How much does an AI integration sprint cost?

€5,000 flat for a fixed-scope, 2-week engagement. This includes discovery and scoping (days 1–2), implementation in your codebase (days 3–12), and handoff with full documentation, tests, and a walkthrough call (days 13–14). Two weeks of bug fixes post-handoff are also included. Most AI agencies charge €50,000–€300,000+ for comparable multi-month engagements.

What if I need more work than fits in 2 weeks?

Two sprints back-to-back, €10,000 total, 4 weeks of work. Each sprint still has its own fixed scope and deliverable — you see shipped results every two weeks rather than waiting months for one big reveal.

Do you offer hourly billing or retainers?

No. Fixed price per sprint, no hourly billing, no retainers. Fixed pricing forces clarity: we agree on the deliverable before I write code, and there is no incentive to stretch the work.

What if the feature does not meet spec?

I fix it for free until it matches the scoping document, or I refund in full. The delivery guarantee removes the risk of paying for something that does not work.

Why only 2 sprints per month?

Deep focus per client is the main value. Running more than two sprints in parallel means context switching, which hurts quality. If you need to book further out, schedule a call to reserve a slot.

What can an AI integration sprint deliver?

Production-ready features including RAG-powered search over internal data, intelligent document processing, AI-driven classification and summarization, LLM-powered workflow automation, multi-agent systems, and custom AI integrations for your existing stack.

How does the 2-week timeline actually work?

Days 1–2: discovery call and scoping document. Days 3–12: implementation in your codebase with daily async updates, feature in staging by day 8. Days 13–14: handoff with documentation, tests, and a walkthrough call.

How much of my engineering team's time does this require?

Minimal. A 60-minute scoping call on day 1, a 30-minute staging review around day 8, and a 60-minute handoff call on day 14. Roughly 2.5 hours of meetings total, plus async review of code and docs.

How long does it take to add AI features to a SaaS product?

With a structured sprint, production-ready AI features ship in 2 weeks. No discovery workshops, no 6-month roadmaps — just scoped, built, and deployed code.

What tech stack do you work in?

TypeScript and Next.js for the web layer, Python for data and ML pipelines, any modern vector database (pgvector, Pinecone, Weaviate). Compatible with most B2B SaaS stacks. If your stack is not a fit, I will tell you upfront on the scoping call.

Do I need to hire a full-time AI engineer?

No. A fixed-scope sprint lets you ship production AI features without the overhead of hiring. You get production-ready code, documentation, and 2 weeks of post-delivery support — all for €5,000 per sprint.

Who owns the code after delivery?

You do. Everything ships into your repository, branded as your team's code. No recurring fees, no lock-in, no dependencies on me to keep it running.

What happens after the handoff?

Two weeks of free bug fixes are included. After that, the feature is yours to own and extend. If new issues surface months later, you can re-engage me for a small scope or lean on your internal team — the code and docs are written to be maintainable.

How Much Does AI Integration Cost in 2026?

AI integration costs range from €5,000 for a fixed-price 2-week sprint to €300,000+ for a 6-month agency engagement. For most B2B SaaS companies with a defined use case, a €5,000 sprint delivers a production-ready RAG pipeline, agent workflow, or LLM-powered feature in 2 weeks.

If you're a SaaS founder exploring AI features, the first question is usually "what's this going to cost me?" The answer depends entirely on who you hire, how the project is scoped, and whether you actually need what's being sold.

I've been building AI integrations for B2B SaaS products for the past few years. Here's what I've seen across the market — and what I charge.

The typical cost range

AI integration pricing falls into three buckets:

Agencies and consultancies: €50,000 – €300,000+ (industry averages from Clutch and Goodfirms consultancy data)

Large firms typically run 3–6 month engagements. They'll staff a team of 3–5 people, run discovery workshops, produce architecture documents, and eventually build something. The bulk of the cost goes to project management, coordination, and overhead. You're paying for the process, not just the code.

For enterprise companies with complex compliance requirements, this sometimes makes sense. For a 20-person SaaS company that needs a RAG pipeline, it almost never does.

Freelance AI engineers: €50 – €150/hour (Upwork average rates, 2024-2025)

Hourly freelancers can be effective, but the economics are tricky. A mid-level AI engineer at €100/hour working 4 weeks full-time costs €16,000. Senior engineers in Western Europe charge €120–€150/hour (based on 2024 StackOverflow Developer Survey and Honeypot EU Tech Salary Report), putting a month of work at €19,000–€24,000.

The problem isn't the rate — it's the scope creep. Hourly billing incentivizes exploration over shipping. I've seen "2 week" projects stretch to 3 months because there was no pressure to converge on a solution.

Fixed-price sprints: €5,000 per sprint

This is how I work. A 2-week sprint costs €5,000 and delivers one production-ready AI feature. RAG pipeline, agent workflow, LLM-powered classification — scoped, built, tested, and deployed.

The fixed price forces clarity. You and I agree on the deliverable before I write a line of code. If the scope you need is larger, I run two sprints back-to-back at €10K total — not a custom quote.

Why most projects are over-scoped

The biggest waste in AI integration isn't technical — it's organizational. Companies spend €100K+ because they skip the most important step: figuring out what they actually need.

Here's what I see repeatedly:

"We need an AI strategy" — No, you need one feature that solves a specific user problem.
"We want to build our own model" — No, you want to call an API and wrap it in good UX.
"We need a 6-month roadmap" — No, you need to ship something in 2 weeks and see if users care.

Most AI features in B2B SaaS are variations of a few patterns: retrieval-augmented generation (RAG), structured data extraction, classification, or workflow automation. These are well-understood problems. The engineering is straightforward when the scope is clear.

What you actually get for €5,000

In a 2-week sprint at €5,000 flat, I typically deliver:

Architecture and integration plan — How the AI feature fits into your existing stack
Implementation — Production code integrated into your codebase, not a separate prototype
Vector store / embeddings setup — If RAG is involved, this includes ingestion pipelines and search
Prompt engineering and testing — Optimized prompts with evaluation against real data
Deployment and monitoring — The feature ships to production with observability built in

What you don't get: a 40-page strategy document, weekly status meetings, or a Gantt chart. The deliverable is working software.

How to evaluate if you need AI integration

Before spending anything, ask yourself:

Is there a specific user problem? "Our customers can't find answers in our docs" is a real problem. "We should add AI" is not.
Do you have the data? RAG needs a corpus. Classification needs labeled examples. If your data is a mess, clean it up first.
What's the business impact? If the feature doesn't reduce churn, increase activation, or unlock a new pricing tier, it might not be worth building yet.
Can you maintain it? AI features need ongoing tuning. Make sure someone on your team can own it after delivery.

If you answered yes to all four, you're ready. If you're unsure about any of them, a 30-minute conversation can usually sort it out.

The bottom line

AI integration doesn't have to cost six figures. For most B2B SaaS companies, the right approach is a focused sprint that ships one feature and proves the value before committing to more.

The €5,000 question isn't "can we afford it?" — it's "do we know exactly what we want to build?" If you do, two weeks is enough.