The tools behind clearer retirement decisions
Example AI combines structured data analysis with predictive modelling so you can see the shape of your finances before you commit to a decision.
Built around your numbers, not a generic template
Every household approaching retirement carries a different mix of savings, pensions, and obligations. Rather than applying a one-size-fits-all rule of thumb, Example AI takes your actual data and runs it through a structured analytical process, surfacing patterns and pressure points that are easy to miss when working from a spreadsheet alone.
The result isn't a prediction of certainty — it's a clearer, evidence-based view of the range of outcomes you might reasonably expect, so decisions are made with more information and less guesswork.
Structured data in. A clearer picture out.
What Example AI does with your information
Data Consolidation
Pensions, savings, and income sources are brought together into a single structured view, removing the guesswork of juggling multiple statements and formats.
Predictive Modelling
Historical and current data feeds a modelling process that projects a range of plausible outcomes rather than a single, potentially misleading figure.
Scenario Comparison
Adjust key assumptions — spending, timing, income — and see how each change shifts the overall picture, side by side.
Plain-Language Reporting
Findings are presented in clear, jargon-free language, with the underlying figures always available for those who want to look closer.
Ongoing Review
As your data changes, your analysis can be revisited, keeping the picture current rather than fixed to a single point in time.
Human Follow-Up
Automated analysis is paired with the option to discuss results directly, so nothing important is left to interpretation alone.
Analysis designed to be understood, not just delivered
It's not enough for a model to be accurate if nobody can follow what it's telling them. Every feature in Example AI is built with a second question alongside "is this correct": is this clear? Reports are structured to walk through assumptions, ranges, and implications step by step, so you can follow the reasoning rather than simply trusting a headline number.
Outcomes shown as ranges, not false certainty
Financial futures are inherently uncertain, and a tool that hides that uncertainty behind a single confident-looking number can do more harm than good. Example AI presents projections as ranges, built from the underlying data and stated assumptions, so you can see best-case, worst-case, and most-likely paths together.
- Clear visual separation between assumptions and results
- Adjustable inputs to explore sensitivity to change
- Historical context alongside forward projections
- Consistent methodology across every scenario you run
Illustrative representation of a scenario comparison output. Actual reports vary by data supplied.
Situations these features are built for
Weighing Withdrawal Timing
Compare how drawing on savings or pensions at different points affects the overall trajectory of your finances over time.
Consolidating Scattered Accounts
Bring pensions and savings held across several providers into one structured view before making a decision that touches all of them.
Stress-Testing Assumptions
Adjust spending or income assumptions to see how sensitive your outlook is to changes you can't fully control.
See what these features reveal about your own numbers
Start an analysis with Example AI and get a structured, evidence-based view built directly from your data.