ASAP Research Automation: FLTMC Finalist
ASAP Research Automation is one of the finalists for the From Lab to Market Challenge.
We spoke with Nele Blum, Johann Engster (Co-Founders), and Maik Stille (Advisor) about ASAP Research Automation, one of the finalists in the From Lab to Market Challenge.
CHEManager: What is your technology, and what makes it work?
Nele Blum, Johan Engster, & Maik Stille: At ASAP we developed a prompt-based visual foundation model for image analysis. The user highlights the structure of interest in a few examples, and the model instantly detects it across entire datasets without retraining. A built-in human-in-the-loop feature lets experts correct errors in real-time, while the system learns and provides smart annotation suggestions instantly, drastically accelerating workflows.
What problem does your technology solve, and what is the business potential?
N. Blum, J. Engster, & M. Stille: Researchers spend months analyzing images, delaying drug development and tying up skilled personnel in repetitive work. ASAP cuts conventional AI analysis from weeks to hours. The beachhead market targets research institutes and CROs, with an estimated SOM of €3.5M ARR. Our SAM (€550M) covers organizations that steer (pre)-clinical studies. The problem extends into further applications, where similar image analysis bottlenecks exist with a TAM of €3.5B, in segments growing at up to 25% annually.
What's the next milestone your team is working towards?
N. Blum, J. Engster, & M. Stille: The next milestone is launching a public beta of our platform, paired with pilot studies alongside academic institutions and CRO partners. In parallel, we are pursuing strategic partnerships with pharmaceutical companies and seeking a minimum of €500,000 in investment to accelerate further development and market expansion. Our ultimate aspiration is for ASAP to become the global gold standard and the leading AI vision foundation model for scientific and industrial image analysis worldwide.
