Our History

In 1986, when Human Inference was established, data was used in a wide range of systems, and data quality was considered to be a minor issue. Human Inference realized that the quality of data highly influences the results of analyses, such as fraud detection by insurance companies. Moreover, Human Inference recognized the value of data for all business processes, a fact quite underestimated at that time. In addition, we discovered that to reach the desired results, mathematical logic is not sufficient. The knowledge about the language and culture of a country was necessary as well. Human Inference proved to be right, since today the largest companies of the world are using our knowledge-based software to improve the quality of their data.

The scope of data quality has changed. Today the value of data is recognized on a broad scale and is restricted not only to name and address data. In addition, data quality has become more and more of a business issue than merely an IT issue. Data quality is a critical success factor for large CRM, ERP or BI projects that require solid investments. Data is the core of the information system of any company, influencing all company processes. Therefore, defective data will have a negative influence on these processes and consequently, the business results.
Human Inference anticipated this change and defined a clear strategy to meet current market requirements.