AI for accounting firms. Custom-built, tested in practice.

The major vendors — Wolters Kluwer CCH iFirm, Visma, Exact, AFAS, CaseWare — have built AI modules into their products. For standard invoice processing, bank transaction categorisation and basic OCR, these work satisfactorily. Until a firm has its first non-standard requirement. A proprietary risk framework for the audit, a sector-specific check for a healthcare or housing association client, an onboarding flow that must cover Wwft, UBO and sanctions list screening in one step — that is where the standard package stops.

Mid-market accountancy firms often struggle with the combination of five or more systems: the accounting package, CRM, document management system, e-invoicing platform and AML tool must work together as one coherent flow. Big Four spin-offs and challengers want their own LLM workflow in which client data is guaranteed not to leak to OpenAI or Anthropic, and they often build their market position on that data sovereignty. Tax advisory firms have their own clause libraries and advice templates that no generic AI can handle. Bookkeeping cooperatives want a white-label tool that all affiliated members can use, without the cooperative having to set up its own IT team. Trust firms with an accountancy arm face AML and sanctions list screening that differs by jurisdiction, and UBO structures more complex than any standard onboarding can handle. Civil-law notaries with financial and governance advisory work face the same compliance requirements and can often reuse the same flows.

That is where we build the custom layer. Not a replacement for Twinfield or CaseWare, but an AI layer on top that supports precisely the flow that sets your firm apart. With the right governance, a watertight audit trail and compliance from the first sprint. Our starting point is always: what do you do better than other firms, and how can AI make that distinctive expertise more scalable without compromising the quality of judgement?

Audit assistance. On assurance engagements, the work is shifting steadily from execution to judgement. An LLM that scans the ledger for red flags for the auditor, audit sampling that combines statistical sample selection with risk-based scoring, and anomaly detection across financial years and sector benchmarks: this is where we see most implementations. MindBridge AI Auditor is often the commercial starting point; we come into the picture when a firm wants its own risk framework that does not fit a standard package. Think of healthcare accountancy, where DBC checks and NHC classifications need to be automated, or housing association audits, where the DAEB and non-DAEB split must be verified separately. The audit team retains ultimate responsibility; the AI does the groundwork and flags where human judgement is essential.

Client communication. A mid-sized firm sends thousands of emails a week: questions about VAT returns, annual accounts components, payroll details, tax changes. A large share of these are repetitive. A well-built client communication assistant reads incoming mail, recognises the intent, and drafts a reply referencing that client's relevant files. The accountant or tax adviser reviews and amends; substantive responsibility remains entirely human. For mid-market clients we often build a CFO-as-a-service layer on top: an automatically generated monthly report commentary to which the firm adds its own perspective and advice before it goes to the client. It scales advisory work to many more clients without losing the feeling of personal contact.

Document classification and DAS. Incoming post, whether physical or digital, now needs to be routed automatically: a UBO notification, a Wwft document, a VAT correction, a revised annual account. A classification model layered over scanning software can do this with considerable accuracy. On top of that we build Document Automation Solutions: standard reports, audit statements and advisory templates that produce a first draft from client data, after which the accountant completes and signs the document. It saves most time in the assistant role, where capacity is currently scarcest. For VAT return and payroll checks we build similar flows, in which the LLM cross-references collective labour agreement (CAO) application, holiday entitlements and shift allowances against the client's input, and refers outliers to a payroll administrator.