About

About Legind Technologies

The early years leading to LT as a university research spinoff
LT was founded in 1993 under the name Adaptive Information Systems A/S (AIS) by Henrik Legind
Larsen, a university professor in computer science, as a spin-off of his research in the European
Strategic Programme in Information Technology (ESPRIT) in the project Knowledge-based user-
friendly systems for the utilization of information bases (KIWI).

Legind Larsen developed in collaboration with professor R.R. Yager, Machine Intelligence Institute,
US, a Fuzzy Term Net model for flexible information retrieval that later has been applied successfully
in several search engines.

The first prototype was developed in 1993 by LT (AIS) with support from the Danish Government of
Industry and Commerce. It represented first fuzzy search engine in the world, and first flexible search
engine for e-commerce. It was publicly presented the same year at IJCAI’93 (International Joint
Conference of Artificial Intelligence) in Chambery, France, in an arrangement in collaboration with
the AI laboratory of University of Savoie, France.

This provided a background for research activities (at that time at Roskilde University), including
projects funded by the Danish Natural Science Research Council in the area of Intelligent Information
Access Systems over four years, and founding the biennial conference series FQAS (Flexible Query
Answering Systems).

Example of larger LT projects

Larger LT projects for, and with, clients have been done through LT subsidiaries created for the
purpose.
In 1999 – 2000, LT developed, organized in a subsidiary (Adaptive Computer Systems ApS), a Fuzzy
Term Net based search engine for Denmark’s at that time largest internet search portal, Jubii. With
this search engine, Jubii was sold in 2000 to Lycos Europe.

In 2004 – 2008, LT developed, also organized in a subsidiary (XSIS Aps), a Fuzzy Term Net based
investigative search engine for, and in collaboration with, the Danish National Center of Investigation.
The subsidiary received seed investment from NOVI Innovation A/S. The Danish IT entrepreneur,
and now former member of the European Parliament, Christian F. Rovsing, became chairman of the
board of XSIS. Christian F. Rovsing was also member of the Group of Personalities in the field of
Security Research who prepared the report Research for a Secure Europe, European Commission,
2004 that provided a basis for the Securtiy Research theme of the 7 th Framework programme.

This provided background for establishment in 2010 of the center ‘Computational Intelligence and
Security Lab’ (CIS Lab) at the Department of Electronic Systems at Aalborg University’s campus in
the city of Esbjerg and participation 2010 2013 in the European project VIRTUOSO (Versatile
Information Toolkit for end-users oriented open-sources exploitation) in the Security Research theme
of the 7 th Framework programme.

Following the VIRTUOSO project, the university
and LT, further participated 2013–2015 in the
European project ePOOLICE (early Pursuit
against Organised crime using envirOnmental
scanning, the Law and IntelligenCE systems),
also in the Security Research theme of the 7 th
Framework programme.
The ePOOLICE project developed proof of
concept of a solution for scanning the
environment for open data (big data) for
predicting, and detecting emerging, organized
crime threats.
A publication spinoff from the latter project is the
book: Henrik Legind Larsen et al. (Eds.), Using
Open Data to Detect Organized Crime Threats:
Factors Driving Future Crime, Springer, 2017

Legind Technologies - Book

From project oriented to product oriented

From 2018, LT has taken a more product and service oriented direction to the market. In this, we take
advantage of the learnings from the proof-of- concept and the end-user involvement in the above-
mentioned European projects, as well as other research results with interesting product and market
potentials in the Big Data and Smart Cities area. Our ambition is now to provide to our clients close to
real-time exploitation of big data—i.e., datasets or streams that are large, fast and/or diverse—for two
categories of applications: strategic and investigative. The strategic is for strategic analysts and
decision makers that need awareness of the current situation, trends and likely and possible future
developments of interest for their business. The investigative is for investigators and researchers
exploring a case or a problem to “connect the dots”, detect patterns, etc., with the aim of solving the
case or the problem. In this, we bring our experience from law enforcement applications (for strategic
analysis and investigation) into solutions for the broader business market for Big Data and Smart
Cities.