Tinkerberry Labs
AI automation for finance

Close faster, chase less, catch more.

Month-end is a fire drill, AR chasing never happens on time, and nobody has read the expense policy since 2019.

Accounting practicesFinance teams in scale-upsBookkeeping firmsShared service centres

80-95%

of invoice lines extracted automatically

10-20 days

typical DSO improvement

30-50%

faster month-end close

8

documented automations for this sector

The automations

Where finance teams lose hours, and what replaces it.

Each one is a system we have specified and built before.

01

Accounts payable invoice processing

The manual process today
Invoices arrive by email as PDFs and are keyed in line by line.
What we build
Automatic extraction, PO and receipt matching, coding suggestions, duplicate detection and approval routing by amount and department.
Typical impact
Most invoices flow straight through; humans handle exceptions only.
Document AIERP / accounting systemApproval workflow
02

Collections and AR chasing agent

The manual process today
Chasing overdue invoices is nobody's favourite job, so it slips.
What we build
Escalating, relationship-aware chase sequences with payment links, dispute detection and automatic handoff when a customer replies with a problem.
Typical impact
DSO improvements of one to three weeks are common.
Ledger dataEmail / SMSPayment links
03

Expense policy enforcement

The manual process today
Expense claims are approved by managers who never read the policy.
What we build
Every claim checked against policy with receipt verification and outlier detection, flagging only what actually breaches.
Typical impact
Policy applied consistently; approver time nearly eliminated.
Expense platformOCR + policy RAGAnomaly detection
04

Bank reconciliation assistance

The manual process today
Unmatched transactions consume the first three days of close.
What we build
Match suggestions with confidence scores and learned rules from past decisions, leaving only genuinely ambiguous items.
Typical impact
Reconciliation effort reduced substantially each month.
Bank feedsMatching engineAccounting API
05

Management reporting and commentary

The manual process today
The numbers are ready on day five, the commentary lands on day twelve.
What we build
Variance analysis and draft narrative generated from your ledger and budget, in your reporting format, for the controller to edit.
Typical impact
Reporting pack drafted the day the ledger closes.
Warehouse / ledgerVariance analysisNarrative generation
06

Client onboarding for accounting practices

The manual process today
New clients need KYC, engagement letters, software access and a data request list.
What we build
One orchestrated flow: identity checks, letter generation, portal setup and an automated chase for missing records.
Typical impact
Onboarding cycle cut from weeks to days.
KYC providersE-signaturePractice management
07

Transaction categorisation for bookkeeping

The manual process today
Bookkeepers categorise thousands of low-value transactions manually.
What we build
Client-specific categorisation learned from history, with confidence thresholds and a review queue for the unclear.
Typical impact
The bulk of routine coding handled automatically.
Accounting APIsPer-client modelsReview interface
08

Audit evidence preparation

The manual process today
Audit requests trigger a scavenger hunt across drives and inboxes.
What we build
An assistant that locates, assembles and indexes supporting evidence against each audit request, flagging gaps early.
Typical impact
Audit prep time cut sharply, with fewer late surprises.
Document searchRequest trackingEvidence index
Questions

What finance teams ask us.

We never let a model do arithmetic that a system of record should do. It reads documents, proposes matches and drafts narrative; the ledger stays the source of truth and every posting keeps an audit trail.

Approval rules stay yours. We encode them explicitly so routing is deterministic, and only the reading and classification steps are AI.

Audits are a fixed fee and are credited against a build. Single-workflow builds typically land in the low five figures, multi-workflow programmes higher, and ongoing running and support is a fixed monthly fee. You get the number before we start, not a rolling hourly bill.

A first pilot on your real data usually runs within two to four weeks of the kickoff call. Full deployment with integrations and training normally lands between weeks four and eight.

Your automation plan

Tell us what your finance team keeps doing by hand.

Thirty minutes, no pitch deck. We map the process, tell you whether automation pays back, and give you a rough cost before you commit to anything.

You and the work

Two more short steps sharpen the answer. An engineer reads it either way and replies, usually within a business day.

Other sectors

Automations for adjacent industries.