My AI assembled my whole year-end package for the accountant
Year end is the part of running a business everyone dreads, gathering every statement, every receipt total, every schedule, and handing a clean package to the accountant. I had Laura assemble ours. She pulled the sources together, built the summary, and in the process surfaced nine data quality issues I needed to resolve.
One pipeline, every source
A year-end package is not one document, it is a dozen of them that have to agree. Revenue from Stripe, expenses from the books, the shareholder loan balance, the meal deductions, the home office math. Laura pulls from each source, assembles them into one folder, and generates the accountant summary from the actual data rather than from numbers I typed in and hoped were right.
Because the summary is built from the source, not re-keyed, it does not drift. If a number changes upstream, the package changes with it. No stale copy floating around with last week's figure.
It found the problems before the accountant did
The more useful thing she did was find nine data quality issues while building it. Gaps, mismatches, amounts that did not line up between systems. Those are exactly the things an accountant charges you to chase down, or worse, the things that quietly make your filing wrong. Finding them in advance turns a messy back and forth into a clean handoff.
This is the right division of labor with a human CPA. The agent shows up with clean, reconciled, complete data. The accountant does the judgment and the filing. You pay for the expertise, not for the data cleanup.
Hand your accountant clean books, not a shoebox. We build the agent that assembles them.
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