What an AI integration costs
and how long it takes
Nobody publishes this, so budgeting an AI project feels like guesswork. Here is how the work is actually scoped, what pushes the number up, and what to expect at each size.
The AI is rarely the expensive part. Everything around it is.
People assume the cost of an AI project tracks the sophistication of the model. In practice the model is a small, well-documented piece. The effort goes into reaching your data, mirroring your permissions, handling the cases your process never wrote down, and making the result land somewhere your team already works.
This is why two projects described in the same sentence can differ several times over in price. "Read our invoices and enter them" is four weeks if invoices arrive by email in three formats and your accounting system has an API. It is four months if they arrive by post, and approval depends on rules that live in one person's head.
You cannot get a reliable number without a conversation. But you can understand what drives it, which is enough to sanity-check any quote you receive, including ours.
Where the money and the weeks actually go.
What actually determines the price
Ranked roughly by how often each one turns a small project into a large one. Notice how far down the model choice sits.
- Access to your systems. A documented API is straightforward. A system with no API, or one only a vendor can change, is the single biggest cost multiplier in this kind of work.
- The state of your data. Not whether it is tidy, but whether it is reachable. Content spread across drives, mailboxes and one spreadsheet somebody maintains privately turns into real preparation effort.
- How many exceptions the process has. Every 'except when' adds logic, testing and review design. This is the item most often discovered mid-project rather than during scoping.
- The accuracy you need. Good enough with a person reviewing flagged cases is affordable. Near-perfect and unsupervised is a different project, and often not worth what it costs.
- Regulatory obligations. Audit trails, explainability and documentation are real engineering. If the process is regulated, expect that to be a visible line rather than an afterthought.
- The model and provider. Genuinely a smaller factor than most people expect, and usually an ongoing usage cost rather than a build cost.
Three project shapes, and what each involves
Most integration work falls into one of these three shapes. Identifying which one you are asking for makes any quote much easier to read.
A single workflow, one system
One input, one destination, rules that fit on a page. Two to four weeks. This is the right size for a first project and the only size we recommend committing to before anything has been proven on your data.
A workflow across several systems
Data read from one place, decisions applied, results written to two or three others, with a review queue for exceptions. Six to twelve weeks, usually split into phases with something usable at the end of each.
A department-wide platform
Multiple workflows, multiple teams, permissions, reporting and audit. Months, and it should never be attempted first. Build one workflow, earn the trust, then extend.
The costs that start after go-live
These are modest but real, and they are the ones most often missing from a budget approved by someone who was only shown the build price.
- Model and API usage. Charged by volume of text processed. Predictable once you know your monthly case count, and worth estimating during scoping so nobody is surprised.
- Hosting and infrastructure. Usually the smallest line for this kind of work, but it exists and someone has to own the account.
- Maintenance. Providers deprecate models, your systems get updated, your document mix changes. Something with no maintenance budget will quietly stop working within a year.
- Monitoring and review time. Someone still looks at the flagged cases. That is a feature, not a failure, but it is time and belongs in the business case.
Where the weeks go in a typical project
The build itself is rarely the longest phase. Being aware of that helps you spot a timeline that has skipped something important.
Discovery and mapping
Understanding the process, counting volumes, checking system access. Short, but skipping it is the most reliable way to overrun later.
Data preparation and access
Frequently the longest phase, and almost always the most underestimated. Credentials, permissions, exports and cleaning all live here.
Build and evaluation
The AI work, plus testing against historical cases with known outcomes. Runs faster than people expect once access is solved.
Pilot and tuning
A small group using it on real work while thresholds are adjusted. Do not compress this; it is where trust is either earned or lost.
Hand-off
Documentation, monitoring and a walkthrough. A week that saves months of dependency later.
Why AI projects overrun, and how to prevent it
In our experience overruns are almost never caused by the AI failing to work. They are caused by four things nobody counted.
- Exceptions discovered late. The process turns out to have fifteen special cases rather than three. Prevent it by asking the people doing the work, not the person who owns the process.
- System access taking weeks. Credentials, security review, a vendor who has to enable something. Start this on day one, in parallel with everything else.
- Scope that was never written plainly. If the deliverable cannot be stated in one sentence a colleague could verify, it will be renegotiated mid-project at your cost.
- Accuracy expectations set by a demo. A polished demo sets an unrealistic bar. Establish the real baseline from your own historical cases before anyone forms an opinion.
Timelines by project shape.
| Project shape | Typical timeline | Right for a first project? |
|---|---|---|
| Proof of concept on your own data | 1–2 weeks | Yes, if you need convincing first |
| Single workflow, one system | 2–4 weeks | Yes |
| Workflow across several systems | 6–12 weeks | Only in phases |
| Regulated process with audit requirements | 8–16 weeks | Not as a first project |
| Department-wide platform | Several months | No |
Get a real number for your case.
Describe the workflow and the systems involved, and we will come back with a realistic range and a first phase. The call is free and there is no obligation to build with us. See how we scope integrations or get in touch.