Multi-Source Data & Finance Automation

Automate
Predict
Multi-source data and finance automation

Messy data from many systems, sorted automatically.

Exports from several systems, each in its own format, the same item spelled ten different ways. Making the table is easy. The hard part is matching the items up first - get one wrong and everything after it is off. Many teams still do this by hand every month, which is slow and error-prone.

We bring the data from every system into one place and turn names, sizes and units into one standard set, stopping obviously bad data at the door. Then we write your accounting rules into the process, so reports come out on their own with problem rows flagged red. Before handover, the system works out the results without looking at the manual answers; where they don't match, we fix the rules and run it again.

Manual effort on monthly reconciliation drops by more than 90%, report turnaround is also more than 90% shorter, and it can run on a schedule. Results stay within 2% of the manual check, and every figure can be traced back to the source row it came from.

Gallery

Diagram: data from three systems is matched into one table, then a report flags one group in red

How it works: data from several systems is matched into one set, then the report flags problems in red. (Diagram, not real data.)

  • Match across systems

    Different names for the same item are matched automatically.

  • Your rules, built in

    Your business rules run every time, not from someone’s memory.

  • Exceptions flagged

    Only the odd rows need a person to look at them.

  • Bad data stopped early

    Clearly wrong records are caught on the way in, before they spoil the totals.

  • Every number traceable

    Any figure in the report can be traced back to the original row it came from.

  • Runs on a schedule

    Once set up, the reports can run on their own at set times.

  • Tested blind before handover

    The system computes results without seeing the manual answers. We only adjust rules when the gap is real.

  • Assumptions written down

    Categories that look alike but differ in business or contract terms are never merged. Anything not yet confirmed is written down as an assumption, not quietly decided in code.

  • Works in any industry

    If your data comes from several places, the same method applies.

Ready to Get Started?

Contact us to discuss your specific needs and learn how we can help transform your business.