Edge Impulse
Enables developers to create the next generation of intelligent device solutions with embedded machine learning.
| Date | Investors | Amount | Round |
|---|---|---|---|
| - | investor investor investor investor | €0.0 | round |
| investor | €0.0 | round | |
| investor investor investor investor | €0.0 | round | |
| investor investor investor investor investor | €0.0 | round | |
| investor investor investor investor investor investor | €0.0 Valuation: €0.0 | round | |
* | N/A | Acquisition | |
| Total Funding | 000k | ||
| USD | 2020 | 2022 | 2023 |
|---|---|---|---|
| Revenues | 0000 | 0000 | 0000 |
| % growth | - | - | 27 % |
| 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
Related Content
Edge Impulse is a tech startup that operates in the artificial intelligence (AI) and machine learning (ML) market. Its primary service is providing a platform that enables developers to build datasets, train models, and optimize libraries to run on any edge device. These devices range from low-power microcontroller units (MCUs) to efficient Linux CPU targets and graphics processing units (GPUs).
The company's clientele includes some of the world's most innovative companies, as well as nearly 100,000 engineers who choose Edge Impulse as their ML platform of choice. These clients use Edge Impulse's platform to add edge intelligence to their products, which can range from low-power wearables to industrial gateways.
Edge Impulse's business model is centered around its platform, which allows developers to get data from various sources, including their own sensor hardware, public datasets, and data generated through simulations or synthetic data generation. The platform also offers advanced data analysis tools to quickly detect data quality issues.
The company makes money by providing these services, which help to shorten product development lifecycles and optimize models for specific hardware acceleration capabilities. It also offers built-in integrations with a variety of partners, including MCUs to MPUs and GPUs, sensors, cloud services, data science tools, and digital twin platforms.
Keywords: Artificial Intelligence, Machine Learning, Edge Devices, Microcontroller Units, Linux CPU Targets, Graphics Processing Units, Data Analysis Tools, Hardware Acceleration, Product Development, Partner Integrations.