AI-enhanced Content Search - Compliance Information
General Information about the search
With product version 14.25.1 imc integrates a new platform-search functionality (Elasticsearch) into the imc Learning Suite.
Elasticsearch offers two distinct search modes (or types), which differ technically:
Lexical Search
This mode directly matches the words from the user's query with titles, descriptions, and keywords of the indexed learning content. It’s a purely text-based lookup - no artificial intelligence involved.
Semantic Search
In this mode, both the indexed learning content and the user’s query are converted into vectors using AI technologies. This allows the system to detect semantic similarities and retrieve related concepts and themes even if they are phrased differently from the query.
Customers can choose between these two modes per system. Lexical search is included out-of-the-box with the imc Learning Suite and is available by default. To use semantic search, the required AI services must be activated by imc. This is coordinated via the imc Service Desk.
For more details on the search, its functions, how to configure and use it, please see:
AI-enhanced Content Search
Third‑Party Providers
The following AI services are integrated into the imc SaaS platform to enable the search:
Elasticsearch: a standalone search and data analysis service using searchable indices accessed via REST APIs.
Ollama (for semantic search): an open-source tool for locally running large language models (LLMs) with support for text generation and embeddings.
Jeffh: (for semantic search) used embedding model.
Grafana: a monitoring platform used by imc for analytics.
Access Control (ACL)
Search results fully respect the access permissions defined by the customer. Each user sees only the learning media, courses, and learning paths they are authorized to access. Therefore results may vary between users.
Hosting
All services for the search are running in the imc clouds.
imc does not develop proprietary AI models. Instead, it provides third party AI services integrated into the imc SaaS platform. All data processing related to these services takes place solely within imc’s Azure Cloud infrastructure.
Activation & Deactivation
The search will be delivered within the standard product to all customers with default setting “lexical search” (no AI involved). The search becomes visible to users once Customers have configured the navigation points. Please see AI-enhanced Content Search | Configuration-&-settings for more details on the configuration
To use semantic search AI services must be made available for the customer's system:
Subscription service (if not already in place)
LLM and embedding service
Provisioning of these services must be requested by the Customer admin via the imc Service Desk, who will coordinate with the relevant imc Deployment and Hosting teams.
Once these services have been deployed by imc, Customers can decide for each system to switch from lexical to semantic search in the Configuration Manager.
After switching, a full re-indexing should be carried out, as the embedding service must now vectorize the entire content. See Data Connector Configuration | Full-indexing
At any time, Customers may decide per system to discontinue the use of AI services and revert back to lexical search:
By using the switch in the search configuration admins can change the search type back to lexical. This will change the method by which the search results are retrieved and ranked for the users (as explained at the beginning of this page).
Please note that switching back to lexical search will not automatically de-activate nor revert the deployment of the AI services. If Customers wish to have the AI services removed again, this can be requested via imc Service Desk.
Fair Use Policy
The semantic search service is generally available to Customers without fixed usage limits.
However, the provider expects fair and appropriate use within the scope of the contractually agreed purpose.
Usage that significantly exceeds the average of comparable Customers, or that negatively impacts system performance, stability, or availability for other users, may be classified as excessive.
In such cases, the provider reserves the right to contact the Customer to jointly agree on appropriate measures - such as technical adjustments, usage restrictions, or a transition to a higher-performance model.
Any restrictions will only be implemented following prior consultation.
The provider also reserves the right to update this Fair Use Policy as needed. Customers will be informed of any changes in a timely manner.
Data Protection
To provide and improve the search functionality, imc processes certain metadata, technical data, and usage-related information. While these data categories are not inherently personal, it cannot be entirely excluded that they may contain or be linkable to personal data. Accordingly, imc treats such data in accordance with applicable data protection laws.
Legal Basis
The processing of such personal data in this context is carried out:
pursuant to Art. 6(1)(b) GDPR (performance of a contract), insofar as the processing is necessary for providing the agreed platform functionalities, including the search capabilities selected by the Customer;
pursuant to Art. 6(1)(f) GDPR (legitimate interest), namely to provide relevant search results and improve system performance and user experience. imc ensures that such processing does not override the fundamental rights and freedoms of the data subject.
Data Minimisation and Retention
Search queries and related technical data are processed only to the extent necessary to provide the service, ensure system security, and optimise performance. Data is retained only as long as required for these purposes and is deleted in accordance with applicable data protection provisions.
No Use for Model Training
Customer data and user input are not used to train, fine-tune, or otherwise develop machine learning models.
Processed Data Includes:
Subscription Service
Embedding subscription and usage volume per tenant, group and user (anonymously) are saved in an imc-managed database
Indexing
Metadata from indexed Customer content (titles, descriptions, keywords) are stored in the search index.
Embeddings for both search queries and content are created using the embedding service within the Azure environment; data does not leave the imc-controlled infrastructure.
User Search Queries
Search inputs and recent search history (e.g., last six queries) are stored in an Azure Cloud database.
Users see their own search history in the UI. They can delete it at any time.
If semantic search is activated: imc tracks the amount of used word embedding tokens used per user (anonymously), per group and per client for search queries.
Metrics & KPI
Stored metrics are not user-related and include:
Timestamp of the search
Query content
Number of queries per Customer and tenant
Number of results returned
Number of zeroresult searches
Relevance score of results
Planned for the future: active filters used in queries
Search request profiling: user inputs may be stored as long as necessary to improve system functionality, troubleshoot errors, or analyze usage patterns; data is deleted according to legal requirements once no longer needed.
General Notes
Neither search inputs nor indexed Customer data are used for training or optimizing machine learning models; no further processing is done for model development.
Customers are strongly advised to inform their users not to enter sensitive, confidential, or personal data in the search field.
Use of the search function is at the user’s own risk. imc AG assumes no liability for any harm resulting from data input, transmission, processing, or misuse by third parties.
By using the search function, users accept responsibility for the content they provide and waive any claims against imc AG regarding its use or processing.
Please also see Guidelines and Recommendations for the Use of the AI-enhanced Content Search
Outlook and further developments
imc plans to extend semantic search to include media files (e.g., WBTs, audio transcripts) to support content-based search within files. This will enable a generative AI assistant to answer user questions about learning content.
Adding User Context
To improve personalization, imc plans to incorporate user context into search results and other services. Potential data points include:
The LMS page where the user is when making the search.
User role.
Profile information (interests).
Job profile and required competencies.
Learning history.
Learning preferences.
Customers will be informed before any such feature releases. The functionality will not be activated by default and will only be enabled upon the Customer’s explicit request.
If imc later changes the underlying AI model setup - e.g., replacing a selfhosted model with an externally hosted one - Customers will be notified in advance. Regardless of the model architecture, Customer data will never be used for the training, tuning, or development of AI models. All data is protected and processed in full compliance with applicable data protection laws.