
Comet
Provides a self-hosted and cloud-based meta ML platform allowing data scientists and teams to track, compare, explain, optimize experiments.
Date | Investors | Amount | Round |
---|---|---|---|
- | investor investor investor investor investor investor | €0.0 | round |
investor | €0.0 | round | |
investor investor investor investor investor | €0.0 | round | |
investor investor investor | €0.0 | round | |
investor investor investor | €0.0 | round | |
investor investor investor | €0.0 | round | |
* | $50.0m | Series B | |
Total Funding | 000k |
USD | 2019 | 2020 | 2021 | 2023 |
---|---|---|---|---|
Revenues | 0000 | 0000 | 0000 | 0000 |
% growth | - | - | 29 % | - |
EBITDA | 0000 | 0000 | 0000 | 0000 |
Profit | 0000 | 0000 | 0000 | 0000 |
EV | 0000 | 0000 | 0000 | 0000 |
EV / revenue | 00.0x | 00.0x | 00.0x | 00.0x |
EV / EBITDA | 00.0x | 00.0x | 00.0x | 00.0x |
R&D budget | 0000 | 0000 | 0000 | 0000 |
Source: Dealroom estimates
Related Content
Comet.ml is a startup that operates in the machine learning (ML) and artificial intelligence (AI) industry. It provides a platform that helps data scientists and ML engineers manage and improve their models throughout the machine learning operations (MLOps) lifecycle. The platform offers features such as Comet Artifacts, which allows users to track and upload data directly or by storing a reference to it. It also includes the Comet Model Registry, which helps users keep track of their models ready for deployment.
The company's platform is tightly integrated with Comet Experiment Management, providing full lineage from training to production. This means that users can see the entire history of their model, from the initial training data to the final deployed version. The platform also helps users identify and track the performance of their models over time, which can degrade due to drift or data quality issues.
Comet.ml's clients are primarily data scientists, ML engineers, and other professionals or organizations involved in developing and deploying ML models. The company operates in the growing AI and ML market, which is increasingly recognizing the importance of MLOps for successful ML deployments.
The business model of Comet.ml is likely based on a subscription or usage-based pricing model, where clients pay for the services and features they use on the platform. This could include fees for data storage, model tracking, and other features.
Keywords: Machine Learning, Artificial Intelligence, MLOps, Data Science, Model Management, Model Deployment, Model Performance Tracking, Data Tracking, Comet Artifacts, Comet Model Registry.