Agentiv X offers a neuro‑symbolic AI platform that automates commercial insurance placement by converting client documents into structured risk profiles, comparing insurer terms, and generating explainable, market‑ready recommendations. Brokers can refine these recommendations in real time and use a dedicated claims module to assess submissions and flag settlement triggers, reducing manual effort, errors, and E&O risk.
Funding
Funding not disclosed
Founders
Product
Problem
Commercial insurance brokers face lengthy, manual submission processes, ambiguous policy language, and repetitive data entry, which slow down placement of complex risks and increase the likelihood of errors and omissions. These inefficiencies make it difficult to demonstrate value beyond price and consume time that could be spent on client advisory.
Solution
Agentiv‑x addresses these challenges with a neuro‑symbolic AI platform that combines proprietary decision‑science models, developed with the University of Manchester, and agentic AI to automate and clarify the placement workflow. Brokers input cover requirements and upload documentation, after which the system translates business needs into structured risk representations and generates market‑ready presentations. The platform then compares insurer terms, highlights trade‑offs, and produces explainable recommendations that can be refined in real time by the broker. A dedicated claims module assists brokers in evaluating claim submissions, identifying settlement triggers, and communicating findings to insurers, thereby improving the overall claims experience. By delivering fast, transparent, and justifiable advice, Agentiv‑x helps brokers close deals more efficiently while reducing operational friction and E&O exposure.
Target Audience
Agentiv‑x is designed for commercial insurance brokers and brokerage firms that place complex risks and manage claims, as well as underwriting teams seeking faster, more accurate risk assessments.
Features
- Neuro‑symbolic AI engine that converts unstructured client documents into structured risk profiles for automated analysis
- Decision‑science models that evaluate and rank insurer terms, presenting clear trade‑off visualizations for broker review
- Real‑time expert control interface allowing brokers to adjust recommendations and maintain professional judgment
- Claims assessment module that flags settlement triggers and streamlines communication with insurers
- Explainable AI outputs that provide traceable reasoning for each recommendation, supporting regulatory compliance and client trust
- Integration-ready workflow that reduces manual re‑keying and consolidates data entry into a single submission step