ZEDEDA Edge Intelligence Platform
ZEDEDA extends its proven edge orchestration foundation to orchestrate the full edge AI stack, including autonomous agents, inference, and infrastructure, across distributed environments. Build, deploy and operate AI and edge workloads on heterogeneous hardware with centralized control, hardware-rooted security, and workflows designed for real-world edge conditions.
Edge intelligence is fundamentally different from cloud AI. Not only do cloud and AI model platforms stop short of the edge and other existing edge platforms, they are also not purpose built for edge intelligence. Teams must manage constrained devices, inconsistent connectivity, physical risk, and diverse hardware architectures, often without on-site IT, while still meeting requirements for traceability, approvals, version control, and operational visibility.
ZEDEDA removes the friction that causes edge intelligence projects to stall by unifying edge orchestration with the end-to-end edge MLOps pipeline in one platform.
Whether you’re deploying models to remote sites, modernizing legacy environments, or running Kubernetes applications at the edge, ZEDEDA helps you:
Run mixed workloads together (containers, VMs, applications, models, and agents) to reduce footprint and simplify operations
ZEDEDA is built on three tightly integrated pillars:
ZEDEDA’s Edge Intelligence Platform is the only Edge AI solution that combines an AI-driven approach to build and orchestrate agents, models, applications and infrastructure.
The open-source edge operating system foundation for running virtual machines and containers on edge devices, deployable on any edge hardware (x86, Arm, GPU, RISC-V), including support for AI-optimized chipsets.
A broad ecosystem of hardware and technology partners, including AI model and agent providers, supporting diverse edge hardware profiles and deployments at scale.
ZEDEDA is architected for the operational realities of distributed edge environments where reliability, governance, and security are required even when conditions aren’t ideal.
Agentic AI Solution Templates: Declarative Helm charts that hyperconverge model, runtime, preprocessing, and business logic into validated solution blueprints.
End-to-End Model Lifecycle Management: Model versioning, import, and promotion with traceability across the lifecycle.
Inference Engine Packaging (Open and Repeatable): Package OpenVINO, NVIDIA Triton, vLLM, and Ollama as Helm charts.
Real Hardware Benchmarking and Validation: Benchmark on real edge hardware (NVIDIA/Intel) using inference speed, latency, and throughput; stress test on curated devices (e.g., Jetson, NUC).
Cloud-Managed Edge Node and Cluster Orchestration: GitOps governance for agents, models, and apps; node lifecycle management; zero-touch provisioning; reliable rollouts/rollbacks across fleets.
Virtualization and Container Services: Hypervisor and container runtime management across diverse hardware; run existing workloads alongside models and agents on the same device.
Dashboards, Observability, and APIs: Central UI visibility and reporting across inventory, deployments, users, and performance; REST APIs for integration.
Multi-tenant Organization Model: Isolate models, users, and permissions by org/team/environment with staging-to-production handoff.
Zero-Trust Security and Access Control: Root of trust via Trusted Platform Module (TPM); measured boot and attestation; encryption; firewall/port isolation; role-based access control (RBAC).
ZEDEDA delivers edge intelligence through services spanning agents, models, applications, and infrastructure.
Create, test, deploy, and operate autonomous edge agents with any AI model on any edge hardware. Includes pre-validated Agentic Solutions that bundle model artifacts, Helm charts, configuration values, deployment metadata, and hardware.
Orchestrate and manage the full AI stack across thousands of edge nodes with fleet-wide observability and manageability, enabling AI workloads to run alongside legacy applications on the same hardware to reduce CapEx.
Operating edge intelligence at scale requires cloud-grade lifecycle control, adapted for real-world constraints. ZEDEDA gives enterprises a platform to deploy, validate, govern, and operate edge intelligence across heterogeneous environments without sacrificing security, control, or speed.