Use Case · Accounting Firms

Scale client capacity
without hiring capacity.

Managing 10, 20, or 50 clients means constant context switching — different systems, different document formats, different people to chase. BeanStack gives each client their own workspace and lets AI do the first pass on every transaction. Your team's job shifts from preparer to reviewer.

Most of your team's hours go to work a computer should be doing, leaving almost no bandwidth for the advisory work clients actually value. The inflection point is when someone realizes the firm has scaled headcount to match client count — and they're scaled to do data entry, not to advise.

BeanStack takes the data entry layer. Documents uploaded by clients are classified, extracted, and turned into draft records the moment they arrive. Bank transactions import directly or from uploaded statements and reconcile against the ledger continuously. Your team reviews drafts instead of producing them — which is where their judgment actually matters.

Multi-client support is built in: each client has their own workspace with separate users and books. Solution packs bundle record types, automations, and approval rules for a specific industry — useful when you onboard a new client type repeatedly.

Where it pays off

Client workspaces

Separate workspace per client

Each client has its own workspace with its own users and books. Sign in once, switch clients from the account switcher. Subsidiaries link as records under the parent.

Document intake

Document AI on every upload

Clients upload PDFs, images, and statements to their workspace. BeanStack reads each one and routes it — bank statements, invoices, reference docs — automatically.

Bank feeds

Direct connections + uploads

Connect bank feeds directly or upload statements. Transactions become records automatically and flow into reconciliation.

Classification rules

Rules per client, shared skills

Description, merchant, and amount conditions map to GL accounts. Rules auto-suggest postings as transactions come in. AI improvements on one client can be reused across your book.

Unified inbox

One queue per client

Extraction reviews, merge suggestions, cash-application suggestions, approvals — staff work a single inbox per client instead of hunting across screens.

Financial close

Five-step close wizard

Setup, validation, execution, monitoring, sign-off. Optional AI analysis, parallel processing, and auto-approval of low-risk journal entries per client.

The old way vs. the new way

Manual grindWith BeanStack
Keying invoice data into the ledgerDocument AI extracts and proposes entries for review
Downloading and importing bank statementsDirect bank feeds and statement uploads
Matching payments to invoicesCash-application suggestions in the inbox
Producing trial balances and financialsAlways-current reports filtered by reporting entity
Chasing clients for contextAI assistant can draft follow-ups from inside chat

Review. Don't
re-key.

Put the AI in the preparer seat. Your team goes back to judgment calls and client advice.

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