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CTERA’s Intelligent Data Platform is designed to unify unstructured enterprise data into a secure fabric that serves as a foundation for AI agents. By transforming the file system into an “agentic coordination layer,” CTERA enables organizations to make their data AI-ready without requiring extensive migration or data movement. This capability addresses the challenges faced by enterprises across financial services, telecom, and manufacturing, which often grapple with petabytes of disorganized unstructured data that needs to be leveraged for business intelligence and automated workflows. The platform facilitates this by allowing agents to automatically process files dropped into designated “magic folders” and extract valuable insights.
The platform’s Content Services are key to this process, transcribing audio files, performing OCR on scanned PDFs, classifying data, and extracting or augmenting metadata. Users define schemas, often in JSON format, to specify the exact information to be extracted from unstructured data, such as call outcomes, customer complaints, or contract details. CTERA then automatically generates “derivative artifacts”: summaries, tags, keywords, and structured metadata files that inherit the permissions of the original file and are stored alongside it. This approach allows AI agents and large language models (LLMs) to efficiently query and analyze data as if it were a structured database, without needing to directly access the original, often complex, raw binary files.
CTERA demonstrated several real-world applications, including analyzing call center conversations to identify churn risk and escalate relevant calls, processing legal contracts to extract critical information, and classifying sensitive data, such as Protected Health Information (PHI), to enforce access restrictions. The system supports building autonomous agents that can execute these workflows in real time or periodically, and even generate dynamic dashboards. Addressing security and governance concerns, CTERA ensures that all derivative artifacts maintain the security posture of the original data, integrates with data loss prevention (DLP) tools, and offers immutable snapshots as frequently as every five minutes to protect against accidental deletions or malicious actions by agents or users, thereby providing robust audit trails and recovery capabilities.
Personnel: Dylan Locsin
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