Valohai for Snowflake

The challenge: operationalizing AI on top of Snowflake

Snowflake customers are increasingly building machine learning, computer vision, and generative AI systems that rely on Snowflake data. These systems often begin as experiments, but quickly grow in complexity as models, prompts, embeddings, and evaluation logic evolve.

At this stage, teams face a common set of challenges:

• Notebook-based workflows that do not scale operationally
• Limited visibility into how models and results were produced
• Fragmented tooling that complicates governance and audits
• Increasing risk as AI systems move closer to production use

Addressing these challenges requires more than data access or model hosting. It requires a consistent execution layer that brings structure, traceability, and governance to AI workflows.

Valohai as the execution layer for Snowflake-based AI

Valohai acts as the workflow backbone for Snowflake customers building and operating AI systems.

Through its native integration with Snowflake, Valohai enables teams to orchestrate and manage AI workflows that interact directly with Snowflake data. These workflows can span the full lifecycle of AI development and operation, including:

• Model training and retraining
• Embedding generation and RAG ingestion pipelines
• Evaluation and validation workflows
• Deployment and promotion to production

Valohai captures full lineage across data, code, models, prompts, and embeddings, creating a system of record for AI execution that supports traceability, explainability, and auditability.

Valohai coordinates execution without replacing Snowflake’s role as the governed data platform.

Designed for real production environments

The Valohai and Snowflake integration has been developed in close collaboration with one of the world’s leading medical technology companies operating in a highly regulated environment.

Valohai serves as the core MLOps platform for this organization today. The Snowflake integration was built to meet concrete enterprise requirements around governance, scale, and operational reliability, and is live in the customer’s environment with onboarding underway.

This real-world validation ensures that the integration is designed for serious production use, not isolated experimentation.

Freedom to build, structure to operate

Valohai does not impose frameworks, models, or cloud lock-in.

Snowflake customers retain full freedom in how they build AI systems, including their choice of:

• Machine learning frameworks
• Large language models and providers
• Vector databases and agent frameworks

Valohai provides structure in how those systems are executed, evaluated, and maintained over time. This separation allows teams to innovate rapidly while maintaining the governance required for enterprise operations.

Interested in a Snowflake Marketplace Private Offer?

Valohai is available via the Snowflake Marketplace as a private offer. If you’re interested in procuring Valohai through Snowflake or aligning it with an existing Snowflake agreement, reach out to the Valohai Partnerships team.

We’ll guide you through the private offer process and help ensure Valohai is set up to match your Snowflake environment, security requirements, and commercial model.

Technical architecture and documentation

Valohai integrates with Snowflake as an execution and orchestration layer for AI workflows, operating in close alignment with the customer’s Snowflake environment.

Valohai acts as a control and execution layer that coordinates AI workloads, while Snowflake remains the system of record for enterprise data. This separation allows teams to preserve data gravity, security, and governance in Snowflake, while gaining a consistent execution layer for machine learning and generative AI workflows.

For teams evaluating technical fit, Valohai provides detailed documentation covering the architecture and operational model of the Snowflake integration, including:

• Execution and deployment architecture
• Data access patterns and security considerations
• Workflow orchestration and lineage tracking
• Integration with external compute, models, and frameworks

Explore the Valohai technical documentation to learn how the integration is implemented in practice.

Available via Snowflake Marketplace

Valohai is available via the Snowflake Marketplace, making it easy for Snowflake customers to adopt Valohai as part of their existing environment.

Customers can deploy Valohai to support governed AI workflows that operate in close alignment with Snowflake’s security, access control, and compliance capabilities.

Who this is for

Valohai for Snowflake is designed for organizations that:

• Are building machine learning or generative AI systems on Snowflake data
• Need traceability, auditability, and governance for AI workflows
• Operate in regulated or security-conscious environments
• Want to move from experimentation to durable production AI

Learn more

If you are a Snowflake customer looking to operationalize AI with confidence, Valohai provides the execution layer to support that journey.

Explore Valohai on the Snowflake Marketplace or contact us to learn how Valohai and Snowflake work together to support governed AI execution at scale.