EdgeImpulse Inc.
SAN JOSE, CA · Founded 2019 · CIK 0001819146 · Software
Machine learning development platform for edge devices
edgeimpulse.com →- Grants
- —
- No SBIR or STTR on record
- Sector median: 0
- Raised
- $53M
- 3 Form D · Dec 2021
- 57 months since last filing
- Contracts
- —
- No federal contracts on record
- Patents
- 16
- 2 granted · 14 pending
- Sector median: 0
Capital Timeline
Federal ↑Equity ↓202020212022
| Date | Event | Source | Amount |
|---|---|---|---|
| Private capital raised | Form D · SEC | $3,820,000 | |
| Private capital raised | Form D · SEC | $14,999,983 | |
| Private capital raised | Form D · SEC | $34,000,000 |
Form D · SEC
Peer position
| # | Company | Contracts | Disclosed equity |
|---|---|---|---|
| 2088 | Footura Inc. | — | $20K |
| 2089 | Sesame AI, Inc. | — | $10M |
| 2090 | Vessl, Inc. | — | $3.0M |
| 2091 | EdgeImpulse Inc. | — | $53M |
| 2092 | Harmonya, Inc. | — | $20M |
| 2093 | sanas.ai Inc. | — | $51M |
| 2094 | SweetSense Inc. | — | $5.6M |
Ranked on federal contract value rather than capital raised. The equity column is the comparison worth making — companies at the same procurement position often sit at very different points in their funding history.
Founders & Team
- Zach ShelbyDirector · Executive Officer
- Zachary ShelbyDirector · Executive Officer
Patents
- Removal of Motion Artifacts in a Photoplethysmography Signalapplication
- Compiling Machine Learning Software For Execution At Edge Devicesapplication
- Trigger-Based Data Ingestion for Machine Learning Using Edge Deviceapplication
- Computer Architecture For Predicting Energy Consumption Of Machine Learning Inferenceapplication
- Configuring a Sensing System for an Embedded Devicegranted
- Determining A Post-processing Configuration For Post-processing Output Data From A Pipelinegranted
- Determining a Value for a Digital Signal Processing Component Based on Input Data Corresponding to Classesapplication
- Anomaly Detection System for Embedded Devicesapplication
- Configuring an Object Detection System for an Embedded Deviceapplication
- Configuring a Pipeline Including a Signal Processing Component and a Machine Learning Componentapplication
- Predicting Energy Consumption of Machine Learning Inferenceapplication
- Compiling Machine Learning Software for Execution at Edge Devicesapplication