Automate
Data Entry
For Good.
Manual data entry creates delay and hidden checking work across finance and operations. We build a controlled pipeline that extracts the fields, validates them against business rules and sends uncertain cases to the right person.
61%
WORK ABOUT WORK, ASANA UK 2021
6 Apr 2026
HMRC MTD FOR INCOME TAX PHASE 1
One input type
THROUGH TO THE TARGET SYSTEM
What traditional RPA misses
For years the answer to manual data entry was RPA: record the clicks, hard-code the field positions, hope the supplier never changes the invoice template. UiPath, Blue Prism and Automation Anywhere made that category mainstream.
The problem: brittle flows fail when the input changes. A bank tweaks a statement layout, a supplier adds a column, a PDF gets re-exported, and the ops team's back in the queue.
Modern extraction works from the document content, not one fixed screen path. Structured data, confidence per field, and a hand raised when it isn't sure.
OLD-SCHOOL RPA
- One template, one bot, one supplier
- Breaks the day a column moves
- Can't read handwritten notes
- Maintenance eats the savings
- Confidence: it ran, or it didn't
AI EXTRACTION
- Handles layout and wording changes
- Works from content, not pixel positions
- Reads scans, photos and clear handwriting
- Corrections feed prompts, rules and tests
- Confidence per field, escalates the rest
How reliable data entry automation works
Invoices, orders, expense receipts, supplier onboarding packs, KYC documents, claim forms. The document changes. The pipeline doesn't.
Intake
Inbox, shared drive, supplier portal, scan-to-email, WhatsApp from the field. Whatever you've already got. We don't change how documents arrive.
Read
Parsing layer first (Reducto, Google Document AI or Amazon Textract, depending on volume and document type), then an LLM that pulls the structured fields you care about.
Validate
VAT numbers checked against HMRC, totals reconciled, supplier matched, duplicate guard. Anything dodgy is flagged before it gets near your ledger.
Human gate
Low confidence or above a threshold? It lands in a one-screen review queue. Two clicks to approve or correct. Corrections feed the next pass of rules, prompts and tests.
Post
Straight into Xero, QuickBooks, Sage, NetSuite, Salesforce, HubSpot, your bespoke ERP, or the spreadsheet we'll eventually replace. Whatever you already use.
Documents and forms we automate
If a person on your team is typing it in today, we can probably automate it. These are common starting points.
Supplier invoices
PDF, scan or photo. Line items, VAT, PO match, supplier lookup. Posted into Xero, Sage, QuickBooks or NetSuite with a trail.
Sales orders
The orders customers email you as PDFs or in the body of an email. Read, validated against your catalogue, dropped into your ERP.
Expense receipts
Photographed on a phone in a taxi. Date, supplier, VAT, category. Right currency, right project, right approver.
KYC / onboarding
Passports, utility bills, certificates of incorporation, bank statements. Extracted, screened, filed under the right entity.
Delivery notes
Three-way match against PO and invoice. Shortages flagged, dates captured, photos kept against the record.
Insurance & claim forms
First-notice-of-loss, repair quotes, supporting photos. Pulled into your claims system with the right policy attached.
Inbound email triage
A shared inbox where every message becomes a ticket, a CRM update, a calendar event or a reply. Read, classified, routed.
Referral & intake forms
For clinics, agencies, advisers. The forms you get from clients or partners that someone re-keys into your system. Read in the format you got them.
How we take it into live use
Audit, build, hand back. Fixed-scope phases, one document type first, your team trained on the review queue before we leave.
We don't sell you a platform. We build it on the tools that fit your volume, your stack and your budget, and you own the code at the end.
BOOK A DATA ENTRY AUDITData entry audit
Send us 30 real documents and a 15-minute Loom of how they're processed today. We come back with what to automate first, what to leave alone, the rough cost, and the rough payback. One page, no decks.
Pilot on one document type
We pick the highest-volume document and build the full pipeline for it. Intake, read, validate, gate, post. It runs on a small slice of real traffic so you can compare it to the person doing it today.
Ramp and evaluate
We run it side by side with your team until the accuracy numbers say it's ready. You see the per-field confidence, the disagreement rate, the time saved. Then we cut traffic over.
Add the next document type
The plumbing's done. Adding sales orders after invoices, or claim forms after KYC, reuses the same intake, review and posting pattern. You roll on at the pace you can absorb.
How we handle uncertain fields
A model output is a candidate value, not a fact. Confidence checks and review rules keep bad data away from the ledger.
Confidence per field
The pipeline records confidence for each value. A reliable total can post while an uncertain date goes for review.
Thresholds you control
You decide what auto-posts, what needs a glance, and what needs a manager. Different rules for £50 receipts and £50,000 invoices. We tune it with your finance team.
