AI INSURANCE PLATFORM

AI insurance built on your policies, your rate tables, your reinsurance rules.

Carriers, MGAs, and brokers ship underwriting AI, claims AI, fraud detection, and insurance AI chatbots on Clarista — grounded in your data, governed by default, integrated with Guidewire, Duck Creek, Majesco, and your legacy core. NAIC-aligned. SOC 2 + HIPAA-ready.

What "AI insurance" means in 2026 — and what most vendors get wrong

Insurance AI software has flooded the market in the last 18 months. Most of it is a generic LLM wrapped around a generic chatbot — pointed at a carrier's PDF policy library and shipped as "AI insurance." It hallucinates on coverage questions, ignores state-by-state rules, and gets jurisdictional exclusions wrong. The result is a regulatory and reputational risk dressed up as innovation.

Clarista takes a different approach. The AI insurance applications you build on the platform are grounded in your data — policy documents, rate tables, coverage rules, loss runs, reinsurance treaties, prior claim outcomes. Every answer cites its source. Every action goes through your existing approval workflow. Every output is auditable.

Carriers using Clarista typically ship their first production AI app — a FNOL triage agent or an underwriting copilot — in 4-8 weeks, on top of their existing Guidewire, Duck Creek, or Majesco stack. No rip-and-replace.

What teams build on Clarista for AI insurance

Underwriting copilot

Submission triage, missing-info detection, exposure analysis, prior-loss summarization, automated quote generation for SMB and middle-market risks. Underwriters spend more time on judgment calls and less on data assembly.

FNOL triage and claims AI

First Notice of Loss reads incoming claims (text, voice transcript, images), classifies severity, routes to the right adjuster, and surfaces fraud signals against your prior claims database. Reduces cycle time on routine claims by 40-60%.

Insurance AI chatbots for customer service

Policy-grounded insurance AI chatbots answer coverage questions, status checks, billing queries, and routine endorsements — citing the specific policy clause that supports each answer. Hands off to licensed agents on regulated questions. Available 24/7 across web, mobile, and IVR.

Fraud detection and SIU support

Pattern detection across claim narratives, provider networks, and historical fraud cases. Flags suspicious claims for SIU review with explanation of which signals triggered the flag. Auditable model decisions for regulatory examiners.

Broker / producer enablement

Internal-facing AI for brokers: appetite checks, market submissions, follow-up tracking, commission reconciliation. Surfaces best-fit markets for a risk based on prior placement history.

Reinsurance treaty analysis

Reads complex treaty wordings, surfaces coverage gaps, models attachment-point scenarios. Used by cedents and reinsurers for treaty renewal preparation and dispute resolution.

Insurance AI chatbots — done right

"Insurance AI chatbot" is the search every carrier's CX team has typed at some point. The market is full of generic bot platforms (Drift, Intercom, Ada) bolted onto a generic LLM with no understanding of insurance regulation. That stack hallucinates. It gives wrong coverage advice. It misses state-specific exclusions. It's a regulatory accident waiting to be filed.

Insurance AI chatbots built on Clarista are different in four ways. First, they're grounded in your actual policy library — every answer cites the specific clause, schedule, or endorsement that supports it. Second, they respect jurisdictional rules — a Florida claim handler sees Florida-specific guidance, not generic boilerplate. Third, they escalate intelligently — regulated questions (coverage determinations, claim adjudication, policy advice) route to licensed humans. Fourth, every conversation is logged, reviewable, and exportable for compliance.

Deployed as a customer-facing assistant, an agent-facing copilot, or both. Plugs into your existing CCaaS stack (Genesys, NICE, Five9, Talkdesk) and your CRM (Salesforce Insurance Cloud, MS Dynamics, HubSpot).

How AI insurance on Clarista compares

Versus generic SaaS chatbots, AI development agencies, and in-house builds.

