What determines the cost of AI development?
Assess AI budgets through data, accuracy, integrations and ongoing operations.
What does it cost to build AI software?
There is no list price, because most of the cost lives in your data and your existing systems, not in the model. A defensible estimate comes from five questions — data scope, document quality, legacy integration, accuracy targets and support — and it should arrive as a range with stated assumptions, not a single number.
Why AI work resists a fixed quote
A website can be estimated from screens and features because the work is visible before it starts. An AI system cannot, because much of the effort is finding out what the data contains: which formats, which exceptions, which pages are missing, and which digital archive is a folder of photographs.
A quote produced before anyone opens the documents is padded or wrong. Experienced vendors handle this the same way: a short discovery phase that produces a measured baseline on a sample of your documents, followed by a fixed-scope build.
Two projects that sound alike can differ widely in effort. One has clean PDFs and an API to the system of record; the other has scans from three offices and no export at all. The second is a harder data problem, not a harder model problem.
The five cost drivers
Data scope
How many document types, languages, sources and formats, and how many people need access. Variety matters more than volume in the early stages: ten thousand pages of one form are easier than two hundred pages across forty forms. Every source adds a connector, a permission rule and its own edge cases.
Document quality
Scans, photographs, stamps, handwriting, duplicates, missing pages, inconsistent naming. Poor input raises recognition and review effort before any model is trained, and it is a common reason an estimate moves. Ask for a sample audit before the build starts.
Legacy integration
Where the answer has to appear: an ERP screen, a CRM record, an intranet page, a LINE thread, a government portal. Authentication, permission mapping and the absence of an API usually cost more than the model. If the system of record is on-premise and owned by another department, add coordination time.
Accuracy targets
"Good enough" is not a specification. Decide which fields must be exact, which can tolerate review, what an error costs in each direction, and who checks the output. The final margin of reliability usually comes from process — review queues, validation rules, fallbacks — rather than from a larger model.
Support and running cost
Monitoring, drift checks, prompt and model updates, re-indexing when documents change, a review queue for low-confidence output, and someone to call when it breaks. Inference is one line on the bill; the surrounding operations are the rest. Decide up front whether you will run this in-house or keep a support agreement.
A decision table for early budgeting
| If this describes your situation | What will dominate the budget | What to ask for before signing | |---|---|---|
| Documents arrive as scans from several offices | Recognition and human review | A field-level accuracy test on a sample of your own pages |
|---|---|---|
| A few fields must be exact, others can wait | Review workflow and test set | Per-field targets and a defined escalation path |
| One team, one language, one document type | Pilot scope and evaluation | A fixed-scope pilot with a measurable exit criterion |
| Personal or regulated data is involved | Hosting, access control and audit | A data-flow diagram showing where text is processed and stored |
Read it as a map of where to look, not as a price list.
Five questions to ask a vendor
- What do you need to see before you can give a firm number, and what will you do if those samples turn out worse than expected?
- How will you measure accuracy, on which documents, and who produces the reference answers?
- What does the user see when the system is wrong, and who reviews it?
- What do we own at handover — code, prompts, index, evaluation set, documentation, cloud accounts?
- What will this cost to run each month, and which parts of that bill are ours?
Specific answers describe a process; adjectives describe a hope.
Three red flags
A price before samples. If a firm number arrives before anyone has looked at your documents, it is a guess with a deadline attached. Expect a range first, then a firm quote after discovery.
An accuracy promise with no test set. A percentage means nothing without the documents, the field definition and the measurement method. Ask what it was measured on, and whether you can reproduce it.
No handover plan. If the index, prompts and evaluation set stay with the vendor, you are renting the system, not buying it. Ask what happens on the day you leave.
FAQ
Can you estimate a project from a description alone?
A range, yes, with the assumptions written down: document types, sample size, integration points and the accuracy target. It narrows sharply once we have seen sample documents, and we would rather explain why it moved than defend a number we invented.
Is a lower day rate always cheaper?
No. A low rate applied to rework and coordination is expensive, and the hours your staff spend checking output rarely appear on the invoice. Compare the total cost of a working, supported system.
Does a hosted model make the project cheaper?
It removes infrastructure work and adds a per-call running cost. Whether that is cheaper depends on volume, latency and where your data may go, which is why running cost belongs in the first conversation.
Next step
Bring a sample of the documents and a description of where the output has to appear. We will tell you what we can measure, what we cannot promise, and where the risk sits. Start at seansolution.tech/contact, or reach us at [email protected], +66 94-865-9978, or LINE lin.ee/WQlPJc5.
SEAN SOLUTIONS CO., LTD., Thailand (DBD 0115565023334): 12+ projects, clients in 2 countries.
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