Artificial intelligence can understand a question.

But in insurance, understanding the words is only the beginning.

To generate a meaningful answer, an AI system needs to understand the data behind the question, the relationships between different insurance metrics, the way results change over time, and the business logic that gives every number its meaning.

That intelligence does not begin with the AI model.
It begins with the BI foundation behind it.

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Intelligence Starts with Insurance BI

Insurance data is complex by nature.

Claims, premiums, profitability, risk, exposure, brokers, products, policies, and time periods are all connected. A change in one metric can have several possible explanations, depending on the portfolio, the reporting basis, the period being analyzed, and the insurance context surrounding it.

This is why generic access to data is not enough.

InsFocus BI was built specifically for the insurance industry. Its foundation includes a comprehensive insurance data model, hundreds of insurance KPIs, built-in business and actuarial logic, advanced time-based analysis, claims development capabilities, and structured access to trusted insurance data.

This foundation already enables insurers to organize complex data, investigate performance, and make smarter decisions with greater confidence.

InsFocus AI adds a new layer of intelligence to this environment.

It makes the insurance knowledge already built into InsFocus BI easier to access, faster to explore, and more proactive in generating real-time insights.

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A New Way to Work with Insurance BI

Traditional BI gives users powerful dashboards, reports, filters, and drill-down capabilities.

InsFocus AI expands the ways users can interact with those capabilities.

Instead of always starting with a predefined report or manually selecting every field, users can begin with a business question, describe the analysis they need, or ask the AI Agent to investigate an existing report.

The result is a more natural analytical process that connects questions, reports, insights, and deeper investigation within the same BI environment.

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Build Reports Using Natural Language

Not every business user knows exactly which dimensions, measures, or filters are needed to build a report.
They usually know the business question they are trying to answer.
With InsFocus AI, users can describe the analysis they need in their own words.

For example:

Show me claims frequency by commercial product line for the last six months and compare it with the same period last year.

InsFocus AI translates the request into a structured, interactive BI report that can be reviewed, adjusted, filtered, and explored further.

The user does not receive a detached AI-generated answer. The request becomes part of the InsFocus BI environment, where the data remains visible, structured, and ready for continued analysis.

This shortens the distance between a business question and the report needed to investigate it.

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Ask the AI Agent About Any Report

Once a report has been created, the investigation does not need to stop at what is immediately visible on the screen.
Users can ask the InsFocus AI Agent questions directly about the report.

They can ask:

  • What is driving this increase?
  • Which segments contributed most to the change?
  • Is the trend concentrated in a specific region?
  • How does the result compare with the previous period?
  • Which brokers or products require closer attention?

The AI Agent uses the insurance context behind the report to help users understand what changed, where it changed, and which factors may be relevant.

This creates a more continuous analytical experience. Instead of moving between reports, exporting data, or starting a separate investigation, users can continue exploring the subject directly from the report they are already reviewing.

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Generate Smart Insights with the AI Agent

Some of the most important findings are not always immediately visible.

A report may contain an unusual movement, a developing pattern, or a relationship between metrics that deserves attention, even when the user did not specifically ask about it.

The InsFocus AI Agent analyzes the report and generates smart insights based on the data it contains.

It can identify meaningful patterns, anomalies, notable changes, and areas that may require further investigation.

The goal is not simply to describe the chart or repeat the values already displayed. The AI Agent helps interpret what may be significant within the report and brings relevant observations to the user’s attention.

This allows teams to go beyond the questions they already planned to ask and discover signals that may otherwise remain hidden inside a large or complex dataset.

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Continue the Investigation

A useful insight should not be the end of the process.
It should be the beginning of the next question.

When the AI Agent identifies an anomaly or generates an insight, users can continue the investigation through follow-up questions.

They can ask where the change is concentrated, when it began, whether it appears across different products, or what happens when a specific segment is excluded.

For example, after identifying an increase in claims severity, a user could ask:

  • Is the increase related to a specific claim type?
  • Which regions are contributing most to the change?
  • Does the pattern remain when large claims are excluded?
  • When did the movement first become significant?
  • Is claims frequency showing a similar trend?

Each answer can lead naturally into the next stage of the analysis.
This creates a connected flow:

Ask. Build. Discover. Investigate.

Users can begin with the questions they already have, while the AI Agent helps surface the questions the data suggests they should ask next.

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Why the Insurance Context Matters

An AI model may understand the language used in a question.
But a useful insurance answer requires much more.

It requires an understanding of what the relevant KPI represents, which dimensions affect it, how different time bases change the interpretation, and which relationships are meaningful within an insurance business.

The same result can have a very different meaning depending on whether it is viewed by product, broker, underwriting period, accounting period, region, risk group, or claims development stage.

This is where the InsFocus foundation becomes essential.
InsFocus AI is built on Insurance BI that already understands the structures, metrics, and analytical logic of the industry.

The AI does not need to create the insurance context from scratch. It works with intelligence that is already embedded in the platform.

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Making Smart Insurance BI Even Smarter

InsFocus BI already helps insurance teams turn complex data into clearer analysis and better-informed decisions.
InsFocus AI extends that value across the analytical process.

It helps users move more naturally from a business question to a report, ask questions directly about the results, receive smart insights from the AI Agent, and continue investigating the data in real time.

The result is not simply a new way to interact with data.

It is a smarter way to work with Insurance BI.

InsFocus AI adds a new layer of intelligence to Insurance BI, turning trusted insurance data into faster analysis, proactive insights, and deeper investigation in real time.

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