AI at the Heart of Our Platform
A platform built from the ground up with AI and not bolted on.
Agiliux AI-Native Solution is a future-ready insurance platform built with multi-agent automation, predictive analytics, and generative AI capabilities at its core. It enables brokers and MGAs to modernise operations, enhance decision-making, and scale digital insurance processes end-to-end. This AI-native architecture is especially valuable for organisations such as direct insurance brokers, reinsurance brokers, and insurance companies modernising operations and reducing reliance on manual workflows.
Multi-Agent AI Workflows
Virtual agents handle complex tasks end-to-end. For example, an agent could engage a broker via chat, collect risk details, extract information from submissions, run pricing models, check compliance rules and escalate or bind automatically. These agents collaborate within the system and orchestrate tasks without requiring manual handovers. These multi-agent workflows are part of the broader Intelligence Automation framework within Agiliux, where structured data and agent logic execute multi-step processes reliably and securely.
Generative AI for Content
Produce draft proposals, policy summaries, renewal letters or client emails within Agiliux. Use natural-language generation to create client-facing documents or internal analysis, reducing the time spent on manual drafting. For organisations requiring tailored document generation or custom workflow outputs, Agiliux Bespoke services help configure AI capabilities to match your unique operational needs.
Generative AI for Content
Produce draft proposals, policy summaries, renewal letters or client emails within Agiliux. Use natural-language generation to create client-facing documents or internal analysis, reducing the time spent on manual drafting. For organisations requiring tailored document generation or custom workflow outputs, Agiliux Bespoke services help configure AI capabilities to match your unique operational needs.
Advanced Predictive Analytics
Machine-learning models continuously learn from your data to predict renewal risk, spot cross-sell opportunities and suggest underwriting changes. Forecasting agents identify emerging risk trends and recommend strategic actions to give you a proactive edge. These predictive insights create value when mapped to structured operational processes captured in your Modern System of Record, ensuring predictions translate into actions you can execute consistently.
Agiliux is built as an AI native platform with generative intelligence, agentic workflows and predictive insights working inside the core system. It learns from your data and automates processes to improve speed and decision making. We are defining the category of AI-Assisted Broking.
Continuous Innovation
The AI architecture is modular and updatable. As new AI techniques such as reinforcement learning or computer-vision for claims images emerge, they can be added to the platform without disruption. The system’s infrastructure ensures that AI modules grow more capable over time and aligned with your business.
Continuous Innovation
The AI architecture is modular and updatable. As new AI techniques such as reinforcement learning or computer-vision for claims images emerge, they can be added to the platform without disruption. The system’s infrastructure ensures that AI modules grow more capable over time and aligned with your business.
Frequently Asked Questions
What is the difference between an "AI-Native" platform and one that just uses AI?
An AI-native platform includes artificial intelligence as its foundational layer, not just as a feature. Every workflow, from the first interaction with a submission to the final claims settlement, is designed to be powered by embedded AI agents. This is more reliable and secure than “bolted-on” AI, which often relies on fragile integrations and disjointed data sets.
Why is an "API-First" architecture essential for future-proofing?
An API-first architecture ensures that the platform is not a “closed ecosystem.” It allows the core system of record to connect seamlessly with insurer portals, third-party data providers, and future AI tools. This ensures that as the market evolves, for example, with Lloyd’s Blueprint Two, the platform can adapt by simply connecting to new services rather than being replaced.
How does the "Model Context Protocol (MCP)" benefit my brokerage?
How does AI-native architecture support "Embedded Insurance" models?
Embedded insurance requires the ability to quote and issue policies in milliseconds within a partner’s website or app. An AI-native, API-first core is designed for this “real-time” environment, allowing brokers and MGAs to distribute products through non-insurance partners (like travel sites or logistics firms) with zero manual intervention.
Does an AI-native platform improve the quality of data for reinsurers?
Yes. Reinsurers and capacity providers increasingly value “data sophistication.” An AI-native platform captures and validates data at the point of bind, ensuring that the information passed to reinsurers is high-quality and structured. This can lead to more favourable capacity arrangements and better-priced reinsurance treaties.
How does a microservices architecture prevent system downtime?
In traditional “monolithic” systems, a bug in one part of the platform can crash the whole thing. In a microservices architecture, different functions (like claims, quoting, and accounting) run independently. If one service needs an update, the others continue to function, ensuring much higher system availability and resilience for the business.
Why this matters?
Because AI is not just an add-on, it is part of the Agiliux DNA and you avoid the complexity of managing separate tools, integrations or scripts. The platform becomes smarter, more predictive and more helpful with every transaction, every renewal and every client interaction.