White label AI bookkeeping software your clients see as yours

The AI works on the most repetitive part of bookkeeping. As bank activity reaches a client’s ledger, it proposes a category for each transaction, drawing on that client’s history and the description on the line. During reconciliation it pairs bank lines with the invoices and bills already recorded, so your team starts from a nearly finished picture rather than an empty register.

Just as important is what it does with uncertainty. Lines it cannot place with confidence are held for a person instead of being filed under a guess. Those items appear as work waiting on the client in the firm console, which is how your reviewers know where to look first. This is deliberate: a confident wrong category is harder to catch than an honest blank.

Because this happens inside the same product as invoicing, bills and reports, there is no hand-off between a separate automation tool and a separate ledger. Corrected categories feed straight into the reports clients read, and every figure traces back to a transaction someone at your firm could open. That traceability lets a reviewer answer a client’s question about a figure by opening the transaction behind it rather than reconstructing the calculation.

AI in bookkeeping is good at patterns and poor at context. It cannot know that a payment to a familiar supplier was really a personal expense, that a transfer between accounts belongs to a loan, or that a client has changed how it treats a cost this year. Those calls belong to a professional, and the software is built on that assumption.

In practice, your bookkeepers confirm or correct suggestions, resolve the items set aside, ask clients the questions only they can answer, and decide when a set of books is ready to close. Your advisers interpret the finished reports. The AI shortens the path to that point; it does not sign off on anything, and your firm keeps the professional responsibility that clients are paying for.

Clear roles also help when you explain the service. Owners generally accept automation readily once they know a named person at your firm is checking the result, and that reassurance is easier to give when the product itself carries your firm’s name rather than a vendor’s. It also sets expectations early, so clients know who to ask when a figure looks odd.

• AI: proposes categories and pairs bank lines with recorded entries
• AI: holds back lines it cannot place with confidence
• Your staff: review, correct and approve the proposals
• Your staff: decide treatment of unusual items and close the period
• Your clients: explain transactions only they understand

A typical day for a reviewer starts in the firm console rather than inside any single client. The console lists every client company with its close status and the number of items waiting, so the reviewer can choose where to spend the first hour instead of opening each ledger to find out.

From there, the loop is short. Open a client, work through the proposed categories, accept or correct each one, handle the lines the AI set aside, and send any questions to the client inside the branded app. As corrections accumulate, suggestions for that client tend to fit its books more closely. When nothing is left waiting, the period can be closed and reports sent on your templates.

Staff seats are unlimited, so a second reviewer, a contractor during a busy season or a partner who wants to check a sample can all have their own login without any change to the license. Adding reviewers is often the quickest way to shorten month end during a busy season, so it helps that doing so carries no seat charge.

Automation is the part of bookkeeping software that clients talk about. When an owner tells a friend their books seem to sort themselves out, they name whatever appears on the screen. Under the White-Label License that is your app name, shown with your logo and colors on the sign-in page, the dashboard and the documents the system produces.

Branding also makes review easier to explain. With one product and one accountable party in view, it is natural to tell clients that the AI makes suggestions and your firm signs off. Your address runs on a hellobooks.ai subdomain from day one; your own domain and email from your firm’s domain arrive at full launch. Clients use the web app in any browser, including on phones, and an own-name native app is a future add-on.

There is a quieter benefit too. When a suggestion turns out wrong and your team corrects it, the client sees a firm that caught the error, not a vendor’s tool that made one. Keeping the whole experience under your name keeps accountability, and the credit for getting things right, in one place.

Your firm pays HelloBooks a flat monthly license. Every client company is placed on one of the published HelloBooks plans, which your firm buys at a discount. AI categorization and reconciliation are part of the included ledger rather than a paid extra. You bill clients your own price, and HelloBooks bills only the firm. The figures are in the pricing table on this page.

Some firms add a separate AI automation tool on top of a ledger they already resell. That can work well, but the client often meets two products, and the ledger keeps its vendor’s brand. Others hand the work to an outsourced white-label bookkeeping service, which adds people but not necessarily better tools, and may keep working files in its own systems. A branded AI ledger keeps the automation, the records and the credit inside your practice.

When comparing these routes, count the products a client has to learn and the logins your staff have to manage, as well as the fees. A route that looks cheaper on paper can cost more in support time if clients meet two or three different brands for what they think of as one bookkeeping service.

Onboarding takes about two working weeks. Branding, the sign-in page and your document templates are set up with you, and your team learns the console and review queues. Many firms begin with a small pilot group, check how the suggestions fit those clients over a couple of closes, and then bring the rest across in batches. Signing before full launch brings founding-firm terms with it. Choosing pilot clients with tidy history and regular bank activity gives the suggestions the clearest patterns to work from.

The client data belongs to your firm, including the corrections your staff make. You can export it at any time, and if you ever leave, you keep read-only access for a period. That makes it reasonable to commit a meaningful share of your client base to the platform without feeling locked in.

A firm hoping AI will remove the need for review will be disappointed; the software is designed around a person checking its work. If your firm is not prepared to review what the software proposes, it should not put its name on the output. Likewise, a practice that wants a provider to do the bookkeeping for it needs an outsourcing service, since HelloBooks sells software, not staff.

Firms that need their own domain and firm email live on the first day should plan for full launch, and those whose clients want an app-store app under the firm’s name should wait for that future add-on. If your clients mostly bring you a shoebox of paperwork once a year, a year-end service may suit them better than a live AI ledger.

Founding firms go live on a firm subdomain with their name, logo and colors throughout. Your own domain and email sent from your domain arrive at full launch.

Firms usually weigh four ways of putting client books under their name. The difference is whose brand clients see, whether the ledger is included, and who does the work.

One flat license covers your brand, unlimited staff and the firm console. Your clients stay on published HelloBooks plans, and your firm gets 20% off each one. Founding firms go live first on a firm subdomain; your own domain and email from your domain follow at full launch.