AI for accountants
Prepare document requests, onboarding steps and routine admin for your team to review, subject to the access your software supports.
In short: EBROTECH assesses how an AI agent could support the accounting software your firm already uses. We verify the product, plan, permissions and available fields. The system prepares document requests, onboarding tasks and replies for a professional to validate; it does not provide tax advice or send emails on its own.
The firm defines which documents are required, the deadline and the exceptions. The system can identify a missing item and prepare a request, but a person reviews and sends each email. The accountant remains responsible for completeness, classification and any tax conclusion.
A generic chatbot on your website can answer 'what are your opening hours'. An AI agent for an accounting firm does real work: it onboards a new client by collecting the right details and documents in the right order, it answers the recurring 'when is my VAT due' and 'have you received my records' questions with the actual answer from your system, and it flags anything it cannot handle to a human with full context. The agent is connected to your data and your deadlines, so it is specific to your practice. A chatbot is a website ornament; an agent is a member of staff that does not sleep.
Most modern practices run on Xero, QuickBooks Online, Sage or FreeAgent, with Dext or similar for receipt capture. These platforms have solid APIs, so the AI layer connects directly: it can see which clients are missing data, which invoices are overdue, and which deadlines are approaching. Older desktop ledgers work through scheduled exports. Nothing about your stack changes; the AI sits on top and reads what it needs. We will tell you in the discovery call precisely what each of your systems supports today, with no inflated claims about integrations that are not live.
Making Tax Digital in the UK, and mandatory e-invoicing across the EU from 2026-2027, are pushing every firm towards more frequent, more structured submissions. That is more deadlines and more document-chasing, not less. AI is the natural fit here: it tracks each client's obligations, requests the data ahead of each deadline, and keeps a clean audit trail of what was asked and when. Firms that put this layer in early turn a regulatory headache into a routine, automated rhythm, and look noticeably more on-the-ball to their clients.
We build the practice's automations with Claude Code from Anthropic, which is why a bespoke system is affordable rather than enterprise-priced. ChatGPT from OpenAI is also genuinely useful inside a firm for drafting client emails, summarising long documents and producing first drafts of advisory notes, with a human always reviewing the output. The important distinction: ChatGPT is a writing assistant for your team, while the AI agents that chase documents and onboard clients are purpose-built and connected to your data. Different tools, different jobs.
The ROI here is mostly in reclaimed hours, and they add up fast. Document-chasing, onboarding admin and answering the same questions can swallow a junior's entire week during busy periods. Automate the bulk of it and you either take on more clients without hiring, or you give your existing team their evenings back at quarter-end. The ranges in the table reflect what mid-sized practices recover, weighted towards hours saved rather than headline revenue.
Hours
call coverage configured for each line and service
Your software
stays the source of truth, with no forced migration
Measurement
goal and baseline defined before work starts
Control
human handoff and limits agreed for each task
Scope, baseline and metrics are agreed for each project.
Agreed baseline and target
The agent requests the records each client owes, follows up the non-responders on a schedule, and only escalates the genuinely late ones to a human. The accountant receives clean, complete bundles instead of fragments dribbling in. The setup is validated in discovery and measured against an agreed baseline and goal.
Onboarding in days, not weeks
The agreed checklist shows the client which details, documents and authorisations are still needed. The system prepares reminders and a person reviews and sends the emails. Timing is measured from a baseline rather than promised.
Agreed baseline and target
The recurring questions ('when is my VAT due', 'have you got my records', 'what do I owe') are answered straight from your system, day or night. The setup is validated in discovery and measured against an agreed baseline.
Agreed coverage and error measures
The firm defines the applicable deadlines, recipients, exceptions and review rules. The system prepares reminders for professional validation and human sending; coverage and errors are measured without guaranteeing that an obligation or penalty cannot be missed.
Faster cash collection
The firm defines eligible unpaid invoices, cadence, stop conditions and dispute handling. The system prepares each reminder for human review and sending; collection speed is measured without a guaranteed outcome.
Steady review growth
Builds the local reputation that wins the next client without spending on ads. The setup is validated in discovery and measured against an agreed baseline.
Connection validation
We check the connection, permissions and scope before deciding whether a layer is enough or any migration is needed.
Your software
EBROTECH AI
Goals
Scope is agreed after validating your system.
Tell us about your caseYes. Xero, QuickBooks Online and Sage have solid APIs, so the AI layer connects directly to see overdue records, unpaid invoices and upcoming deadlines. Dext and similar capture tools plug in too. Older desktop ledgers run via scheduled export. You do not migrate your stack.
Yes. The chasing and onboarding messages are written in your firm's voice, reviewed and signed off before going live. The AI keeps the tone professional and consistent across hundreds of clients, which is hard to do by hand.
Yes. It tracks each client's obligations, requests the data ahead of each deadline and keeps an audit trail of what was asked and when. As filings get more frequent under MTD and EU e-invoicing rules, that automation is exactly where AI pays off.
Compliance depends on the roles, lawful basis, suppliers, location, retention and safeguards in the agreed setup. Discovery maps the permitted accounting fields, minimises access and records the agreements for the firm and its adviser to review.
No. It removes the repetitive admin (chasing, onboarding, routine queries) so your accountants and bookkeepers spend their time on advisory work and judgement calls. Most firms use the freed capacity to take on more clients rather than to cut staff.
Engagements are structured month to month. Commercial terms and any applicable guarantee are set out in the written proposal.
Tier 1 Bridge: ~7 days. Tier 2 Augment: ~14 days. Tier 3 Migrate: 3-4 weeks with full data migration and workflow rebuild.
That depends on the product, plan, permissions and available interface. We prefer a maintained connection to the current ledger, but confirm it with controlled data before promising read or write access. If there is no safe route, the diagnosis records the limit and alternatives.
Think of it as a member of staff who works around the clock on repeatable, rules-based tasks: sending the right document request to the right client at the right time, answering the standard queries that come in every week, chasing unpaid invoices and onboarding new clients in the correct sequence. It does not do the accounting; it does the admin that surrounds the accounting, so your qualified staff can focus on work that actually requires their judgement.
Start with the form. We review what is holding you back and, if it makes sense, arrange a short call afterwards to define what we would build.
EBROTECH guide
Guided journeyThree questions to understand your case and point you to the next step.
