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DataOps.live, a London-based startup specializing in streamlining data operations with real-time management and collaboration tools, announced last week the immediate availability of its AIOps capabilities to further enhance its product suite.
The new features offer end-to-end lifecycle management of AI workloads. Leveraging AWS Bedrock and Snowflake Cortex, the new AIOps capabilities allow data engineers, product owners, and data scientists to effectively develop and deploy AI-driven data products, for improved consistency, scalability, and governance.
Businesses often rely on manual processes to create, deploy, and manage AI workloads. However, this approach can be time-consuming, inefficient, and prone to errors. This has emerged as a major hurdle for streamlined operations.
Through its new AIOps features, DataOps.live aims to automate and simplify the processes of defining, training, and validating AI models. Users can now evaluate models more effectively using training loss scoring, a metric that gauges model performance. This allows businesses to optimize their AI models according to key factors such as cost, quality, speed, and other metrics tailored to their unique use cases.
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Snowflake Cortex acts as a platform for storing, transforming, and analyzing data, which can then be used by AI/ML models in AI systems, such as AWS Bedrock.
The data management practice of DataOps is focused on building, managing, and operationalizing data pipelines, while AIOps is dedicated to optimizing and maintaining AI models to ensure efficient performance within those pipelines.
DataOps.live claims that adopting DataOps can boost data engineers’ productivity by up to 10x, ensuring data quality, governance, and streamlined pipeline efficiency. The growing investment and importance of AI lifecycle management is evident in the 26.6% year-on-year increase in this category in the last 12 months, according to IDC.
DataOps.live has historically integrated with various cloud platforms and data management solutions, including AWS and Snowflake, to enhance its capabilities. However, with the recent introduction of its AIOps features, DataLiveOps has specifically tapped into AWS Bedrock and Snowflake Cortex to streamline AI model management and improve data workflows.
The new features include Simplified Technical Abstractions to quickly initiate MVPs and early development projects to simplify technical abstractions. The new Comprehensive Model Management capabilities enable automation of training and fine-tuning while assessing quality drift to maintain optimal model performance.
Additionally, DataLiveOps has introduced new tools to enhance operational efficiency with built-in CI/CD and security while utilizing pre-built templates to accelerate data preparation and model customization, ultimately reducing costs and boosting productivity.
“With the launch of our new range of AIOps capabilities, we’re providing a complete foundational level of capability that boosts data engineering productivity and provides the critical capabilities needed to operationalize AI Models and Workloads within DataOps.live pipelines,” said Guy Adams, CTO at DataOps.live.
(Image courtesy DataOps.live)
“Developer productivity, model governance, model change control, and model auditability are critical as businesses make real decisions based on their AI models, and DataOps.live ensures that these elements are baked into every step as we operationalize AI Workloads.”
In a recent interview with Dattnami, Justice Mullen, the co-founder and CEO of DataOps.live, shared that the DataOps.live was founded to function as an “assembly line” for data products, enabling easier building, testing, and deployment in the Snowflake environment.
Mullen mentioned that Snowflake is not only a customer of DataOps.live but also an investor, referring to the $17.5 million Series A funding round in May 2023.
DataOps.live’s introduction of AIOps capabilities with Snowflake Cortex and AWS Bedrock is a significant advancement for the startup. By integrating AI model management into DataOps workflows, DataOps.live addresses the complexity of AI-driven data products and highlights the industry’s growing focus on AI management.
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