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.

AI Integration for Fintech

Financial products drown in documents, compliance rules, and manual review. I build AI pipelines that automate the tedious parts so your team can focus on the product.

AI integration for fintech means building production AI pipelines that automate document processing, KYC verification, transaction monitoring, and compliance workflows. A 2-week sprint delivers one of these features for €5,000, integrated into your existing stack (Stripe, Plaid, Supabase, PostgreSQL).

The core bottleneck in fintech is not engineering capacity — it is the ratio of documents to humans. A mid-stage payments company processes thousands of invoices, compliance filings, and KYC documents per month. Each one requires reading, extracting data, cross-referencing against rules, and logging the decision. AI does not replace the compliance officer — it handles the 80% of documents that follow standard patterns so the officer can focus on the 20% that actually need judgment.

Problems I solve for fintech teams

Manual document processing costs hours per transaction.

Your team is copy-pasting data from invoices, receipts, and statements into spreadsheets. Every transaction requires manual review that could be automated.

Compliance checks are slow and error-prone.

Regulatory requirements change constantly. Manual compliance review means delayed approvals, missed updates, and audit risk that keeps growing.

Customer onboarding takes days instead of minutes.

KYC and document verification bottleneck every new account. Customers abandon onboarding because they're waiting on manual review that should be instant.

What a 2-week sprint delivers

Each sprint focuses on one high-impact integration. Here are typical fintech deliverables.

Automated invoice and receipt processing — extracts line items, amounts, tax codes, and vendor details from 50+ document formats and maps them to your general ledger codes

KYC document verification pipeline — processes IDs, proof of address, and corporate filings with automated fraud signal detection and configurable approval thresholds

Transaction anomaly detection — flags suspicious patterns across payment flows in real time with explainable risk scores your compliance team can act on

Automated compliance report generation — pulls transaction data, applies regulatory rules, and produces audit-ready reports that cut quarterly reporting time from weeks to hours

Built for regulated environments

Fintech AI features touch sensitive financial data. Every sprint ships with compliance guardrails from day one.

PCI-DSS compliant data handling — card numbers and bank details are never stored in plain text or sent to LLM providers

SOC 2 audit trail — every AI decision is logged with inputs, outputs, and timestamps for regulatory review

AML/KYC regulatory alignment — verification pipelines follow current EU Anti-Money Laundering Directive requirements

Data residency controls — embeddings and vector stores deploy in your preferred region (EU, US, or on-prem)

Tech I integrate with

SupabaseStripePlaidPostgreSQL

Also serving:

Healthcare Legal Tech HR Tech E-commerce B2B SaaS

Automate the boring parts of your fintech stack.

Book a 30-minute call to discuss how AI can automate your document processing, compliance, or onboarding workflows.