FactorGeneric AI / bot SaaSCustom build (agency)Clarista platform
Grounded in your policiesNo (generic LLM)YesYes — natively
State / jurisdictional rulesGenericCustom-codedConfigurable
Guidewire / Duck Creek / MajescoLimited connectorsCustom integrationNative connectors
NAIC AI Model Bulletin supportPartialDepends on buildBuilt-in audit + bias monitoring
Time to first production app2-4 weeks (shallow)6-12 months4-8 weeks
Annual cost (regional carrier)$30K-$120K SaaS$400K-$1.5M build$100K-$300K

Who builds AI insurance applications on Clarista

1

Regional carriers (P&C, life, health)

Underwriting + claims + service AI on top of Guidewire / Duck Creek. Smaller IT teams, faster decisions, lower total cost than enterprise SaaS.

2

MGAs & specialty programs

Submission triage and quote generation for niche risk classes. Surfaces appetite fit faster than email-based intake.

3

Brokerages

Producer copilots, client servicing chatbots, renewal analytics. Internal AI without a six-figure SaaS contract per seat.

4

Reinsurers & treaty teams

Treaty analysis, cedent reporting, accumulation modeling. AI applied to the structured + unstructured data that drives renewals.

5

Insurtech and digital MGAs

Greenfield AI-first platforms — quote, bind, service, claim — built on Clarista in months, not years. Faster time-to-market than building from scratch.

6

Self-insured employers + captives

Claims analytics, vendor performance, loss-cost forecasting on your own program data. AI on the program without the cost of the enterprise carrier stack.

Compliance & governance — built for regulated insurance work

The NAIC Model Bulletin on AI (adopted by 25+ states as of 2026), Colorado SB21-169, NY DFS Circular Letter No. 7, and the EU AI Act all classify insurance AI as high-risk. Compliance requires explainability, bias monitoring, human oversight on adverse decisions, and full audit trails. Clarista provides each of these as platform primitives — not bolt-ons.

AI insurance, on your data, governed by default.

20-minute demo for carrier, MGA, and broker leaders. Bring an underwriting workflow, a claims pain point, or a chatbot RFP — we'll show what shipping on Clarista looks like for your stack.

Book a demo →

Frequently asked questions

What is AI insurance software?

AI insurance software applies machine learning and generative AI to insurance workflows — underwriting, claims, customer service, fraud detection, policy admin. Built on Clarista, it's grounded in your policy library, rate tables, and historical data rather than generic public information.

How are insurance AI chatbots different from generic chatbots?

Insurance AI chatbots on Clarista cite policy clauses, respect state-by-state coverage rules, escalate regulated questions to licensed humans, and log every conversation for compliance. Generic chatbots — even well-known ones — hallucinate on coverage questions because they have no grounding in your actual policy data.

Does this replace Guidewire, Duck Creek, or Majesco?

No. Clarista is an AI layer that sits on top of your existing core. We have native connectors for Guidewire ClaimCenter / PolicyCenter / BillingCenter, Duck Creek Policy / Claims, Majesco, Insurity, and Sapiens, plus direct DB access for legacy systems.

Is AI underwriting compliant with the NAIC AI Model Bulletin?

Yes, when configured correctly. Clarista provides the explainability, bias monitoring, human-in-the-loop, and audit trail required by the NAIC bulletin and the 25+ state regulators that have adopted it. We help you design controls that survive examiner review.

How long does deployment take?

First production AI insurance app (underwriting copilot or FNOL triage) typically ships in 4-8 weeks. Insurance AI chatbots for customer service: 3-6 weeks. Full multi-app rollouts (UW + claims + service): 3-6 months. Faster than enterprise SaaS implementations, materially faster than custom builds.

Can we start with one use case and expand?

Yes — that's the recommended path. Most carriers start with either FNOL triage (claims) or submission triage (underwriting), prove ROI in 60-90 days, then expand to adjacent workflows. The platform scales with the program.