What does AI integration in your existing product cost?
Integrating an AI feature into an existing system or product typically costs SEK 200,000–1 million per feature. The price is driven by production-quality requirements: latency, error handling, fallback, and per-user cost caps. The model choice via API affects both operating cost and legal exposure, for example where the data is processed.
Many companies aren’t facing the question of “introducing AI” – they already have a product or a business system and want to add an AI feature to it: smart search, automatic summaries, suggested replies, categorization. That’s usually a smarter path than building from scratch, and the price tag is manageable: typically SEK 200,000–1 million per feature.
Pricing by feature type
| Feature type | Typical cost | Example |
|---|---|---|
| Standalone feature | SEK 200,000–400,000 | Summarizing cases, generating drafts, categorizing incoming items |
| Feature with a data connection | SEK 400,000–700,000 | Smart search or Q&A over the product's own data |
| Deeply integrated feature | SEK 700,000–1,000,000 | An AI assistant inside the product that acts on the user's data across multiple flows |
The lower end of the range assumes your product has a modern API layer and that the feature can be clearly scoped. If the data model needs to be reworked or permissions need to be extended, you’ll land higher.
The difference between demo and production – that’s what you’re paying for
Getting an AI feature working in a demo takes days. Making it production-ready is most of the project, and that’s where quotes differ. Four things decide it:
- Latency. A demo can take eight seconds; a feature in your product can’t. Production solutions use streaming responses, preloading, and sometimes a faster model for the most common cases.
- Fallback. What happens when the model vendor has an outage or responds slowly? A production feature has a backup path: another model, a cached answer, or a clear degradation – not a spinning loader.
- Error handling. Models sometimes give unusable answers. Production code validates the answers, retries with an adjusted prompt, and knows when to give up and show an honest error message.
- Per-user cost cap. Without a cap, a single heavy user – or a script – can run away with the operating cost. Quotas and alerts per user need to be in place from the start.
A quote that doesn’t mention these four points is pricing a demo, not a feature you can launch to customers.
Model choice via API: price and legal exposure in the same decision
Most integrations call a model via API instead of hosting their own – the right choice for almost everyone. But which model and vendor you choose affects two things at once:
Price. The difference between model tiers is often a factor of ten or more per call. A feature used thousands of times a day can cost a few hundred kronor or tens of thousands of kronor a month depending on the model choice – so always evaluate whether a cheaper model is enough for your specific task before you lock in a top-tier model.
The legal side. Where is the data processed? Is it stored? Is it used for training? The answers differ between vendors and contract tiers. For features that handle personal data, you need a data processing agreement and a handle on third-country transfers under GDPR; EU hosting or European operating options can be a requirement rather than a preference. It’s cheaper to choose right from the start than to migrate after an objection from your data protection officer.
Also build in swappability: prompts, model choice, and parameters should sit in their own layer so you can switch models when the pricing or the requirements change. It costs a little extra to build but pays for itself the first time a new model generation halves the price – or when the legal situation requires a switch.
A concrete scenario
A SaaS company with a case management system wants to add “suggest a reply” for its customers’ support teams. The feature is scoped to a button in the existing interface, using the product’s own case history as source material. The build – prompt design, data connection, streaming responses, fallback, cost caps, and evaluation against historical cases – comes to roughly SEK 500,000 and three months. Operating cost is forecast per customer and priced as a premium add-on, which makes the feature self-funding.
Do you have a product and an idea of what AI could do inside it? At Weapp we have deep experience with both system development and AI integrations – get in touch and we’ll talk through scope and price.
Frequently asked questions
Do we need to rebuild our system to add AI?
Rarely. Most AI features connect via API calls from your existing code, much like a payment service or a map component. What can require work is the data layer – the feature often needs access to the right data in the right format – along with the interface where the feature will live.
How long does it take to launch an AI feature?
A well-defined feature in an existing product typically takes 6 weeks to 4 months from start to production, depending on integration depth and testing requirements. The actual AI call is often in place in the first week – the rest is production quality: error handling, testing, monitoring, and polishing the experience.
What does the AI feature cost to run per user?
It depends on how often the feature is used and which model it calls. Work out an expected cost per active user per month based on typical usage, and build in a per-user cost cap. Without a cap, a small group of heavy users can end up accounting for most of the bill.
Can we switch AI models later without rebuilding?
Yes, if the solution is built with an abstraction layer where the model choice, prompts, and parameters are swappable. Require that in the order. The model market moves fast, and the ability to switch to a cheaper or better model is worth a lot over the feature's lifetime.
What happens to our customer data when it's sent to an AI model?
That's governed by the contract with the model vendor: where the data is processed, whether it's stored, and whether it's used for training. Reputable vendors offer business terms where data isn't used for training. Review the terms, sign a data processing agreement where required, and document the flow under GDPR.