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Case Study

Private AI for Accounting Firms

How accounting and tax advisory firms automate document collection, reconciliation, filing deadlines, and reporting — with client data redacted before any AI model is involved.

6–13
Hours Saved per Person, Weekly
40+
PII Types Redacted Before Any Model
5
Workflows in Daily Operation
15 Days
Idea to Working Prototype

The Challenge

An accounting firm's month is a chase: chasing client documents, chasing reconciliation differences, chasing deadlines. The data is sensitive — financial records, salaries, tax IDs — so public AI tools were never an option. The hours went into email ping-pong and copy-paste instead of advice.

The Document Chase

Receipts, statements, and contracts arrive late, in every format, across email, portals, and paper. Every close starts with hunting.

Reconciliation by Hand

Matching bank statements to ledgers line by line — skilled people doing work a machine should pre-sort.

Deadline Pressure

Dozens of clients, each with filing dates, each missing something different three days before it's due.

Confidentiality Rules Out Public AI

Financial records and tax IDs in a public chatbot is a client-trust incident, not an efficiency gain.

The Solution

The same privacy layer as in every d2b deployment — real-time redaction, EU or on-premise processing, full audit trail — with five workflows plugged into the firm's existing tools: inbox, PDF folders, Excel, the ERP, and the shared calendar.

Client Document Collection

The system knows what each client owes for the period, requests it automatically, watches the inbox and PDF folders for arrivals, extracts the data into structured rows, and keeps chasing what's missing — politely, persistently, without an accountant writing a single reminder.

  • Automated, per-client document requests with escalating reminders
  • Inbox and folder watchers detect arrivals in any format
  • Redacted extraction into Excel/ERP rows — typed by nobody
  • Month-end close starts complete, not with a hunt

Reconciliation & Exception Flagging

Bank statements meet ledger entries automatically. Clean matches clear themselves; differences arrive ranked and explained. Accountants spend their time on the ten exceptions, not the thousand matches.

  • Auto-matching on redacted, structured data
  • Exceptions ranked by size and likelihood, each with a suggested cause
  • Every decision logged for the audit trail

Filing-Deadline Calendar

Every client's filing dates live in one orchestrated calendar. Ahead of each deadline, the system checks document readiness, warns the right person, and escalates until someone acts.

  • Per-client deadline calendar, maintained automatically
  • Readiness check N days out: what's still missing, who owes it
  • Escalation chain instead of silent expiry

Reporting Cadence

Daily intake digest, weekly per-client status board, monthly close checklist with management figures, quarterly filing-season capacity forecast — generated from live data, on schedule, without anyone compiling slides.

  • Daily: what arrived, what's missing, what's urgent
  • Weekly: status board across all clients
  • Monthly: close checklist + management figures
  • Quarterly: capacity forecast for filing season

Report Templating

Source documents and ledger data are aggregated, and the findings flow straight into the firm's templates — client letters, management reports, filing packages. Drafts arrive review-ready; partners edit instead of assemble.

  • Firm templates filled from analyzed source data
  • One data set, many outputs: letter, report, filing package
  • Partners review and sign — assembly time near zero
intake → redact → reconcile → report IDLE
1 — A document arrives
bank-statement-mar.pdf · 214 KB · via inbox
Account holder: Müller GmbH
IBAN: DE89 3704 0044 0532
Contact: a.schneider@…
Period: 01–31 March · 148 lines
2 — What the firm sees back
01Lines auto-matched to ledger141
02Cleared without a human95%
03Exceptions, ranked + explained7
Daily intake digest
Representative example. The workflow is real; the specimen document is synthetic — client files never leave the client.

System Architecture

Client documents cross a redaction boundary before any model processes them THE FIRM'S SYSTEMS PROCESSING Inbox statements, receipts PDF folders client uploads Excel / ERP ledger Shared calendar filing dates Redaction layer 40+ PII types Classifier what is this document Reconciliation match, rank, explain Report writer digest, checklist REDACTION BOUNDARY

Implementation Timeline

Phase 1

Audit

Week 1

We map the firm's back office: where hours leak, which data is sensitive, what the regulator expects.

Phase 2

Connect

Week 2

We plug into the tools already in use — email, calendar, document folders, Excel, and the practice systems.

Phase 3

Orchestrate

Weeks 3–5

Workflows go live behind the privacy layer; the team approves exceptions while the system does the typing.

Phase 4

Report

Ongoing

Daily, weekly, monthly, and quarterly reporting runs itself from live data.

The Results

6–13 hours saved per person per week across participating teams

Thousands of documents collected, extracted, and reconciled behind the privacy layer

Closes start complete; deadlines escalate instead of expire

The firm talks to its data: "Which client files are missing for the March close?" is a question, not a morning of email

Technologies Used

n8nPrivate LLMsPII Redaction LayerEU HostingDocument IntelligenceCalendar & Email APIs

For law & accounting firms

Your AI Audit — €399, not €599.

A mapped back office, an hourly value on every leak, and a privacy-first build plan you could hand to anyone — now €399 for legal and accounting firms (normally €599). You save €200.

We run a limited number of founder-led audits each month. Introductory pricing while we expand into legal and accounting — it won't run forever.

Claim your €399 AI Audit

Eligibility: commercial law firms and accounting/tax practices. One audit per firm.

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