Bridge the gap between how humans communicate and what computers understand

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Make your content ready for AI-driven applications

Add business meaning to make content findable, comparable and query friendly
Unlock insight into your unstructured content
 
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Take up your next challenge

Capture and secure key enterprise metadata
Reuse and apply it consistently in core systems and workflows
Harness the power of graphs to solve the next enterprise challenges
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Semantic technology for business problems

For more than twenty years we have helped organizations across the private, public and academic sectors benefit from Semantic Technologies. The goal of Semantic Technology is to make computer systems understand content like text, voice, image or video. Our products help maintain meaningful business data, manage enterprise taxonomy,categorize content, define its subjects, discover items of interests, identify relationships and much more.

Problems we help solve

Complexity of information management

Get rid of inconsistencies in tags used to describe content, which lead to the inability to find content and documents on collaborative platforms (e.g. SharePoint)

Improve search capabilities

Export taxonomies and entities to the search engine querying layer to facilitate, control and disambiguate end user queries and expose semantic facets and filters in the results set

Interoperability

Establish and maintain alignments between different metadata sets to facilitate interoperability between different solutions

Intelligent e-mail processing

Understand incoming e-mail content, categorize and route to the right recipients

Solution mindset Person solving a problem - looking a shapes

Let's get started

It is not just about having the right business data – it’s about defining optimal ways to use it so that problems can be successfully resolved. We work closely with you to ensure that taxonomies and semantic analysis will support intended use cases. We support and train your business and IT teams throughout the deployment and integration processes to make them totally autonomous.

Precision in targeted alerts

Identify high level topics in long texts to direct content to the right person, department or organization

Context-based ad targeting

Map content to targeted audiences by combining taxonomies and precise semantic rules

Open domain-driven conversations with chatbots

Maintain and synchronize ontologies used as knowledge bases to track topics or entities of interest in the development of domain-driven conversational systems

Understand voice of customers

Detect and score important messages from a mass of user generated content

Efficiency in content syndication

Produce relevancy scores for every single tag to further boost precision in search results when dealing with content expressing multiple subjects

Mondeca’s products

ITM

Intelligent Taxonomy Manager

Software for taxonomy, knowledge, data governance and AI program managers.

An enterprise grade taxonomy software and metadata repository.

Build, manage and synchronize your business data, in any language.

Built-in semantic data model management

Define any type of data, attributes and relationships that support your business objectives.

OWL
SKOS
RDF
Sharepoint
REST

CAM

Content Auto-tagging Manager

Helps metadata and media managers generate smart tags.

Best-of-breed approach

Multiple simultaneous tagging techniques: linguistic/semantic analysis, rule-based classification and machine learning!

Insight into unstructured content

Extract business specific information from text, image, video and voice. Multiple languages supported.

Text
Image
Audio
Video
Neo4J
Elastic
Sharepoint
REST

KB

Knowledge Browser

Easy access to your knowledge graph, for everyone!

The power of search over a graph database.

Browse through your knowledge graph or through your taxonomies with a user-friendly search and graph visualizations.

A web portal and a REST web service.

Open your knowledge and expose valid and persistent enterprise data to a large number of users and to systems in place.

RDF
Neo4j
Elastic
Download
REST

Our keywords

Business specific taxonomy
Controlled vocabulary
Glossary, thesaurus
Knowledge graph
Metadata
Multilingual taxonomy
Ontology
Semantic data model
Taxonomy
Terminology
Vocabulary
Auto-tagging
Classification
Content tagging
Disambiguate
Document clustering
Inferred tags
Machine learning
Metadata
Named entity
Natural language
Part-of-speech tagging
Text analytics
Word2vec
Browse taxonomy
Faceted search
Full text search
Graph database
Knowledge graph browsing
Navigate through taxonomy
Semantic query
Taxonomy publication
Taxonomy visualization
Terminology publication

The people we work for

We work for a broad range of people. They are information managers, business managers or civil servants. We work for clients who have in-depth knowledge of technology, we work for people focused on business issues only. We learn a lot from all of them.

Analytics Manager
Chief Content Officer
Content Architect
Digital Experience Manager
Digital Transformation Leader
Knowledge Manager
Library & Taxonomy Manager
Metadata Manager
Ontologist
Product Metadata Manager
Sharepoint Consultant
Taxonomy Specialist
VP Content Strategy
VP Business Intelligence
VP Data And Analytics

Analytics Manager

Chief Content Officer

Digital Experience Manager

Knowledge Manager

Metadata Team Manager

Ontologist

Product Metadata Manager

Sharepoint Consultant

Taxonomy Manager

VP, Business Intelligence

VP, Data & Analytics

Featured project

City of Toronto Enterprise Classification

Search and analytics for employees and general public

The project

The City of Toronto has identified the need for an Enterprise Classification solution to support improved central data management, semantic tagging and classification of content, as well as dynamic integration of the City controlled vocabularies with the enterprise platforms in place. Based on the use cases and requirements Mondeca provides the City with the Intelligent Taxonomy Manager (ITM), Content Autotagging Manager (CA Manager) and Knowledge Browser (KB) as on-premises solutions together with APIs and web services to support tight integration with existing information systems. The goal of this project is to make City of Toronto content more searchable and improve the analytical capabilities for both City’s employees and the general public.

Please get in touch with us to see how we can help with taxonomy management, metadata management, content tagging, semantic technology projects, deep learning or graph databases.

Why Mondeca ?

Making decision Person looking at a checklist

Modular

Made from loosely coupled components with specific/dedicated functions

Scalable

Supports horizontal/vertical scaling – deploy in a high-availability environment to support heavy workloads and throughput

Data model driven

Designed to support any type of business data, in any character set or language

Open

Highly configurable and parameterizable

Collaboration

Browser-based software designed for collaboration with fine access permissions

User experience

Capable of exposing the same value in both its UIs and APIs

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