device—desktop, mobile, or tablet
Design adaptive templates for various computer vision tasks—from object detection to compliance monitoring
Your visual data is protected with end-to-end encryption and stored on secure, compliant cloud infrastructure
Train custom AI models using your proprietary datasets within a secured environment