Insur.Cap revolutionizes risk management with algorithmically driven augmented underwriting, leveraging computer vision AI & LAM for image-caption fusion. The orchestration processes proactively predict risks and facilitate accessible comprehensive coverage, overcoming traditional insurance limitations. Insur.Cap optimizes “Assistant-LAM” communication via a chatbot-based UI conversation flow interface. Looking from the perspective of Knowledge augmentation, we have a “data point issue” while the PROBLEM is that the incumbent does not employ DATA {as a tool, knowledge…} driven decision making, (to help processes make better-agile decisions by bringing in {data} more {usable} information to the risk underwriting, as a new data set - data points.) -Traditional insurance is too complex. -Definitely there is still a gap between the needs (mainly on-demand or custom-target needs). -Last but not least, proactive prevention might play a crucial role - if we emphasize prevention as a service proposition. Multimodal orchestration is our magic weapon! We develop a seamless-simple customer UuserInterface that delivers more/new datasets and data points for augmenting underwriting. Through the {Large Action/Agentic Model} we empower algorithmically driven architecture and orchestrate the process flow decision tree. Let me show you how we do that! First, with a simple User Interface we ingest the image and from the AI receive the CAPTION - this means the context from the image. That is the first pillar of the AI_assitant Then the core pillar of AI_ “Agent - Action” capability is to compute the: proper insurance product line based on the item from the caption execute premium calculation logic offer personalized coverage and finally issue the insurance policy All of that is our AI assistant Chatbot-based user interface; a SaaS (IaaS) API-driven technology stack.