DataOps.live, The Data Products Company, is offering a new range of AIOps capabilities that provides end-to-end lifecycle management of AI workloads from development to production.
Centered around Snowflake Cortex and AWS Bedrock, these latest AIOps capabilities enable data engineers, data product owners, and data scientists to easily and quickly build and operationalize AI-driven data products with unparalleled consistency, scalability, and governance, the company said.
With these new AIOps features, users can now define, train, and validate models, as well as assess their fit through training loss scoring. This ensures AI models are optimized around each critical dimension, such as quality, cost, and speed for each business use case.
DataOps.live’s new range of AIOps capabilities include:
- Simplified technical abstractions: Quickly initiate MVPs, proof-of-technologies, and early development projects with capabilities that abstract technical complexities.
- Snowflake and AWS integration: Seamlessly integrate with the Snowflake ecosystem of LLMs through Snowflake Cortex, and the AWS ecosystem of LLMs through Amazon Bedrock, enabling the efficient use of a variety of LLMs either as the foundation model or fine-tuned models specialized for an organization’s domain.
- Comprehensive model management: Automate model training, fine-tuning, and assess/re-assess quality drift over time to ensure optimal performance.
- Governance and scalability: Drive operational efficiency with built-in CI/CD, security, and governance, and reduce operational costs by right-sizing models for specific business needs.
- Improved data engineering productivity: Pre-built templates accelerate data preparation and model tailoring, enhancing data engineering 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. “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.”
For more information about this news, visit www.dataops.live.