SenseMaking Technologies Corporation, a spin-out of Temple Universityâs QED Proof of Concept Business Incubation Program, is developing a suite of software products that support Applied Behavior Analysis (ABA) based training and therapy, especially towards the use of ABA therapy to treat those with autism. The technology will be used by program supervisors, certified analysts, non-certified therapists, educational assistants and parents. The firm plans to market the software for traditional software sales distribution, in a Software as a Service (SaaS) package, as a fully serviced integrated model and as licensed technology to ABA-focused organizations. The software will be hosted and available to consumers via the internet, eliminating the need for software to be installed at the customer site and would be similar to online tutoring services for teachers. By facilitating a cost-effective way to apply ABA techniques to treat autism, the technology will ultimately benefit the children with autism, while reducing the financial burden on families and other providers for the affected children. Although the initial focus of the technology will be on the autism marketplace, additional markets and revenue from ABA-therapy products to treat issues such as drug and alcohol abuse and non ABA-therapy products, such as improved learning instruction to enhance studentsâ long-term retention of knowledge will be available. Autism affects more than 1% of the worldâs population. Applied Behavior Analysis (ABA) is the gold standard in treating autism. Children with autism who undergo early treatment by a team of certified and non-certified instructors, including parents and educational assistants, have a nearly 50% chance of improving their IQs and developmental progress enough to allow them to mainstream into regular education classrooms. Unfortunately, without this early intervention there is almost no chance of advancement and the process complexity barriers experienced by instructors, coupled with the burdens of data collection and high costs (60K/child/year) limit its availability. SenseMakingâs cloud-based, mobile technology uses expert knowledge embedded in software agents and data mining to guide instructors using speech recognition, overcoming instructor expertise and process complexity barriers and eliminating data collection burdens to ensure better, faster, less-costly learning and instructor tr
