As enterprises move artificial intelligence from experimentation into production, strong governance, consistent data context, and secure access are becoming essential. Snowflake has announced new capabilities across its Horizon Catalog designed to help organisations govern, contextualise, and secure AI systems at scale.
The updates address several challenges that can undermine enterprise AI initiatives, including inconsistent data definitions, fragmented business logic, limited visibility, and concerns about how AI agents access sensitive information. By bringing governance, context, and security together, Snowflake aims to help businesses deploy trusted AI while maintaining compliance and control.
Creating Consistent Business Context with Horizon Context
A key addition is Horizon Context, a context layer that helps organisations maintain consistent business definitions and data interpretations across databases, data lakes, business intelligence tools, applications, and AI systems.
Without a shared semantic foundation, different teams and AI agents may interpret the same business metric differently. For example, “active customer,” “net revenue,” or “product availability” may have varying definitions across departments. These inconsistencies can lead to inaccurate analysis, unreliable AI outputs, and poor decision-making.
Horizon Context enables enterprises to create and maintain semantic views and shared business logic. This allows analytics tools, applications, and AI agents to work from a common understanding of organisational data. Snowflake is also supporting interoperability initiatives such as Open Semantic Interchange, helping enterprises extend consistent context across a broader technology ecosystem.
Expanding Security for Enterprise AI Agents
Snowflake is also introducing security capabilities designed for emerging AI environments. These include agent identity management, AI security posture monitoring, and centralised controls for governing how AI systems access enterprise data.
Agent identity management can help organisations identify individual AI agents, determine what information they can access, and apply appropriate permissions. Centralised governance also gives security teams greater visibility into AI activity, supporting stronger oversight and accountability.
These controls are particularly important as AI agents become capable of independently analysing data, initiating actions, and participating in operational workflows. Applying existing enterprise security principles to agents can help reduce unauthorised access, data exposure, and compliance risks.
Adaptive Compute Simplifies AI Workload Management
Alongside the Horizon Catalog enhancements, Snowflake introduced Adaptive Compute. The capability automatically adjusts compute and software resources in real time based on workload requirements.
This can reduce the need for teams to manually provision and optimise infrastructure for dynamic AI and application workloads. It also supports Snowflake’s broader vision for a serverless environment where performance, resource allocation, governance, and security are managed within a unified platform.
Turning Trusted Data into Trusted AI
For enterprises, scalable AI requires more than powerful models. It requires governed data, shared business meaning, secure access, continuous monitoring, and efficient infrastructure.
As a Snowflake partner, Prolifics helps organisations establish trusted data foundations, modernise analytics environments, strengthen governance, and operationalise AI use cases. By combining Snowflake’s evolving AI Data Cloud capabilities with Prolifics’ data engineering, governance, security, and AI expertise, enterprises can progress from isolated pilots to secure, business-ready AI solutions.
Snowflake’s latest updates signal a clear direction for enterprise AI: intelligence must be built on governed data, consistent context, and security by design.
Media Contact: Chithra Sivaramakrishnan | +1(646) 362-3877 | chithra.sivaramakrishnan@prolifics.com
Frequently Asked Questions
1. What is Snowflake Horizon Catalog?
Snowflake Horizon Catalog is a collection of governance capabilities for discovering, managing, protecting, and monitoring data and AI assets across enterprise environments.
2. What is Horizon Context?
Horizon Context is a shared context layer that helps maintain consistent business definitions, semantic views, and data interpretations across databases, applications, analytics tools, and AI systems.
3. How do these updates improve AI security?
The updates introduce capabilities such as AI agent identity management, security posture monitoring, and centralised controls for managing AI access to enterprise data.
4. What is Snowflake Adaptive Compute?
Adaptive Compute automatically adjusts compute and software resources according to workload demands, simplifying infrastructure management for AI, analytics, and application workloads.
5. How can Prolifics support Snowflake AI initiatives?
Prolifics can help enterprises modernise data platforms, implement governance frameworks, integrate data sources, secure AI workloads, and build scalable AI solutions using Snowflake’s platform capabilities.
