Canopus Networks
Canopus Networks is a provider of AI-based Network Traffic Analytics software that gives Telecommunications Service Providers deep visibility into application usage and user experience over their fixed-line and 5G mobile networks.
| Date | Investors | Amount | Round |
|---|---|---|---|
| - | investor | €0.0 | round |
| investor | €0.0 | round | |
| investor investor | €0.0 | round | |
* | AUD4.5m Valuation: AUD50.0m 11.2x EV/Revenue | Series A | |
| Total Funding | 000k | ||
| USD | 2021 | 2022 | 2023 |
|---|---|---|---|
| Revenues | 0000 | 0000 | 0000 |
| % growth | - | 119 % | 26 % |
| EBITDA | 0000 | 0000 | 0000 |
| Profit | 0000 | 0000 | 0000 |
| EV | 0000 | 0000 | 0000 |
| EV / revenue | 00.0x | 00.0x | 00.0x |
| EV / EBITDA | 00.0x | 00.0x | 00.0x |
| R&D budget | 0000 | 0000 | 0000 |
Source: Dealroom estimates
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Canopus Networks, a 2018 spin-off from the University of New South Wales (UNSW), was co-founded by Professor Vijay Sivaraman and Himal Kumar. Both founders are recognized leaders in the field of Software Defined Networking, with their academic and research backgrounds from UNSW's School of Electrical Engineering and Telecommunications directly shaping the company's technological foundation.
The company provides an AI-based network traffic analytics platform designed for the telecommunications industry. This software leverages programmable switch (P4) technology to offer deep and real-time visibility into network traffic at a terabit scale. The core of its business is to help telecommunications providers accurately measure and enhance the online experience for their users. By offering detailed analytics, Canopus Networks enables its clients to understand network usage, classify traffic, and optimize performance, ultimately redefining how networks are operated and managed.
The business model is centered on licensing its specialized software to telecommunication companies. These clients use the platform to gain a competitive edge by improving their network's efficiency and the quality of service delivered to end-users. The technology is designed to be a cost-effective solution for gaining deep insights into network traffic, which is a significant challenge for large-scale network operators.
Keywords: network analytics, traffic classification, telecommunications, AI, software defined networking, P4, network visibility, user experience, terabit-scale, network management