AI Integration Cost Calculator (2026)

How this estimate is built

The calculator adds nothing you can't see. The range is the base range for the complexity you pick, plus the features you tick, multiplied by the factor for where the team is based. Results are rounded to the nearest $500.

Example: a Standard project with no extra features, built by a team charging the global average, comes out at $12,000 – $45,000. The same project with all six features, Complex scope and a North American team comes out at $83,000 – $276,000.

The ranges are Vitasoft’s own editorial model, not quotes from vendors. We publish every number so you can check the model against market data and against the proposals you get.

What the estimate covers, and what it leaves out

It covers the build: scoping, the integration work and the features you tick. It doesn’t cover what the feature costs to run once it’s live. For an LLM feature, that’s usually four separate lines:

• model usage, billed by the provider per token
• hosting for anything you run yourself, such as a vector database for a knowledge base
• monitoring and logging
• people’s time to review outputs and fix the cases the model gets wrong

Ask any vendor to quote build cost and running cost on separate lines. A single number hides the part you’ll pay every month. How to evaluate an AI vendor covers what else to ask for before you sign.

How to estimate the monthly model bill

Providers price models per million tokens, with input and output priced separately (Anthropic, Google Gemini). Prices differ by model and change often, so take them from the provider’s page on the day you estimate.

The arithmetic fits on one line:

monthly cost = requests per month × (input tokens per request × input price + output tokens per request × output price) ÷ 1,000,000

A worked example with made-up prices, to show the method only: 20,000 requests a month, each sending 2,000 tokens and getting 500 back, is 40 million input tokens and 10 million output tokens. At a hypothetical $1 per million input and $5 per million output, that’s $40 + $50 = $90 a month. Run the same sum with the real price of the model your vendor proposes, and ask them how they measured tokens per request. A knowledge-base assistant that pastes long documents into every prompt sends far more input tokens than a short classifier does.

How the ranges compare with market data

Clutch puts the average AI development project at $120,594.55, with 10 months as the typical timeline, based on client reviews on its site (Clutch, updated September 21, 2026). That’s an average across every project reviewed there, so it doesn’t map onto one row of the table above. At global average rates, our model reaches that figure only once several features are added.

Our timelines run shorter than Clutch’s typical 10 months. If a vendor quotes a longer schedule, that alone isn’t a warning sign. Ask what happens in each month.

Using the estimate with a real quote

Line up the vendor’s quote against the feature rows above. A quote that bundles everything into one figure is hard to compare and hard to cut later. Ask which features could wait for a second phase, and check which pricing model the quote uses: vendor pricing models compared explains what fixed price, time and materials, and retainers each reward. Then compare AI integration companies in our rankings.