How Much Does AI Automation Cost?

For a fixed-price studio model like ours, a single-workflow automation — one agent, one clear task, one or two system integrations — typically runs $2,500 to $8,000. This covers most of what shows up on our individual service and use-case pages.

Multi-system builds, compliance-sensitive industries (legal, financial services, insurance), or projects requiring deeper data integration and validation typically run $6,000 to $15,000+. The jump usually comes from integration complexity and the testing rigor a higher-stakes use case demands, not from the AI component itself being more expensive.

Ongoing platform usage (if you're also using Blockium Labs' hosted tools, not just a custom build) runs separately on a subscription — Free, $49/mo, or $199/mo depending on usage volume, which is unrelated to a one-time project's build cost.

A useful sanity check before committing to any quote, from any vendor: ask what happens if the real scope turns out to need more integration work than expected once the project is underway. A credible fixed-price quote will tell you upfront whether that triggers a separate change order or was already padded into the number — leaving it ambiguous until mid-build is where a lot of budget surprises actually come from.

What actually determines the right call.

How many systems does it need to touch?

Each additional system integration adds real scoping and testing time — this is usually the single biggest cost driver.

How much judgment versus fixed rules is involved?

Fixed-rule automation is cheaper to build and test than something requiring nuanced judgment calls and extensive guardrail design.

What industry-specific requirements apply?

Compliance-sensitive industries add real scoping, access-control, and review time beyond the core engineering.

How much of your process is already documented?

A well-documented existing process scopes faster than one we have to reverse-engineer from scratch during discovery.

Is this a net-new build or an extension of existing work?

Extending something we or you already have in place is usually cheaper than starting from a blank page.

Common questions.

Why won't you just give me one number?

Because an honest number requires knowing what you're actually automating — the same category of project can genuinely cost 3x more or less depending on integration count and complexity.

Is there a minimum project size?

No formal minimum, but very small, one-off automations sometimes aren't worth custom development cost-wise — we'll tell you honestly if that's the case for your situation.

Do you charge hourly or only fixed-price?

Fixed-price only, scoped after discovery — you know the number before any code is written, with no surprise hourly overage.

What drives cost up the most?

System integration count and complexity, by a wide margin — a simple AI layer connected to one system is cheap; the same AI layer connected to five legacy systems is not.

Are there ongoing costs after the initial build?

The build itself is one-time; ongoing costs (if any) depend on what infrastructure the system runs on and whether you want continued support — we scope that separately and transparently.

How does this compare to hiring a full-time AI engineer instead?

A full-time hire makes sense if you have ongoing, continuous AI engineering needs. For a specific, bounded project, a fixed-price build is almost always cheaper and faster to get running.

Can a project's price change mid-build?

Not for the agreed scope — if new requirements come up during the build, we treat that as a separate, clearly priced addition rather than silently expanding the original quote.