// accounting
Automation that ties out.
Accounting automation has a trust problem: an AI that's 95% right on document extraction is 100% useless at close, because nobody knows which 5% is wrong. The systems worth building are the ones that verify themselves — extract, then reconcile against source, then surface only the exceptions a human should see.
That architecture is our home turf. Our own trading operation runs on it: every automated position reconciled to the exchange's fill records, every P&L number tied to source before it's believed. An accounting firm's version of that bar — every extracted figure tied to its document, every batch tied out before it posts — is the same engineering.
Where the hours go, and come back
invoices, receipts, statements, K-1s: classified, extracted with confidence scoring, exceptions queued for review instead of everything queued for data entry.
the follow-up chase ("we still need your December statement") drafted, sent, tracked, and escalated automatically.
cross-system checks that run nightly and report only variances, with links to the underlying records.
LLMs are genuinely strong at first-draft narrative from structured numbers; your reviewers' time moves to review.
Built for a regulated profession
Human-in-the-loop gates where judgment lives, full audit trails on every automated action, your data in your accounts — never in a vendor's black box. Builds from $5,000, scoped to one workflow first, expanded only after it proves itself through a real close cycle. studio@anchor163.com
studio@anchor163.com
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