Digital Decision Making upgrades corporate IT with Artificial Intelligence (AI), providing enterprises with a unique competitive advantage.
Success factors include:

Hybrid AI – INFORM technology integrates Operations Research and Artificial Intelligence, including Fuzzy Logic and Machine Learning. Leveraging computer algorithms with human expertise yields results significantly superior to both, traditional management and purely data driven algorithms.

Agile Optimization – Digital Decision Making empowers a new management strategy based on smart, rapid, and interactive decision making. Agile Optimization is particularly valuable where complex operations face many ad-hoc changes, volatility, disruptions, unpredictability, and time pressure.

Industry Experience – Our more than 1,000 business analysts, data scientists and software engineers proudly support turn-key solutions for more than 1,000 current customers in over 40 countries. Industry sectors and business processes include Aviation, Automotive, Banking & Insurance, Fraud Prevention & AML, IBP, Inventory & Supply Chain, Logistics, Manufacturing, Materials Handling, Production, Transportation, Workforce Management, and more.

INFORM Campus, Headquarters in Aachen, Germany

Corporate Growth


Facts & Figures

  • Software for Digital Decision Making based on OR and AI, including Fuzzy Logic and Machine Learning
  • For planning and real-time control of complex, dynamic business operations, including automated data driven decision making where appropriate
  • Turn-key solutions, with long-term 24/7 support if desired, for a multitude of business sectors and types of operations
  • More than 1,000 staff including more than 30 nationalities
  • Established in 1969, since 1985 more than 30 years of double-digit growth
  • Revenues 2022: 115,3 Mio. EUR
  • Profits consistently re-invested into substantial R&D - i.e. incremental system innovations as well as visionary new products
  • Internal ownership – founder, directors, long-term employees
  • Corporate vision: sustainability and long-term business partner relationships



Worldwide Client References

With our partner offices worldwide, we are represented on almost all continents. More than 1,000 current customers in more than 40 countries run INFORM software systems. They are supported 24/7 from Aachen, Germany, and several partner locations in Atlanta GA, USA / Sydney, Australia / Santiago de Chile, Chile / Sao Paulo, Brazil / Lisboa, Portugal and Singapore.



We build upon a long history of expertise in many areas of AI, from general problem solving and decision making over knowledge representation, automated reasoning and deductive intelligence  to machine learning and intelligent control of autonomous systems. By combining techniques from these areas in a hybrid approach, our software systems can perform core functions traditionally associated with human intelligence: decision making and learning.

•    Expert knowledge about business processes and behavioral patterns as well as planning objectives and constraints is cast into digital decision models.  AI techniques (e.g. constraint programming) together with OR algorithms (e.g. mathematical optimization) can explore many millions of alternative decision options extremely fast, hence producing truly optimized results.

•    Machine learning techniques are used to automatically discover new knowledge by mining large data sets for patterns. Predictive models make use of these patterns to classify events and make forecasts about volumes, times and durations, thus providing improved input for the decision models.

Operations Research

Operations Research

Operations Research (OR) applies advanced analytical methods and algorithms to help make better decisions - a uniquely powerful approach to decision making.

Using techniques such as mathematical modeling and optimization, OR leads you to the very best choices. The power of OR algorithms comes from their ability to quickly compare an incredibly large number of feasible options to find solutions that are often overlooked by mere human intuition.

By combining OR with machine learning, we can mine data to gain insights and make forecasts that fuel our OR optimization algorithms.

OR puts data to its most valuable use: Sophisticated algorithms leverage today's computing power to suggest optimized options for decision makers.

Fuzzy Logic

Fuzzy Logic

“All traditional logic habitually assumes that precise symbols are being employed. It is therefore not applicable to this terrestrial life but only to an imagined celestial existence.” [Bertrand Russell]

Building upon the scientific work of our company's founder H.J. Zimmermann, recipient of the prestigious IEEE Fuzzy Systems Pioneer Award, we apply Fuzzy Logic for solving the fundamental challenge of deriving correct decisions from imprecise or uncertain input.

In traditional bivalent logic, any statement is either true or false, without a possibility in between.  Fuzzy logic, in contrast, allows intermediate values, making it suitable for representing linguistic information and expert knowledge. Decisions are taken in a manner similar to that used by humans.

Everybody regularly makes fuzzy decisions, for example when parking their car.  Instead of measuring the parking space exactly, you make a rough guess on all sides as to whether the car fits in the gap.

Fuzzy Logic lets us transfer our human ability of drawing the right conclusions from imprecise information into software.



Data is the oil that powers the digital economy of the 21st century. Like crude oil, it must be refined to fuel the algorithm engines that can turn it into competitive advantage.

Machine learning is about refining data. It blends concepts and techniques from different fields - such as mathematics, statistics, and computer science - to look for structural patterns in data to find valuable connections and insights and make reliable predictions.

Machine learning is a multi-step process, from data engineering (harmonization, transformation, and enrichment) and feature selection over the training and evaluation of predictive models to the final execution and monitoring of models in challenging real time environments.

The focus always is on model accuracy as well as on comprehensibility, with a preference for models that are understandable and produce justifiable results.



Agile Optimization is a management strategy for dealing with complexity and uncertainty in the planning and control of business processes. By responding quickly to ad-hoc changes and disruptions in complex business environments, it helps to increase a company's efficiency, agility, and resilience.

More traditional management strategies, such as Lean Management, sophisticated planning, or ad-hoc improvisation, are ill suited to cope with the challenges of today's VUCA world: volatility, unpredictability, complexity, ambiguity, and ever increasing time pressure. By providing smart, rapid, and interactive computer assistance, Agile Optimization is the strategy of choice to elevate decision making for many dynamic business operations.

Executive Board

Dr. Andreas Meyer Co-CEO
Dr. Jörg Herbers Co-CEO
Peter Frerichs Co-CEO

Dr. Torsten Inkmann SVP Manufacturing Logistics Division
Dr.-Ing. Eva Savelsberg SVP Terminal & Distribution Center Logistics
Thomas Bergmans SVP Logistics Division
Uschi Schulte Sasse SVP Aviation Division
Dr. Jörg Herbers SVP Workforce Management
Roy Prayikulam SVP Risk & Fraud Division
Andreas Gladis SVP Production Division
Jens Siebertz SVP DataLab
Andreas Falter SVP Inventory & Supply Chain Division
Stefan Witwicki SVP Inventory & Supply Chain Division

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