ARIA AI
Not a chatbot with canned responses. An autonomous agent with real tool use, built specifically for insurance workflows, with full audit trails and PII protection.
The insurance industry has been promised AI for years. What it has received, mostly, are glorified search bars and chatbots that can answer FAQ-level questions but break down the moment you ask something that requires actual data access. "What's the renewal date for the Johnson account?" Sorry, I can't access your systems. "Draft a renewal outreach email for my top 20 accounts." Sorry, I don't have that capability. The gap between the AI that vendors market and the AI that agencies actually use is enormous.
ARIA is different because it is not a bolted-on chatbot. It is an AI insurance assistant built directly into the PrizMova platform with real tool use — the ability to query your client database, read policy details, analyze claims history, access carrier information, draft communications, extract data from documents, and execute multi-step workflows. When you ask ARIA a question, it does not guess or hallucinate. It looks up the answer in your actual data, shows you the source, and lets you act on it immediately.
The technical distinction that makes ARIA useful where other insurance AI tools fail is tool use. ARIA has access to a defined set of tools — functions that can query the PrizMova database, perform calculations, generate documents, send communications, and update records. When you ask "Which of my commercial accounts have a loss ratio above 60%?", ARIA does not try to generate an answer from its training data. It calls the policy and claims APIs, calculates loss ratios from actual premium and incurred loss figures, and returns a structured table of results with links to each account.
This tool-use architecture means ARIA's responses are grounded in your real data, not statistical predictions about what the answer might be. It can pull a client's full coverage summary, identify which policies are expiring in the next 30 days, compare premium trends across renewal cycles, and surface accounts where coverage limits have not been adjusted despite revenue growth. Each of these tasks would take a human 10 to 30 minutes of clicking through screens and cross-referencing data. ARIA completes them in seconds.
Ask ARIA about any client and get an instant briefing: active policies, premium totals, claims history, outstanding tasks, and recent communications. Go deeper with natural language questions like "Does the Martinez account have cyber liability?" or "What was the premium change on the Anderson renewal?" ARIA queries the live database and returns precise answers with policy numbers, effective dates, and coverage details.
ARIA continuously evaluates your book of business for churn risk signals: premium increases above market trends, claims frequency spikes, declined renewals at other carriers, reduced communication engagement, and late payments. Each at-risk account receives a churn score from 1 to 100, and ARIA generates specific retention recommendations — whether that means a coverage review call, a remarketing exercise, or a proactive rate comparison. Agencies using ARIA's churn prediction retain 12% more accounts than those relying on renewal-time intuition alone.
ARIA drafts context-aware insurance emails using live client data. Renewal outreach includes the specific policies expiring, current premiums, and any coverage changes to discuss. Welcome emails reference the policies just bound and the assigned CSR. Claims status updates include the current workflow stage and next steps. Every draft is pre-filled with real data — not generic templates — and presented for human review before sending. Your team edits and approves; ARIA handles the heavy lifting of composition and data gathering.
Insurance agencies process thousands of documents annually: dec pages, applications, ACORD forms, loss runs, certificates of insurance, endorsements, and carrier correspondence. Manually reading these documents and entering data into the management system is one of the most time-consuming and error-prone tasks in any agency. ARIA's document extraction capability uses vision and language models to read uploaded documents, identify the relevant fields, and extract structured data.
Upload a dec page, and ARIA extracts the named insured, policy number, carrier, effective and expiration dates, coverage lines, limits, deductibles, and premium amounts. Upload a loss run, and ARIA parses each claim with date of loss, description, incurred amount, and status. Upload an ACORD 125, and ARIA populates the client profile with business classification, revenue, employee count, and requested coverages. Extracted data is presented for human confirmation before being committed to the database — ARIA accelerates the work, but a human always approves the result.
One of ARIA's most powerful capabilities is the ability to work while your agency sleeps. Overnight autonomous operations are scheduled tasks that ARIA executes during off-hours and summarizes in a morning briefing delivered before your team arrives. These operations include scanning the book for policies expiring in the next 90 days and creating renewal tasks, identifying claims that have been stagnant for more than 14 days and flagging them for follow-up, running churn prediction models against the full client database, and checking for coverage gaps in accounts that have had recent revenue or headcount changes.
The morning briefing is a structured report that tells your team exactly what happened overnight and what needs attention today. "23 renewal tasks created. 4 stagnant claims flagged. 7 accounts identified with elevated churn risk. 2 coverage gaps detected." Each item links directly to the relevant record in PrizMova, so the team can act immediately without additional research. The result is an agency that operates 24 hours a day even though your staff works 8.
ARIA is not a single monolithic model. It is an orchestration layer that delegates tasks to six specialized sub-agents, each trained and optimized for a specific domain within insurance operations:
When you ask ARIA a question, the orchestration layer routes it to the right sub-agent. Complex requests that span multiple domains are decomposed and distributed across sub-agents, with results assembled into a single coherent response.
Insurance data includes Social Security numbers, medical records, and financial details. ARIA is built with PII protection as a foundational requirement. Before any data is sent to the language model, PrizMova's scrubbing layer redacts sensitive fields. The model receives anonymized data, generates its response, and PrizMova re-inserts the original values on the way back. The language model never sees raw PII.
Every interaction with ARIA is logged in an immutable audit trail: the question asked, the tools invoked, the data accessed, the response generated, and the user who initiated the request. For agencies subject to regulatory examinations or E&O audits, this trail provides complete transparency into what the AI insurance assistant did, why it did it, and who approved the result. There is no black box. Every decision ARIA makes can be reviewed, explained, and defended.
Related Features
ARIA classifies incoming emails, scores priority, extracts action items, and drafts replies — turning your inbox from a source of stress into a managed workflow.
ARIA's overnight operations power the renewal engine — detecting upcoming expirations, preparing remarketing packages, and generating client outreach automatically.
The Compliance and Audit sub-agent monitors regulatory deadlines, validates surplus lines filing requirements, and ensures every workflow meets state-specific rules.