LGN Innovations
Scaling AI infrastructure for globally deployed autonomous systems.
| Date | Investors | Amount | Round |
|---|---|---|---|
| - | investor investor investor investor investor investor | €0.0 | round |
| investor | €0.0 | round | |
| investor | €0.0 | round | |
| investor | €0.0 | round | |
| investor investor investor | €0.0 | round | |
| investor | €0.0 | round | |
| N/A | €0.0 | round | |
* | N/A | Support Program | |
| Total Funding | 000k | ||
| USD | 2022 | 2023 |
|---|---|---|
| Revenues | 0000 | 0000 |
| % growth | - | 300 % |
| EBITDA | 0000 | 0000 |
| Profit | 0000 | 0000 |
| EV | 0000 | 0000 |
| EV / revenue | 00.0x | 00.0x |
| EV / EBITDA | 00.0x | 00.0x |
| R&D budget | 0000 | 0000 |
Source: Dealroom estimates
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LGN Innovations is a technology company specializing in Edge Artificial Intelligence (AI). The company provides software that offers comprehensive technical and financial control of Edge AI systems. This allows for the orchestration of deployments, supervision of models, optimization of system learning, and cost control. LGN extends OpenShift and Kubernetes to manage and scale Edge AI deployments.
The company serves clients who need to deploy AI systems in real-world, resource-constrained environments. The market for Edge AI is experiencing significant growth, driven by the increasing use of AI in various applications. LGN's business model is centered on providing its software products and solutions to help organizations scale their Edge AI deployments effectively. The company also offers services to optimize AI models for specific hardware and build resilience to external factors.
LGN's technology has a broad range of applications, including autonomous systems, by enabling human-level perception in embedded hardware. The company has a strong academic background, with founders from MIT and Oxbridge, and has secured funding to support its growth.
Keywords: Edge AI, AI management software, OpenShift, Kubernetes, autonomous systems, human-level perception, embedded hardware, AI deployments, system learning, cost control