5G Today to 6G Tomorrow
Our expertise in IP Protocol Stack, GSMA 5G Systems, RAN, VPP, DPDK, Routing, Neural networks, machine learning, K8S helped us to build very scalable, reliable and resilient solutions.
Bridging today’s 5G to tomorrow’s 6G Innovation
Our 5G Core-in-a-Box and CU-DU-in-a-Box (O-RAN) provide a complete, deployable 5G Standalone (SA) ecosystem. The system has been validated with an integrated RAN (Mini Radio Unit), our O-RAN components, our high-performance User Plane Function (UPF), and the full 5G Core stack (AMF, SMF, PCF, UDM, NRF, SCP, AUSF, NSSF). It has also been tested with commercial Samsung and MI devices using OpenSIM, along with over 10,000+ UEs. The platform supports real-time 10–25 Gbps throughput optimization, 5QI QoS latency benchmarking, and Multi-Slice orchestration.
A Singapore-based Telecom company and an India-based Deep Tech company are using this platform for Future Communication use-cases, helping bridge commercial readiness with research flexibility.
💡 Ideal For:
- Enterprises building 5G-enabled applications (Industrial IoT, AR/VR, robotics, edge AI).
- Telecom operators & OEMs testing interoperability and Private 5G deployments.
- Research Labs exploring R&D-grade environment for building low-latency edge computing.
- Building next-generation 6G frameworks, including AI-driven network control, adaptive spectrum management, and autonomous service assurance.
- Government & Defense evaluating secure, sovereign, field-deployable 5G systems.
Please feel free to ask for live demo sessions &
architecture walk-through showcasing
low-latency live video tests on
Samsung and MI devices using our
5G Core-in-a-Box together with our
CU-DU-in-a-Box (O-RAN) and
mini-RU. The setup includes an
SA environment with eMBB and
uRLLC slices, as well as Local Breakout.
Please email
connectus@tranzsilica.com
or
marketing@tranzsilica.com
.
Software-Defined to Self-Defined, Networks that Learn, Adapt, and Heal Themselves.
Our IP is transforming how data networks are managed at scale. Powered by AI-driven analytics and adaptive automation, it continuously detects anomalies in real time and heals issues before they impact users.
This applies to PNF, VNF, and CNF-based network components running across telecom backbones, enterprise networks, and cloud infrastructures, ensuring the delivery of reliable, always-on services.
A U.S based technology company, a Singapore-based telecom provider, and private-sector companies in India are using our solutions to manage their delivery networks.
💡 Key Capabilities:
- Continuously learns, adapts, and repairs network behavior (traffic patterns, latency hotspots, bandwidth trends).
- Predicts and prevents failures before they affect performance.
- Self-learning, adaptive, and self-repairing mechanism enhances SDN with AI-driven intelligence.
- Applies to PNF, VNF, and CNF-based network components across diverse infrastructures.
Engagement
Would a brief
10-minute technical discussion on
failure pattern discovery,
fault isolation,
auto-recovery workflows, and
congestion prediction help you evaluate
potential alignment with your ongoing roadmap?
If so, please feel free to contact us at:
connectus@tranzsilica.com
or
marketing@tranzsilica.com .
High-Performance, Low-Latency Data Plane Foundation
With deep expertise in Vector Packet Processing (VPP) and the Data Plane Development Kit (DPDK), and QoS algorithms, we deliver a high-performance data plane that powers the future of connectivity.
Our solutions enable ultra-high throughput, microsecond-level latency, and scalable efficiency, making them ideal for edge computing platforms and emerging 6G research.
Whether you’re an operator optimizing your network, a developer building latency-sensitive 5G applications, or a research team exploring next-generation architectures, our VPP + DPDK-powered QoS Framework ensures unmatched speed, reliability, and programmability. Real-time and data-intensive applications—such as AR/VR, IoT, connected vehicles, industrial automation, video analytics, and cloud gaming—can also benefit by applying this concept.
Why need us:
- Require ultra-low latency and high throughput to handle growing data volumes.
- Seek CPU-efficient packet processing for cost-effective scaling.
- Aim to enhance network reliability, programmability, and service agility.