How do education content creators keep up with changing standards and make the best use of their existing content?
Finetune Catalog is an AI-powered content classification and alignment tool that tags learning or assessment content more accurately, deeply, and meaningfully.
Unlike other systems that rely on keywords and crosswalks, Catalog is powered by cutting-edge natural language processing (NLP) that analyzes deep conceptual and contextual relations in content to classify it against a wide variety of standards and taxonomies.
How can Catalog help you?
Tag learning content to updated standards or new standards — Catalog skips crosswalks entirely and analyzes the content directly to create significantly more accurate tags.
Make use of legacy content — Deploy your legacy content in new products. Catalog can help your organization tag the content quickly and efficiently so it is usable to your development teams.
Content insight and analytics — Catalog can create a picture of your inventory so you know what you have at your disposal when you bid, what gaps you need to fill, and what you are working with when ideating new products for the market.
Adaptive Learning Systems
Create an adaptive and personalized learning system — Adaptive systems are excellent ways to provide remediation and track growth for students who need extra attention. More precise and accurate tagging is essential to enable such systems.
Quality assure tagging work — Catalog can be a check on internal teams whose time is better spent on content development, and external teams whose judgement and quality of tagging vary greatly.
Finetune Catalog™ Differentiators
Catalog uses the direct phrase as truth for every tagging event; it does not rely on keywords or previous associations. This leads to significantly higher accuracy.
Fast & Responsive
Tagging projects can take time, especially if the tagging need arises because of an incoming opportunity. Catalog’s AI amplifies SME productivity and cuts down content tagging workload.
Direct Analysis of Original Text
No Crosswalk! The content is analyzed and tagged using the original context which creates more accurate tagging. Discard the superficial tagging of raw content and crosswalks and remove propagated and magnified errors!
Owned GUIDs & Fair Pricing
Catalog will not lock the client into a system of proprietary GUID keys, and it will also work within your existing system.
Because it is primarily driven by AI analysis, the costs are significantly less.