IBM Content Cortex
Make enterprise
content work
with AI.
Bring enterprise documents, content operations and AI together in a governed platform. Connect people and agents to the information they need, with controls across the content lifecycle.
From content to action
A trusted foundation for content-driven work.
Content Cortex brings together repository services, process automation and AI capabilities. It supports enterprise content from capture and classification through storage, retrieval and disposition.
Manage the lifecycle
Store and retrieve business documents, manage versions and classifications, and apply retention and records controls.
Work through conversation
Use the Navigator Core Agent to find documents, manage folders and update content through natural-language interactions.
Connect agents with MCP
Expose content operations through the Core MCP Server, enabling AI applications to work with repositories through a standardized interface.
Coordinate content processes
Combine content services and workflow capabilities to route document-centered work to the right teams.
Add document assistance
IBM Content Assistant is an optional add-on for document questions, summaries and comparisons in natural language.
Fit your environment
Plan traditional on-premises or containerized deployments. AI Services support Red Hat OpenShift and CNCF-compliant Kubernetes environments.
Where Content Cortex can help.
Illustrative application scenarios adapted from IBM’s industry examples. Each solution needs to be designed for your systems, policies and selected capabilities.
Banking · Audit preparation
Challenge: Regulatory records are scattered across repositories.
Approach: Classify documents, enrich metadata and apply retention or legal holds with an activity history.
Goal: Easier evidence retrieval and traceable reviews.
Insurance · Claims intake
Challenge: Claims arrive in different formats and need manual sorting.
Approach: Classify and organize incoming content; redact sensitive details before sharing.
Goal: Less repetitive handling during claims preparation.
Healthcare · Controlled sharing
Challenge: Records contain sensitive patient information.
Approach: Apply access policies and reviewed redaction while preserving the original.
Goal: Share appropriate information with authorized recipients.
Government · Information requests
Challenge: Large record volumes make retrieval difficult.
Approach: Centralize classification, retention and records management.
Goal: A more consistent response process.
Manufacturing · Document control
Challenge: Drawings and quality files have conflicting versions.
Approach: Centralize and classify governed documentation.
Goal: Find the controlling record.
Enterprise AI · Content agent
Challenge: A business assistant needs controlled access to enterprise documents.
Approach: Connect an AI application to content operations through MCP, with repository authorization and defined action scopes.
Goal: Help employees find and organize content from a conversational interface.
Match the edition to your use case.
Essentials
Core content governance, Navigator Core Agent and intelligent archiving.
Premium
Additional smart search and specialized agents for classification, extraction, redaction and legal hold.
Capabilities depend on edition, entitlement, version and configuration. IBM Content Assistant is an optional add-on. We can confirm the required components before implementation.
Start with the content.
Build around the process.
We help connect your content strategy with integration, business process automation and AI implementation. Bring us a workflow or document set, and we can shape a practical starting point.
- Assess
Map repositories, document types, policies and the business process. - Design
Define the capability set, architecture, integration and review controls. - Pilot
Start with a bounded use case and representative documents. - Improve
Review retrieval quality, handling effort and user adoption before expanding.
Which content process should move forward first?
Tell us about your repositories, FileNet environment or AI initiative. We can discuss the fit, required components and a focused demonstration.
