# Connecting your accounting and CRM without double entry > What to synchronise between accounting software and CRM, in what order, where generative AI adds something, and why monitoring decides everything. Author: Anthony Crowther-Alwyn · Published 2026-09-23 · https://www.praedic.com/en/guides/connecting-accounting-and-crm-without-double-entry In a small or mid-sized company, the accounting software knows about the invoices and the CRM knows about the deals. Between the two, someone re-keys a quote every month, checks that a deal marked won has actually been invoiced, or rebuilds the state of incoming payments by hand for a sales meeting. That work appears on no job description, yet it takes several hours a month and it produces errors. Here is how to remove it, drawn from a project run for a twenty-person consultancy. ## The real cost of two tools that do not talk to each other The visible cost is the re-keying. The real cost lies elsewhere: sales management drifts away from financial reality. A deal marked won in the CRM does not necessarily have a matching invoice. A client who has stopped paying keeps receiving sales outreach. Forecast revenue gets calculated on deals nobody has updated in weeks. And these gaps only come to light at the end of the financial year, when it is too late to act. The problem is not technical. Every accounting package and every CRM on the market exposes an application programming interface that lets them be connected. The problem is that nobody has the time to build and maintain that link, and off-the-shelf connectors rarely cover the way the company actually works. ## What gets synchronised, and in which direction In the reference project, [the accounting ran on Pennylane and the CRM on HubSpot](/en/case-studies/connecting-finance-and-crm). Three objects move between the two. **Clients.** A single record per company, recognised on both sides. This is the foundation for everything else, and it is often the longest part to make reliable, because duplicates and variants of a company name have built up over years. **Quotes.** A quote that is issued becomes visible on the matching deal in the CRM, with its amount and status. The salesperson no longer has to attach it themselves. **Invoices.** An invoice, issued and then paid, flows back into the CRM. The gap between what was sold and what was invoiced becomes visible as it happens. Each flow has a defined direction, and only one tool is authoritative for each piece of information. The accounting software is the source of truth for invoiced amounts and payments, the CRM for sales progress. Syncing the same piece of data in both directions sooner or later produces conflicts nobody knows how to resolve. At the outset, historical data is carried across, so the CRM does not start empty and the dashboards make sense from the first week. ## What automation then makes possible Once the two tools are connected, automations that used to be unreliable start working, because they finally rest on accurate information. The simplest is chasing prospects based on the actual state of the deal, rather than on whenever someone happens to think of it. A follow-up sent from stale information is irritating. A follow-up sent at the right moment, with the right context, gets read. There is also a benefit for management: signed, invoiced and collected revenue that can be read in one place, with no spreadsheet rebuilt by hand. ## Where generative AI adds something Everything above is classic automation. It needs no language model, and it would be dishonest to claim otherwise. Generative artificial intelligence comes in where classic automation cannot help: writing text that depends on context. In the same project, every new newsletter subscriber receives a welcome message written for them, drawing on what is known about their sector, their company and the content that brought them in. Not a template with a first name as a variable, but a message that speaks to their subject. Some of these subscribers reply, and some of those replies turn into a sales conversation. No team can write these messages by hand at scale, and a model does it properly. The same reasoning applies on the finance side. Checking every supplier invoice against the negotiated terms, prices, end-of-year rebates, payment terms, requires reading contracts in PDF form and invoices line by line. That is what we did to [check an entire invoicing flow](/en/case-studies/invoice-and-contract-audit) rather than a sample, with a return on investment that was almost immediate: incorrect payments are blocked before they leave the company's cash account. ## The part everyone forgets: monitoring A sync runs on its own, and that is exactly what makes it dangerous. Automation that breaks silently is worse than no automation at all, because it gives the impression that the work is still being done. You find out three months later that invoices stopped flowing through after one of the two pieces of software was updated. Every process therefore needs to report on its own execution, and any anomaly must trigger an alert sent to a named person, not to a generic inbox nobody reads. A monthly check also verifies that the figures still match between the two tools. This is the least glamorous part of the project, and it is the one that decides whether the system will still be in place in two years. We treat it with the same care on [our reference data pipelines](/en/case-studies/monitored-reference-data-pipelines). ## The order that works The most common mistake is trying to synchronise everything at once. The order that works is as follows. 1. **Identify the flow that costs the most re-keying.** Usually, quotes or invoices going to the CRM. 2. **Make it reliable, duplicates included.** This is often where most of the time goes. 3. **Monitor it.** Alerts and a matching check before going any further. 4. **Only add the next flow once the first one has been running unattended for several weeks.** This work sits within the [admin and finance lever](/en/levers/admin-and-finance). It is rarely the most visible part of the business, but it is one of the easiest gains to measure, in hours given back each month and in errors that no longer happen. If you want to know what it would be worth for you, [the diagnostic](/en/diagnostic) puts a figure on it within eight days.