UK GDPR & automated decisions
Where automated decisions could have legal or similarly serious effects for a person, the UK GDPR automated decision-making rules and the Data (Use and Access) Act 2025 matter. We design those paths with human review and a written DPIA.
UK / EU data residency
We default to UK or EU hosting and to model providers with no-train commitments. If your data can't leave the UK, we'll tell you what's possible and what isn't.
Full audit log
Every document, every extracted value, every human override, kept and queryable. When the auditor or HMRC asks how that number got into the ledger, you can show them.
Corrections become tests
When your team corrects a value in the review queue, we turn the example into a regression test or extraction rule. The same failure gets checked before the next release.
Choosing the right extraction tool
Gartner published its first Magic Quadrant for Intelligent Document Processing Solutions in September 2025. Forrester's closest recent Wave is Document Mining and Analytics Platforms, Q2 2024. Useful context, but not a shopping list. Tool choice depends on volume, document type and where the data has to go.
PARSE & OCR
For the read layer
Reducto, LlamaParse, Mistral OCR, Unstructured, Azure Document Intelligence, AWS Textract, Google Document AI. We choose per document type and volume.
EXTRACTION LLMs
For the judgement layer
Claude Sonnet, Gemini and GPT-class vision models, routed by document type, cost and confidence. No default vendor because there isn't one.
ENTERPRISE IDP
When that's the right fit
Established options include ABBYY Vantage, Hyperscience, Rossum and UiPath Document Understanding. We compare their supported documents, integrations, review tools, data terms and cost with a focused custom pipeline.
Leo Associates saves around 45 hours a month
Supplier quotes arrive in different formats. The platform extracts and categorises the data before it enters the project and finance workflow, removing a large manual entry job without replacing the systems around it.
When this is worth discussing
We work best when there is a real operating problem, enough volume to measure and people from the affected teams who can make decisions.
Usually a good fit
- An established UK business, usually with annual revenue above £10m
- A repeated process with a known cost, delay, error rate or capacity problem
- A senior sponsor and a day-to-day owner who understand the work
- Access to the relevant staff, systems, sample records and security requirements
We may point you elsewhere
- A standard product already covers the process well
- The requirement is a one-off small build with no wider operating case
- There is no owner or access to the people and data needed to test the result
- The plan relies on AI making high-impact decisions with nobody responsible for review
Questions before connecting the systems
How accurate is it really?
On clean invoices and orders, the read layer usually handles the headline fields well. Scans, photos and complex multi-page documents need more checking, which is why every field has a confidence score and anything below your threshold goes for human review. The right question isn't "is the AI perfect" but "is the whole pipeline more accurate than what we do today", and that one we answer with numbers from your pilot.
Do I have to fire anyone?
The operating model is a leadership decision, not something the software should imply. Before rollout, we record who will handle exceptions, how roles change and whether the expected value comes from capacity, service, accuracy or a staffing plan.
What about hallucinations? Making up numbers?
Fair worry, and the right way to handle it isn't to trust the model. We treat extracted fields as candidates, not facts. Totals are recomputed from line items. VAT is checked against HMRC. Suppliers are matched against your master list. Anything that doesn't reconcile gets surfaced before it posts. The model can be wrong; the pipeline catches it.
Where does our data go?
Default is UK or EU hosting, with provider terms checked before build. If you've got tighter constraints (financial services, healthcare, anything FCA or NHS-touching), we'll design around them and write it down in a DPIA. If nothing can leave your tenancy, we'll tell you which providers can run that way and what it costs.
Would our existing automation platform be enough?
Use what you've got where it earns its keep. RPA is fine for the deterministic bits, click here, copy there. The reading and the judgement are where AI extraction is a step change and where the RPA bots tend to break. We're happy plugging an extraction service into your existing UiPath or Power Automate flow rather than replacing it.
How much does it cost?
Audit is a fixed fee. A first pilot pipeline is priced per phase, scoped against how many systems it has to talk to. Running costs scale with document volume and provider choice. We tell you both numbers before you commit.
Will it work with our weird internal system?
Probably. If it has an API, we connect to it. If it has a database, we write to it. If it has neither, we'll either build the connector or, more often, replace the weird internal system with something proper while we're there. That's the day job.
What if Making Tax Digital is what's prompting this?
Good timing. MTD for Income Tax applies from 6 April 2026 to sole traders and landlords with qualifying income above £50,000, with the £30,000 threshold following from 6 April 2027. If you're doing the bookkeeping for clients in that range, automated intake of receipts and invoices is one way to absorb the extra workload without hiring.
Talk to us about your data entry
Send us representative documents, monthly volumes, error examples and the destination system. We will assess extraction quality, validation rules, exception volume and the likely business case.