
VertaAI
Software infrastructure to help enterprise data science and machine learning (ML) teams rapidly develop and deploy ML models.
Date | Investors | Amount | Round |
---|---|---|---|
- | investor investor investor investor | €0.0 | round |
investor investor | €0.0 | round | |
investor investor | €0.0 | round | |
* | N/A | Acquisition | |
Total Funding | 000k |






USD | 2020 | 2021 | 2022 | 2023 |
---|---|---|---|---|
Revenues | 0000 | 0000 | 0000 | 0000 |
% growth | - | 136 % | 30 % | 7 % |
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
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VertaAI provides a software infrastructure platform designed to help enterprise data science and machine learning (ML) teams manage the entire lifecycle of their models. The company targets organizations looking to scale their AI initiatives, offering tools that bridge the gap between data scientists and developers. Verta's business model centers on its Operational AI Platform, which is offered as a service that can be deployed as SaaS, on-premise, or in a virtual private cloud, catering to enterprise clients.
The company was founded in 2018 by Dr. Manasi Vartak (CEO) and Dr. Conrado Miranda (CTO). Vartak's journey into entrepreneurship began during her Ph.D. at MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL), where she created ModelDB, the first open-source system for managing machine learning models. Her experiences in applied data science roles at Google, Twitter, and Facebook, working on projects like ad recommendations and feed ranking systems, provided her with firsthand insight into the challenges of operationalizing ML models. This academic research and industry experience formed the foundation of Verta. The company officially launched from stealth in August 2020 after securing $10 million in a Series A funding round led by Intel Capital, with participation from initial seed investor General Catalyst.
Verta's platform addresses critical challenges in the MLOps space by providing a unified solution for model management, deployment, operations, monitoring, and governance. Its core is the Verta Enterprise Model Management system, which acts as a central repository for all model assets, integrating experiment tracking, versioning, and monitoring. The platform is designed to be interoperable with a wide array of tools data scientists use, including TensorFlow, PyTorch, and Spark.ml, allowing teams to standardize fragmented workflows and reduce model deployment times significantly. Key features include automated monitoring for performance and data drift, outlier detection, and integrations with enterprise IT systems like Apache Kafka, Datadog, and identity providers such as Active Directory and Okta. In June 2024, Verta was acquired by Cloudera, a data company focused on enterprise AI. The acquisition integrated Verta's team and its Operational AI Platform into Cloudera's machine learning division to enhance Cloudera's capabilities in serving the growing demand for enterprise AI.
Keywords: MLOps platform, model management, machine learning operations, AI governance, model deployment, model monitoring, data science infrastructure, ModelDB, enterprise AI, model versioning, experiment tracking, ML lifecycle management, operational AI, retrieval-augmented generation, generative AI workbench, AI model catalog, CI/CD for ML, Cloudera, Manasi Vartak, model risk management, real-time AI, responsible AI, AI regulation compliance