Compounder
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THE DATA FOUNDATION

The structure behind better AI answers and decisions.

Compounder brings together and structures financial, customer, product and supplier data from your business systems. The data is connected to your definitions and rules — into one shared basis for reports, analysis and AI.

Has the board received a polished AI analysis with the wrong numbers?

It is quick to upload a general ledger to Claude and get a well-written decision paper back. But were the right periods compared? Were overlapping figures counted twice? Were the key figures calculated by your definitions?

Compounder structures the data and makes the relationships clear before the analysis starts. That gives the AI a better chance of getting the numbers right — and you a better basis for your decisions.

From scattered data to one context.

01

Structure the data

Charts of accounts, product groups, customer names and geographic divisions can differ between systems and companies. Compounder brings the data into one shared structure, with the link to the source kept.

02

Connect and define

An amount needs to be readable together with, for example, company, period, account, customer and product. The relationships make it possible to examine the same data from several angles.

Your definitions set how the measures are read: which accounts are part of revenue, how the margin is calculated or which countries count as the Nordics.

03

Use and verify

The same foundation is used in reports and connected AI tools. Permissions control access, and traceability lets you go from the summary to the data behind the number.

The data, relationships and detail available depend on your connected systems.

More power for the analysis. Less for the groundwork.

With the structure in place, the relevant information can be fetched for the task. The AI needs to spend less effort interpreting and reconciling large numbers of exports and documents.

  • Better decision support

    Shared definitions and clear relationships give Claude, ChatGPT and other connected AI tools a better basis for relevant comparisons and useful analysis.

  • Faster answers

    When the AI has less material to read and process, response times can drop.

  • Lower token use

    Relevant selections can reduce the amount of information external AI services need to handle — and with it, the tokens used.

  • Value that is reused

    The same structure can be used in the next question, monthly report and follow-up. You also get a foundation to build on as new AI tools and agent-based workflows become relevant.