🏷️ €29900 | Base Price
includes MX-DT License and 1-year Updates and Support
📰 What is MX-DT?
MX-DT delivers a scalable, 5G-compliant digital twin environment with UE-in-the-loop capabilities, mirroring real networks at scale and reproducing operational data with high fidelity. It supports parallel replicas, state synchronization, and AI-driven analytics for rigorous planning, experimentation, and optimization of network operations and decisions.
💡 Getting started is simple: choose or customize a network blueprint from our library, then deploy it at scale with a single command:
bash$ brc install digital-twin 5g-oran-ndt.yaml
Why MX-DT ?
- Spawn parallel replicas: Mirror RAN and Core components with high fidelity — in both emulated and over-the-air environments.
- Decouple from live changes: Run synchronized with production or freeze the network at any point in time.
- Safely: Evaluate hypotheses, actions, and outcomes before applying them in production.
- Scope: Clone specific regions, slices, or sites to optimize resources.
- O-RAN: Integrate seamlessly with MX-AI, MX-PDK, and SMO/RIC through open Telco APIs — with built-in multi-vendor support and no lock-in.
What’s Included
- MX-DT Core – The heart of the framework: a powerful orchestrator managing perceptors and replicators across RAN, vRAN, C-RAN, Core VNFs, and transport layers.
- Scenario Kit – Everything needed to model reality: replay live traffic, generate synthetic loads, inject faults, and simulate mobility or spectrum changes.
- SDK / CDK – Extend and customize MX-DT with your own mappers, traffic generators, and analytics pipelines.
- MX-HUB Access – Tap into a shared ecosystem of templates, dashboards, and digital twin models from the global MX community.
- Web GUI & CLI – Intuitive interfaces to build, run, compare, and visualize twins — with exportable insights and reporting.
- Virtual & Physical Twins – Deploy in the cloud via MX-ORS or connect directly to live network equipment for hybrid testing.
Tiered Packaging
| Tier | What’s Inside |
|---|---|
| Base | Core capabilities including (1) parallel & scoped twins, (2) live-sync or frozen states, (3) scenario replay, (4) and reporting dashboards. |
| Pro | Adds closed-loop automation and AI-driven optimization powered by O-RAN and MX-AI. |
| Custom | Fully tailored models, integrations, and workflows — built around your specific network architecture. |
Capabilities at a Glance
| Capability | Description |
|---|---|
| Parallel Replicas | Instantly spin up multiple twins for targeted cells, slices, or regions. |
| Live or Time-Locked | Operate in sync with production or rewind to analyze historical network states. |
| Scenario & Fault Kit | Recreate traffic conditions, test fault responses, and assess spectrum or mobility changes. |
| Apply-if-Better | Automatically benchmark outcomes and deploy only verified improvements. |
| Open APIs & MX-HUB | Built for openness — O-RAN–ready interfaces and community-driven model sharing. |
| Virtual + Physical Twins | Unify emulation and over-the-air testing in a single, scalable environment. |
Benefits at a Glance
| Benefit | Description |
|---|---|
| O-RAN–Friendly & Open | Seamless integration with R1/A1, SMO, and RIC; share and reuse assets via MX-HUB. |
| Risk-Free Deployment | Test and validate in the twin before applying changes to live networks. |
| Smarter Planning | Gain real-time insight into capacity, coverage, and energy efficiency. |
| Reduced Downtime | Predict and prevent issues before they impact service. |
| Faster Iterations | Experiment rapidly with parallel twins for quicker innovation cycles. |
| Flexible Deployment | Scale effortlessly from lab validation to field deployment. |
Practical Use Cases
From optimization to AI validation, MX-DT turns digital twin technology into measurable network impact:
| Use Case | Description |
|---|---|
| Clone & Tune Regions | Mirror network regions or slices to fine-tune spectrum, capacity, and virtualization strategies. |
| Replay & What-If Analysis | Recreate and manipulate past conditions to test “what-if” scenarios, identify root causes, and optimize outcomes. |
| Closed Loops & Simulation | Simulate configurations, validate RIC policies, and confirm improvements before live rollout. |
| Data Generation | Generate high-fidelity synthetic datasets to accelerate analysis and AI/ML training. |
| AI/ML Validation | Safely validate and refine algorithms within a controlled digital twin environment. |
What’s Included?
- MX-DT Core: Twin orchestrator with state perceptors and replicators for RAN, vRAN, C-RAN, Core VNFs and transport.
- Starter Twin Templates: gNodeB, L2/L3, AMF/SMF/UPF, transport layers, VNFs.
- Scenario Kit: traffic mirroring, synthetic generators, fault injection, mobility, spectrum toggles.
- SDK / CDK: build custom mappers, generators and analytics pipelines.
- MX-HUB Access: templates, scenarios, dashboards; share models with the community.
- Web GUI & CLI: create, run, compare and export reports; 3D visualisations.
- Virtual & Physical Twins: deploy via MX-ORS or connect to physical equipment.
Need more information ?
Check our frequently asked questions about MX-DT here below and get quick replies.
To answer your unique deployment and projects needs, we can plan a live demo, help you forward with a requirements questionnaire, and connect you with our partner ecosystem.
Frequently Asked Questions
1️⃣ Can MX-DT run fully on-prem? Yes. You can deploy twins entirely on your own servers or edge nodes. MX-DT also supports large-scale cloud deployments (e.g., GKE) using Terraform automation.
2️⃣ Does MX-DT integrate with our SMO/RIC? Absolutely. MX-DT is O-RAN–aligned (R1/A1) and exposes open APIs for seamless SMO and RIC integration.
3️⃣ How are templates created and reused? Through MX-HUB, where you can pull existing templates or publish your own with version control and collaboration support.
4️⃣ What are the hardware requirements? Requirements vary by network scale. A typical setup starts from 16–24 CPU cores at 4 GHz. When running in emulation mode, MX-DT removes the need for radio front-ends.
5️⃣ How is data privacy ensured? All data remains local in on-prem deployments. MX-DT supports audit logging, role-based access control (RBAC), and federated learning for secure data handling.