Pricing and quotation guide
Data entry automation cost
The cost of data entry automation depends mostly on which approach fits each task. Removing an unnecessary step costs almost nothing. Connecting two systems that both have APIs is a contained piece of work. Redesigning a form so data is captured correctly at source sits in between. Reading documents automatically has set-up costs, often per-page or per-document fees, and continuing review time. Choosing the cheapest approach that solves each task keeps the overall cost down.
This page explains how the approaches compare and how to estimate the value.
Illustrative diagram
Approaches compared
| Approach | Typical cost profile |
|---|---|
| Remove the step | Very low; mainly agreeing the change |
| Connect systems | One-off build, small running cost |
| Capture at source | Form design and integration; low running cost |
| Extract from documents | Set-up, per-document fees and review time |
What drives the cost
- Number of tasks
- Each needs its own design and testing.
- Systems involved
- Systems with good APIs are cheaper to connect.
- Document variety
- Many layouts need more tuning and review.
- Validation rules
- More checks take longer to define and test.
- Volumes
- Drive both fees and the value of automation.
Costs paid to third parties (separate from our fees)
- Document extraction or AI usage fees
- Form or automation platform subscriptions
- Higher system plans for API access, where required
- Staff time for mapping, pilots and review
Extraction tends to be the most expensive of these approaches to run; check whether connecting or better capture could avoid it.
Estimating the value
Use the entry inventory: time per entry, entries per week and errors found later. Multiply time by staff cost for a yearly figure, and estimate the cost of errors, such as wrong deliveries or invoices that need correcting. Set these against the one-off and running costs of each approach. Tasks with high volumes and simple data often pay back quickly; low-volume tasks with complex documents may not be worth automating yet.
Count review time honestly: extraction rarely removes it entirely.
Example: three tasks, three answers
Illustrative example — not a client case study
Situation: A business wants estimates for three entry tasks: web enquiries, supplier delivery notes and weekly timesheets.
- Web enquiries are solved by connecting the form to the CRM, a small one-off cost.
- Timesheets move to a phone form that feeds payroll, removing paper altogether.
- Delivery notes are low volume and vary widely, so extraction is estimated but postponed.
What this shows: Two tasks were automated cheaply, and the costly one was deferred until volumes justified it. This example is illustrative.
Ongoing costs
Fees
- Extraction or AI usage
- Platform subscriptions
People
- Reviewing uncertain entries
- Source owners' time
Upkeep
- Form changes
- New layouts or systems
Comparing quotations
Check whether each quotation considers removing or connecting before extraction, includes validation and a review route, measures a baseline and runs a pilot. Ask how per-document fees are estimated and at what volumes. A quotation proposing extraction for every task may be selling a tool rather than solving the problem.
Phasing the work
Do the cheap wins first: remove unnecessary steps and connect systems that already have APIs. Then improve forms at source. Leave extraction for the tasks that remain, where the case is clearest.
Costs that appear later
Watch for rising extraction volumes, new document layouts from suppliers and changes to forms or systems that break connections. A periodic review of the inventory keeps automation matched to how work is actually done.
The cost of mapping
Mapping entry tasks takes a little time from each team, but it is what makes the estimate trustworthy and often reveals steps that can be dropped for free. It is usually worth doing before any quotation is fixed.
Off-the-shelf capture tool or custom extraction?
Off-the-shelf capture tool
Suits you when
- Common document types such as invoices or receipts
- Integrates with your systems
- You want a ready review screen
Watch out for
- Per-page or per-user fees
- Limited control over unusual fields
- Where documents are processed and stored
Custom extraction
Suits you when
- Unusual documents or fields
- Several destinations
- Specific validation rules
Watch out for
- Accuracy must be measured and maintained
- You maintain it through changes
Forms are often underrated
Improving a form costs little compared with building extraction for the documents it replaces, and it improves data quality for every entry from then on.
Paying for a pilot
A short pilot on one task, run alongside the existing process, costs a fraction of a full rollout and shows real accuracy, time saved and review effort before larger commitments are made.
Questions about data entry automation cost
What drives data entry automation cost?
The approach chosen, systems involved, document variety, validation and volumes.
Which approach is cheapest?
Removing the step, then connecting systems, then capturing at source.
Is document extraction expensive?
It has set-up, often per-document fees and review time.
How is the value of data entry automation estimated?
From entry time, volumes and the cost of errors, using an inventory.
What running costs does data entry automation leave?
Fees, review of uncertain entries and upkeep when forms or systems change.
Where should data entry automation start?
With cheap wins: removing steps and connecting systems.
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