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AI for accounting

AI for accounting and tax, with the bookkeeper deciding

OceanLab builds AI into bookkeeping and tax work: matching payments, checking receipts and turning raw transactions into reports. The AI suggests and shows how sure it is; people book and file. Every example below is a product we built.

2
AI product builds
7
Builds in this industry
2
Countries
2
Frameworks cited
Proof

OceanLab product builds

AI products we designed and built in this industry. Each one is a full case study with screens, scope and the rules it was built for.

Use cases

Where AI earns its place

Each use case names the builds that did it.

Suggested bookings

A bank feed where every payment arrives with a suggested booking and a confidence score, so the person only checks the unsure ones.

Receipt and e-invoice checks

A receipt inbox that validates e-invoices and checks the fields a valid invoice needs before anything is booked.

Tax returns from raw data

A VAT advance return previewed box by box before it is submitted, so nothing goes out unseen.

Tax reports from transactions

Transactions pulled in from 30+ exchanges and wallets, cost basis worked out and the tax forms generated in one click.

Compliance

What to plan for

The rules that shape AI in this industry. General information, not legal advice: check with your own counsel.

Rules stay rules

Tax rates, invoice fields and filing formats are fixed rules, not guesses. Keep them in code and let the AI handle only the fuzzy part, such as which account a payment belongs to.

Show how sure it is

Every suggestion carries a confidence score. Low-confidence items go to a person instead of being booked.

A full audit trail

Record what the AI suggested, what the person changed and who approved it. Auditors and tax offices ask for exactly this.

Keep records as long as the law says

Retention periods for books and receipts differ by country. Plan storage and deletion around your country's rules, and check them with your adviser.

Frameworks our AI builds here cite

GDPR · 2SOC 2 · 1
How it works

From one workflow to production

  1. 01

    Pick the workflow

    We start from one workflow your team wants off its plate and agree what a working result looks like.

  2. 02

    Clickable AI prototype

    Your team tries the flow on a clickable prototype before any production code is written.

  3. 03

    Production build

    We build the production version, with the approval steps and records your industry needs.

  4. 04

    Launch and improve

    It goes live in your team's hands, and we tune it as real work runs through it.

Priced either way, whichever suits the work: outcome-based, paid per milestone, or hourly at $30-50 depending on role and seniority. More on AI automation →

FAQ

Questions teams ask

What can AI do for an accounting or tax team?

Take the matching and checking off people: suggest a booking for each bank payment, check receipts and e-invoices before they are booked, and build tax returns and reports from raw transactions for a person to review. Each of these is a product OceanLab built.

Does a person still sign off?

Yes. In our accounting builds the AI suggests and scores its confidence, and a person books, approves and files. Low-confidence items always go to a person.

How is it priced?

Either way, whichever suits the work: outcome-based, where you pay per milestone, or hourly at $30-50 depending on role and seniority.

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Are you an AI lab looking for human training or evaluation data? That is a separate offer, OceanLab Labs.

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