AI agents, built for P&C

Invisible AI. Visible results.

LLMira Suite turns insurance product documents into live, auditable products.

See how it works Request a demo

Our programming language is English

No Code. Just business language.

Say what your product should do, in your own business words. AI agents build it, and your people approve every step.

You say

“Give a 10% discount to customers who insure both their car and their home.”

Plain business language, the way you already talk about your products. For example only.

Agents build

The product takes shape

AI agents turn your words and your documents into rules, rates and forms, and show where each one came from.

You approve

Your product runs

Your analysts review and approve. The approved product runs live policies, with every rule traceable.

Built for the whole table

Executives

Launch faster. Spend less.

Move a product from approved documents to running policy in a fraction of the time legacy systems take. Keep every decision traceable for regulators and the board.

For executives →

A product and actuarial team gathered around a table while a colleague presents analysis charts on a wall screen.

Business leaders

Own your products again

Change a rate, a rule or a form without a ticket to a specialist. See exactly which document section every rule came from.

For business leaders →

Architecture diagram: user interfaces, an API gateway, core services, data and analytics, and external integrations.

Technology

Open, modern, built to integrate

Open-source building blocks, an API-first design, open data and AI providers you can swap. Runs on the database, cloud and operating system you already use.

For technology →

The problem, in three numbers

Why insurance is slow to change

36–72 weeks

To launch a single product on a legacy core system

Source: Celent, 2023

$1M–$3.5M

Per state, to bring that product to market

Source: Celent, 2023

96.9%

2024 industry combined ratio, leaving about a 3.1% underwriting margin

Source: NAIC, 2024

Every point of speed and cost matters when the margin is this thin.

The LLMira Insurance Suite

One suite, built like a fleet

One platform that reads your product documents, builds the product and runs it. Each orchestrator does one job well.

See every product →

LLMira

Insurance Suite

LLMira

Semantic Orchestrator

Available

Reads your product documents and builds the product definition, with a person approving every phase.

LLMira

Policy Orchestrator

Available

Runs that product for quoting, rating, binding and renewals, on the version each policy was written on.

LLMira

SelfService Orchestrator

Early access

Lets insureds and agents create and manage policies on the same engine.

LLMira

Workflow Orchestrator

Coming soon

Routes work between people and AI agents with limits, approvals and service levels.

How it works

From documents to running policy

Before an insurer can sell a product, it submits its rates, rules and forms to the state regulator. That package is called a filing. LLMira Suite reads it and builds the product from it.

01
Upload your product documents
A rate manual, a rule change from your rating bureau (an ISO circular) or your own product documents.
02
Review and approve
The AI agent drafts each phase and checks its own work; a person approves before it moves on.
03
Run live policies
The approved product definition drives the forms, the rating and the audit trail.

Why it is different

What makes it different

Every rule has a reason

Each rule links back to the document section that required it. Answer "where does this come from?" without calling a senior analyst.

Screenshot: a rule traced back to its source section

Guided phases

You define the phases, from document index to final product, with a person approving every gate.

People approve, AI agents draft

AI agents do the reading and drafting; analysts keep the decisions. Rejection notes feed the next run.

Policies keep their rules

A policy always runs on the version it was written on. Production definitions are protected at the database.

Change rules, not software

Rules are stored with the product and tested one rule at a time. A rule change is a product update.

One definition, every screen

Underwriter and client screens are generated from the product. Change a rule and every form follows.

Blocks, not towers

Inheritance is used where it helps, not everywhere. Auto and Homeowners snap together as blocks into one product, and each version carries only the rules that changed. See how →

Any channel, any AI

A typed API serves broker portals and embedded channels. Swap the AI provider with configuration.

Azure OpenAI
OpenAI
Anthropic Claude
DeepSeek
Kimi
Gemma

AI providers

Azure OpenAI, Azure AI Foundry and Anthropic Claude, by configuration.

A worked example (illustrative)

One rule change, two live versions

A rating bureau (ISO) publishes a change to Personal Auto rating in Massachusetts, effective 1 March 2026. Upload the PDF, approve the extracted factors, and the new product version goes live for new business while renewals stay on the old one. No developer writes business logic.

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