Somebody in your office retypes the same numbers into the same workbook every week, and the report everyone argues about in the Monday meeting comes out of it. Both halves are fixable: we automate the entry that shouldn't be manual, clean up what's already there, and turn the pile into numbers your team stops disputing.
Every one of these has a fixed-scope first project hiding inside it.
Forty megabytes, a dozen tabs, formulas nobody dares touch, and exactly one person who understands it. That person takes holidays.
Sales, operations, and accounting each produce a different number for last month — and every meeting starts by arguing about which one is real.
Numbers retyped from one system into another, or from a PDF into both. Every retype is a chance to be wrong and a cost you're already paying.
Duplicates, 'TX' and 'Texas' and 'tx', dates stored as text, and trailing spaces that quietly break every lookup.
Export, paste, pivot, format, email. Every month, by hand, by the person you hired to analyze the business rather than assemble it.
The transactions are all there. Nobody has ever asked them which customers are profitable, which routes lose money, or what next quarter looks like.
Usually in that order — an answer built on data nobody checked is just a confident guess.
Backlogs and recurring entry handled — automated first, and made fast where a person is still required.
The unglamorous pass that makes every later number believable.
When the workbook everyone depends on has outgrown being a workbook.
The monthly export-paste-pivot ritual, done by software instead of a Tuesday.
A specific question, a defensible answer, and the method shown rather than hidden.
If the documents arrive as files, or the data already exists in another system you own, then paying anyone — us or an offshore service — to retype it by hand is a rate you pay forever instead of a pipeline you pay for once. So the first question on every entry project is how much of it can stop being manual. What's genuinely left for a person, we make as fast as possible: the right screen, the right keyboard order, and validation that catches the typo at entry rather than in next quarter's report.
We look at what you actually have: record counts, duplicate rates, which fields are usable, and what proportion is beyond saving. You get that in writing.
What counts as an active customer, a completed order, a late delivery. Most disagreements about numbers turn out to be disagreements about words.
The cleanup, pipeline, or report gets built — then checked against the source with counts, totals, and spot checks you can verify yourself.
Documented, scheduled, and runnable without us, with validation rules at the point of entry so the mess doesn't quietly grow back.
A pipeline you buy once beats a per-record rate you pay forever — whenever the source is a file rather than paper.
Written down, agreed, and used by every report. That single step ends most of the arguments about whose number is right.
Readable code, documentation, and scheduled jobs in your accounts. No black box only we can run.
If it can't leave your building, the processing — including AI-assisted extraction — runs on your hardware instead.
We're not here to take your spreadsheets away. Excel is an excellent analysis tool and a poor database, and nearly all the pain we get called about comes from asking it to be the second one — shared by nine people, edited by all of them, with no rule stopping anyone typing "Texsa" into a column that feeds the board pack.
So the shared, must-be-right data moves somewhere that can enforce rules, and your team keeps Excel for what it's genuinely good at: modelling, one-off questions, and the export nobody should have to ask permission for.
For a one-off backlog of genuinely unstructured paper, that can be the right call, and we'll say so. The difference is that we try to delete the job first: if the documents arrive as files, or the same data already exists in another system, the honest answer is a pipeline you pay for once rather than a rate you pay forever.
Almost never. We start with a profiling pass — how many records, how many duplicates, which fields are unusable, what proportion is recoverable — and you get that as a written report before committing to a cleanup. Sometimes it shows that only the last two years are worth saving, which is a cheaper project than you feared.
No. Excel is an excellent analysis tool and a poor database, and most of our work here is just moving it to the first job. Your team keeps their spreadsheets for modelling and one-off questions; the shared, multi-user, must-be-right data moves somewhere that can enforce rules.
Reconciliation, not reassurance. Migrated and cleaned data is checked with record counts, control totals, and spot checks against the source, and reporting pipelines carry tests that fail loudly when a figure stops tying out. You sign off on numbers you can verify.
We take the least data that does the job, work under an NDA when you want one, keep access scoped to the people doing the work, and delete or return the working copies at the end. If it can't leave your building at all, the processing runs on your hardware — including the AI-assisted extraction, which we can host entirely on-premise.
One dataset or one report, fixed price, usually a couple of weeks. That's enough to prove the numbers, hand you something you use immediately, and let you judge whether the bigger cleanup is worth doing — without signing up for it first.
We'll tell you what shape it's really in, what a cleanup would take, and which question it can honestly answer today.
