Reliable foundations
Bring source data, definitions, time windows, assumptions, and costs into view before interpreting a result.
In active development · Economic and market intelligence
Economic and market data,
Economic and market data,
seen from more angles.
EigenMap AI is an analytical workbench for examining economic and market data. It brings source context, linked visual analysis, and explicit assumptions into one environment so users can compare periods and conditions, inspect results, and pursue new lines of investigation.
An Appalore platform
The approach
Keep the evidence, assumptions,
Keep the evidence, assumptions,
and results connected.
A change in time period, comparison, or assumption should carry through the analysis. EigenMap AI keeps views linked so users can examine the same market from multiple angles without reconciling disconnected charts or numbers.
Results remain tied to the data, method, costs, and limits behind them, making it easier to distinguish an observation from a scenario, benchmark, or model output.
Capabilities
What EigenMap AI does
Four elements shape the analytical workbench.
Adaptable exploration
Use linked views and filters to compare periods, conditions, measures, and outcomes without changing the analytical context.
Patterns and scenarios
Examine recurring behavior and changing relationships, then adjust explicit assumptions and compare the resulting scenarios with observed history.
Model-assisted discovery
Local AI models add a grounded layer for surfacing connections and questions for further examination.
Workflow
From information to investigation
01
Establish context
Select the data, period, measures, assumptions, and comparisons that define the question.
02
Change the view
Move across linked charts, tables, distributions, and comparisons while keeping the same analytical scope.
03
Test assumptions
Change selected inputs or constraints and see how the result changes, with each scenario kept distinct from observed data and model forecasts.
04
Follow the questions
Inspect outliers, drawdowns, transitions, and unexpected results, then pursue the next comparison or question.
Analytical foundation
Built to compound
Compounding foundation
New analytical capabilities strengthen a shared foundation rather than remaining isolated tools.
Adaptable scope
The platform can expand across new questions and available information while retaining its central purpose.
Traceable method
Data, assumptions, calculations, and limits remain visible as questions and views change.
Evolving intelligence
Each new capability builds on the analytical foundation, allowing the workbench to compound over time.
Explore economic and market systems more clearly.
Interested in a clearer way to explore complex economic or market data?