Mondeca software

Comprehensive suite of taxonomy, content tagging and knowledge navigation tools

Intelligent Taxonomy Manager

Easy management of a controlled vocabulary, taxonomy or ontology

Mondeca offers a  comprehensive solution for taxonomy and ontology management an well as artificial intelligence based content tagging. Create your metadata repository with Intelligent Taxonomy Manager.

Key features

Multiple taxonomies

Multiple languages

  • Any language and character set
  • Alignment of taxonomies
  • Translation management

Access rights

  • Fine grained user profiles
  • Integrates with enterprise IAM

Import / export data

  • CSV, Excel
  • Semantic standards: OWL, RDF, XML, SKOS, XTM, RDF/XML, N-Triples, Turtle, N3, JSON-LD, and RDF/JSON


  • Easy navigation
  • End user views
  • Graphical data representation

Query and search

  • Advanced search UI
  • Multicriteria search
  • Saved search
  • Search based imports & exports

Improve data

Alert & track

  • Event based alerts
  • Event based data push
  • Audit trail
  • Activity dashboards

Open access to your data

Stop losing time building and searching for reference data. Establish a single source of truth for your teams, partners, and clients. Start out simple and ramp up with more complex data representations to take up new challenges in time.

Content Auto-tagging manager

Speed up indexing work and free up quality time for assessment

Enable automation of mundane and time-consuming indexing processes while allowing manual, qualitative review of machine-processed content using Content Auto-Tagging Manager

Key features


  • Store your work in the application persistence layer to support iterations and fine tuning of manual indexing work


  • Use existing templates for the creation of new resources (profiles, connectors, scripts, workflows, and engines)
  • Edit and reload CAM central configuration without server restart
  • View classification rules, RDF resources, and gazetteers


  • Use CAM REST web service to execute auto-tagging workflows from content-centric applications
  • Connect to CMS: Sharepoint, Drupal, WordPress
  • Search engines: Elastic, SolR
  • Graph databases


  • Execute, control and review results with informative and visual information
  • Modular display: select side by side panels or widgets when reviewing results
  • Monitor and configure CAM directly from the administration UIs

Execute multiple analyses

  • Analyze content using NLP powered by business taxonomies
  • Classify content using SPARQL classifications rules
  • Execute Machine-learning to train CAM on a corpus of documents – and apply ML at sentence, paragraph or document level

Learn from content

  • Analyze a corpus of several documents in one go
  • Detect candidate terms
  • Bulk extract terminology from a corpus with TF/IDF scores
  • Compute precision/recall metrics at document or corpus level

Application Monitoring

  • Track workload and activities from the user and administrator dashboards
  • Server nodes activity and storage capacity details

Permissions & Security

  • Editable and granular rights for profiles
  • Optionally map permissions to Mondeca Identity and Access Management component

Machine learning

  • Supports Google Bert
  • Transformer models
  • Neuronal deep learning
  • Integrates spaCy library

How to use machine learning for content annotation

Unleash the power of the latest deep learning models
Solve your NLP tasks with state of the art Transformer models like BERT with CAM

When to use

When the rules required to properly execute the task are not known or to complex to formulate. You will also need an annotated set of data with at least a hundred examples for each category.

What can you do with machine learning models

Classify sentences or documents, identify named entities or concepts, detect sentiment and others.


Create and train your own model.  Alternatively, use the transfer learning approach – take an existing complex like a Transformer model and retrain it for your task.
Use Jupyter notebook to define and train Python ML models.
Here is an example of notebook for a BERT based Tensorflow model.
Train deep learning models on environments like Google Colab. Remember, training will work best on a GPU fitted server.
Once your model is ready, use the CAM AdminUI to import it and set up the serving environment.

Supported models

Gate plugins

  • Naive Bayes, Maximum Entropy, and Decision Trees (MALLET)
  • linear chain Conditional Random Fields (MALLET)
  • Support Vector Machines (LibSVM)

Python models including neuronal deep learning models

Enjoy the machine learning in an industrial grade production setup


Select the algorithm


Get annotated data set


Split into training and validation


Train using the training data set


Evaluate results using validation set


Deploy to production

Knowledge Browser

Knowledge Browser is a web-based portal featuring powerful search capabilities combined with graphical visualizations. It provides intuitive, read-only access to broad audiences who need to visualize, search, navigate and browse collections of enterprise data.

Your Challenges

  • Publish reference data using open standards and formats
  • Enable internal/external access to enterprise data via any web browser
  • Organize and control the type and amount of data shared with clients
  • Capture client requests for terminology improvement
  • Aggregate data sources to streamline integration with applications
Person browsing taxonmy graph Person browsing well structured taxonomy graph mind map

Browse, search & find, explore & discover, share & publish your data

knowledge browser

Key features


  • User-friendly ultra-intuitive access to data.
  • Navigate flat, hierarchical or graph-based terminologies

Explore and discover

  • Configurable home dashboard for quick access to predefined datasets
  • Graph-based visualization


  • Search enhanced through smart options
  • Auto suggestion and query interpretation
  • Multicriteria search


  • Refine search results based on facets (properties, types and data sources)
  • Sort results according to relevancy

Share & Publish

  • Configurable web portal
  • Connected to ITM and CAM
  • Standards REST services
  • Users can provide feedback, ask questions and download data

Move away from spreadsheet exchanges and think Graph

Let systems and targeted audiences take advantage of your enterprise data using semantic standards for data publishing and dissemination

Book a demo of Mondeca


Let’s talk about your project needs & goals

We will share with you how we can rapidly increase the performance and value of your taxonomy.

  • Discuss your use cases and challenges
  • Show relevant features and capabilities
  • Agree on next steps

Just complete the form and we will be in touch!