Context: Search-Based Software Testing (SBST), and the wider area of Search-Based Software Engineering (SBSE), is the application of optimization algorithms to problems in software testing, and software engineering, respectively. New algorithms, methods, and tools are being developed and validated on benchmark problems. In previous work, we have also implemented and evaluated Interactive Search-Based Software Testing (ISBST) tool prototypes, with a goal to successfully transfer the technique to industry. Objective: While SBST and SBSE solutions are often validated on benchmark problems, there is a need to validate them in an operational setting, and to assess their performance in practice. The present paper discusses the development and deployment of SBST tools for use in industry, and reflects on the transfer of these techniques to industry. Method: In addition to previous work discussing the development and validation of an ISBST prototype, a new version of the prototype ISBST system was evaluated in the laboratory and in industry. This evaluation is based on an industrial System under Test (SUT) and was carried out with industrial practitioners. The Technology Transfer Model is used as a framework to describe the progression of the development and evaluation of the ISBST system, as it progresses through the first five of its seven steps. Results: The paper presents a synthesis of previous work developing and evaluating the ISBST prototype, as well as presenting an evaluation, in both academia and industry, of that prototype's latest version. In addition to the evaluation, the paper also discusses the lessons learned from this transfer. Conclusions: This paper presents an overview of the development and deployment of the ISBST system in an industrial setting, using the framework of the Technology Transfer Model. We conclude that the ISBST system is capable of evolving useful test cases for that setting, though improvements in the means the system uses to communicate that information to the user are still required. In addition, a set of lessons learned from the project are listed and discussed. Our objective is to help other researchers that wish to validate search-based systems in industry, and provide more information about the benefits and drawbacks of these systems.