Automate
Data Entry
How much time is your finance team wasting on data entry? You can cut it down with a pipeline that extracts invoice values and sends them directly into your systems, saving your team valuable time.
Read the input
Check the fields
Update the system
Clean data reaches the right system.
How it works
The first step in setting up this service is checking your existing automation platform. If your current setup doesn't handle intake, review or posting, Vu can build it for you.
That pipeline consists of four steps: intake, read, validate and post. In the intake phase, we review your existing systems, agreeing which channels we'll check. When invoices arrive through any of those channels, the read phase uses a parsing layer to separate the invoice text, then extracts the required fields. After that, the validate phase does a series of business-rule checks: for example, matching totals, checking against duplicates, and in some cases verifying VAT numbers with HMRC. Documents with a failed check are sent to a review queue, where one of your team can inspect the source and correct any necessary fields. Finally, the post phase sends approved records to the relevant destination: ERP, CRM or finance integration, according to your needs.
It's important to note that we can't eliminate all human mistakes. You or your team can still accept a wrong result or make an error while correcting the record. What we CAN do is reduce the risk of those errors, with business rules, comparisons against the original source, and a review queue. On your end, you control the tolerance.
What's in the audit log?
The first part of the audit log holds documents and extracted values. You can search that log, finding any field or set of fields. The second part shows your team's corrections. We can't promise to eliminate recurrence, but we'll make it as rare as possible.
What's your approach to auditing?
We'll ask you for a sample of your documents, and do a thorough review to assess extraction quality. From that audit, we'll develop a plan for validating the extracted fields, flagging exceptions and correcting mistakes. You'll know exactly what's covered, how many errors and exceptions we expect, and how that can save you time and effort. We'll also test out whether our error-identification system works as advertised.
What's the pilot process?
That pilot pipeline handles the whole process: intake, read, validate and post. Using only a small slice of real traffic, we'll evaluate the extraction quality and the impact on your team.
After that, we'll set out some acceptance criteria for rolling the pipeline out to all your traffic. If you decide it's worth continuing, your team will continue to process documents alongside the pipeline, and we'll measure extraction errors, time spent reviewing exceptions, and any failures during posting. Using that data, you can decide whether to roll out the pipeline across all document types.
How does a rollout work?
As usual, we'll handle it at a pace your team can absorb.
What should I think about for staffing and the operating model?
There's no right answer here, and it's a question of leadership, not automation. Think about the role of your team, and where you want their value to come from. Before we roll out any pipeline, we'll record the exception responsibilities and any role changes. That way, you'll know how your team can create value in the future.
How do commercial terms work?
The audit we just discussed is priced as a fixed fee. The pipeline pricing is based on the work involved, according to the systems you want to use. In addition, running costs will scale with your document volume, and the provider you choose. We'll give you all those costs, and you'll agree them, before you commit.
What's the delivery and ownership model?
We'll build the pipeline using tools suitable for your volume, stack and budget. At the end, YOU own all the code.
What are the next steps?
If your finance team could use a break from data entry, it's time for a data-entry audit. Ask us for one, sending a few representative documents, your monthly volumes, examples of past errors, and the system you're posting to. We'll audit those documents, assessing extraction quality, validation rules, exception volumes and business case.