Blog / Valohai Mentioned in 2022 Gartner® Market Guide for DSML Engineering Platforms Report
Valohai Mentioned in 2022 Gartner® Market Guide for DSML Engineering Platforms Report

Valohai Mentioned in 2022 Gartner® Market Guide for DSML Engineering Platforms Report

Viktoriya Kuzina

Valohai, an MLOps platform built to empower practitioners developing cutting-edge machine learning models, has been mentioned as a Representative Vendor by Gartner® in the "Market Guide for DSML Engineering platforms" on 2 May 2022. This is the second time Valohai was included in the Gartner® report after being recognized as a Representative Vendor in the Market Guide for AI Trust, Risk and Security Management on 1 September 2021.

Gartner writes: "Data science and machine learning (DSML) engineering platforms combine the flexibility and utility of open-source ML frameworks with proprietary controls and procedures that support repeatable and reliable delivery of models into production". Valohai was mentioned as one of the Representative Vendors in this category.

Valohai focuses on reducing the time to market for commercial ML projects by bringing the model lifecycle under a single workflow since only a model running in production can bring value. Moreover, the platform prevents knowledge loss, makes it easier to update the product, and smoothens the governance audit.

"Currently, every company starting with large-scale machine learning needs to build a lot of overhead infrastructure before they can apply deep learning to solve the actual problem. By providing a standardized infrastructure and workflow, we help companies focus on the actual business driving machine learning models instead of the infrastructure," says Eero Laaksonen, CEO and co-founder of Valohai.

The Valohai platform is used by companies such as JFrog, Syngenta, Maytronics and Preligens. Visit for more information.

Gartner, Market Guide for DSML Engineering Platforms, Afraz Jaffri, Erick Brethenoux, Sumit Agarwal, Farhan Choudhary, Pieter den Hamer, Carlie Idoine, Shubhangi Vashisth, Peter Krensky, Alexander Linden, 2 May 2022

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