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Filtered Intelligence review

#42 of 43 in Learning Experience Platforms

An API and MCP infrastructure layer for structuring learning data for enterprise AI.

4.7/10Editor score
Contact Filtered
Filtered Intelligence4.7 Contact Filtered

Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026

Filtered Intelligence is an enterprise learning infrastructure layer from Filtered Technologies Ltd. It connects learning content, skills data and learning systems, breaks courses and documents into smaller parts, and maps information to skills, roles and proficiency levels. Relevance scoring can flag duplicated or obsolete material. The product is aimed at organisations working on AI readiness and workforce transformation, particularly those that need structured learning data behind existing workplace tools or an LXP rather than a standalone learner portal.

The platform is delivered through cloud deployment with an API interface, and its MCP connection makes linked learning content and skills data available to AI agents. Listed integrations include Microsoft Copilot, Microsoft Teams, Claude, ChatGPT Enterprise, Workday, Oracle, SAP, Google and Okta. This ecosystem focus suits enterprises that already operate several business, identity and learning systems and want a common data layer for AI-driven access. It also supports multi-source content, multi-format content and SCORM in its category capabilities.

Pricing uses a contact-sales model, so buyers should expect a commercial evaluation rather than self-serve plan selection. Filtered positions the product as an addition to, or possible alternative to, an existing LXP, not as the learner experience itself. Organisations seeking content structuring, skills mapping, relevance assessment and AI access should consider it; teams primarily looking for a learner portal, mobile experience or built-in learning paths should choose a more front-end-focused platform. Its value depends on having systems and content that can connect through APIs and on a clear enterprise use case for exposing structured learning data to AI.

Filtered Intelligence pros and cons

  • Where it wins
    • Structures content, skills, roles and proficiency levels in one layer
    • Scores relevance while flagging duplication and obsolete content
    • Exposes learning data to AI agents through APIs and MCP
  • Where it doesn't
    • It is infrastructure rather than a learner-facing LXP
    • Pricing uses a contact-sales model instead of published tiers
    • Cloud deployment and API access may not fit teams seeking learner apps

Filtered Intelligence fact sheet, pricing and score →

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