Cisco launches AI-powered data fabric to unify enterprise analytics

Cisco has launched an AI-driven data fabric powered by Splunk, designed to help enterprises unify and analyze distributed business and machine data. The new architecture, unveiled at Splunk .conf25 in Boston, integrates the Cisco Data Fabric with Splunk Federated Search for Snowflake to enable AI-powered insights from machine-generated telemetry across multiple platforms.

What you should know: The Cisco Data Fabric creates a unified framework that connects disparate data sources for comprehensive analytics and AI applications.

• Built using Splunk Enterprise and Splunk Cloud Platform capabilities, the fabric federates data from cloud, on-premises, and platforms like Snowflake and Splunk Indexes.
• The system applies AI and machine learning to create a single analytical view from previously siloed data sources.
• A companion Machine Data Lake provides a virtual repository for federated data sources.

Key capabilities: The platform delivers four core features designed to transform how enterprises handle machine data.

• Time Series Foundation Model (TSFM) provides advanced pattern analysis and temporal reasoning for anomaly detection, forecasting, and automated root cause analysis.
• Intelligent data foundation transforms data from SecOps, ITOps, DevOps, and NetOps into real-time actionable insights.
• Borderless real-time search and analysis enables federated searches across Amazon S3, Apache Iceberg, Delta Lake, Snowflake, and Microsoft Azure.
• Flexible and open architecture adapts to any environment with open standards and plug-and-play integrations.

In plain English: Think of this like creating a universal translator for your company’s data. Instead of having information trapped in separate systems that can’t talk to each other, Cisco’s platform connects everything—whether it’s stored in the cloud, on company servers, or with third-party services like Snowflake (a cloud data storage company). The AI then analyzes patterns across all this combined information to spot problems, predict issues, and help businesses make better decisions.

The Snowflake integration: Splunk Federated Search for Snowflake combines machine and business data across multiple platforms in unified workflows.

• The integration enables enterprises to analyze and correlate data from business databases, S3 storage, and Splunk indexes simultaneously.
• Companies can perform distributed queries to understand business impacts of performance changes or telemetry shifts.
• The system simplifies data management while providing deeper operational and business insights.

What they’re saying: Cisco executives emphasize the platform’s ability to scale data analysis across distributed environments.

• “This is really the notion of weaving data together wherever it is, leading AI into it, and delivering a turnkey solution that allows customers to leverage this machine data in a way they already have been with Splunk,” says Kamal Hathi, senior vice president and general manager of the Splunk business unit at Cisco.
• “We’re talking about going through these little ponds and bundles of data and combining them as a set into one federated, distributed view, so we can start to scale and work with data, literally infinite scales, because data can be in all kinds of places,” Hathi explains.

Availability timeline: The platform components will roll out in phases through 2026.

• The Cisco Data Fabric is available immediately, with additional data management, federation and AI features coming through 2026.
• Splunk Federated Search for Snowflake will become generally available for Splunk Cloud AWS commercial customers in July 2026.
• The Time Series Foundation Model will be listed on the open-source Hugging Face community in November 2025.