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AI data analyst
Nederlands

AI Data Analyst in Amsterdam

The best AI Data Analyst in Amsterdam, at the best available price.

$0 upfrontPay per accepted checkpointSenior engineer, no agency markup

Your team asks in English. The service finds the tables, writes the SQL, runs it against a read-only replica inside your own cloud, and returns the number with the query attached. It cannot touch a table whose schema it has not just read, and that is enforced in code rather than requested in a prompt. Starts at $0: you pay at checkpoints you accept.

Amsterdam is one of Europe's most international business cities, with payments and fintech, travel technology, and the European headquarters of many non-EU companies. English is the working language in most tech teams, and buyers are direct, quick to evaluate and comfortable with remote suppliers. The Dutch market takes data protection and algorithmic accountability seriously, and buyers expect it to be designed in.

Marketplace and travel teams in Amsterdam ask fast-moving questions about bookings, conversion and payments. A read-only analyst answers them in plain English with the SQL shown, so analysts can review the logic.

What you get

  • Deployed in your own cloud account against a read-only replica you create, so we never hold a credential to your database
  • A signed schema check the model cannot skip: no SQL runs against a table it has not just inspected, and the tokens expire in fifteen minutes
  • A grant list your data owner approves, naming the exact tables and columns the analyst may read, with everything else refused at the database
  • Exposed inside Claude or ChatGPT in your organisation's workspace, behind your existing Google sign in, so nobody learns a new interface
  • Every question logged with the SQL it ran, the tables it touched and whether it errored, which is what an auditor actually asks for
  • Runs on a private LLM on your own hardware where data security demands it, up to fully air-gapped, so nothing at all crosses your perimeter
Builds from $6,000. Assessment fixed fee, credited in full.

No payment before a checkpoint is delivered and accepted. Most builds land between $6,000 and $18,000 depending on how many databases are in scope and how much of the schema the first domain covers. Optional upkeep from $1,200 a month, and only if you want it.

Invoiced in USD or EUR, payable by Wise or bank transfer.

Request a callback

You speak to the engineer who does the work. No sales rep, no deck.

No spam and no sales team. You talk directly to Neeraj.

Amsterdam, Netherlands

Who builds here

Payments and fintech, including AdyenTravel and marketplace technology, including Booking.comThe Zuidas financial and legal districtAMS-IX and Amsterdam Science Park
Best fit in Amsterdam

AI Development Company

Amsterdam's fintech, travel and platform companies are ready to ship AI features to customers, and they want them built with the accountability Dutch regulators and works councils expect.

Try a question
1Question

How many free signups from June converted to paid, by week?

2Schema read
customers

plan tier is a column here, not a separate status table

subscriptions

one row per plan change, so take the first paid one

Schema proof issued, expires in 15 min
AQIAaPr2xQAAAACqL3d1Zw
3Verified SQL
SELECT DATE_TRUNC('week', s."startedAt")
         AS "Week",
       COUNT(DISTINCT c.id) AS "Converted"
FROM   customers c
JOIN   subscriptions s
         ON s."customerId" = c.id
WHERE  c.plan = 'free'
  AND  s.plan = 'paid'
  AND  c."createdAt" >= DATE '2026-06-01'
  AND  c."createdAt" <  DATE '2026-07-01'
GROUP  BY 1 ORDER BY 1
WeekConverted
2026-06-01214
2026-06-08188
2026-06-15243
2026-06-22201

Stage three refuses to run unless it is handed a valid token from stage two for a table in the query. The model cannot skip the schema read, because the check is a signature in code rather than an instruction in a prompt.

Architecture diagram of an AI data analyst that can only read: a question asked in Claude or ChatGPT goes to an MCP server running in your cloud, through a semantic layer of your metrics and definitions, into generated SQL, then a validation step that enforces read-only access, row limits and cited numbers, before it reaches a read-only replica. The answer returns with the numbers cited, and a write is refused by the database itself.
Every answer comes from a read-only replica through a validated query, with the numbers cited.
How you pay

Get it built at $0.

That is not a discount. It is when you pay. The work is split into checkpoints with acceptance criteria written down before anything starts, and each checkpoint is invoiced only after you have seen it and accepted it. No deposit.

$0 to start
You hold every dollar until a checkpoint is delivered and you accept it. No approval, no invoice.
Fixed cost, unlimited features
Or hire the team outright: one fixed monthly cost, unlimited feature development, any stack.
The engineer takes your call
The person on your first call is the one who architects and writes it. No account managers, no bench time.

A US agency quotes $50,000 to $150,000 for the same build and asks for 40 to 50% of it before a line is written. Account managers, project managers, sales commission and bench time. None of it appears in your product.

How it works

Three stages, nothing hidden.

01

Fixed-fee assessment

Five business days from the day read-only access is in place. Schema inventoried, the questions your team actually asks classified as answerable or not, the grant list drafted with whoever owns data protection, and acceptance criteria written as testable statements.

02

Build in checkpoints

About three weeks. Deployed in your cloud account, connected to your replica and to your assistant workspace, with the semantic layer written for the first domain. Each checkpoint has criteria agreed before work starts and is invoiced only once you accept it.

03

Handover and closeout

A real question from your team, answered end to end, with the SQL shown and the numbers reconciled against the source rows. Runbook, recorded handoff, code and semantic layer in your repository, and all our access removed with written confirmation.

Working in Amsterdam

What actually applies here.

Regulation and data

GDPR applies with the Dutch implementation act (UAVG), supervised by the Autoriteit Persoonsgegevens, which also coordinates algorithm and AI supervision in the Netherlands. Banks, insurers and payment institutions are supervised by De Nederlandsche Bank and the AFM and have applied DORA since January 2025. Under Article 27(1)(l) of the Works Councils Act, a works council must consent to systems capable of monitoring employees' presence, behaviour or performance, which can include AI tools. The Dutch NIS2 law, the Cyberbeveiligingswet, took effect on 15 August 2026. The Dutch AI Act implementation bill was still in preparation in 2026. The EU AI Act has been in force since August 2024: general-purpose model rules applied from August 2025 and transparency duties from August 2026, while the 2026 Digital Omnibus moved the main high-risk obligations to December 2027 for stand-alone systems such as hiring or credit scoring, and August 2028 for AI built into regulated products.

Contracting and payment

You contract with an individual consultant based in India. Invoices in EUR or USD, paid by Wise or bank transfer. Your accountant handles an overseas supplier in the usual way, and any documentation they need is provided before access is granted.

Working hours

Four or more hours of daily overlap across your morning, Central European time, with same-day replies on working days.

Do you work with Dutch works council requirements for AI tools?

We document what the tool does, what it logs and who can see it, which is the material a works council needs to consider a request for consent. The consent process itself belongs to you and your works council, and we can adjust logging to fit what is agreed.

Can our data stay in the Netherlands or the EU?

Yes. Deployments go into an EU region of your own cloud account, including Dutch regions where your provider offers them, or onto your own hardware. Models run there too, so data does not leave that boundary.

We already have a BI tool. Does this replace it?

No, and it should not. Your dashboards answer the questions somebody anticipated, and they will keep doing that. This answers the ones nobody built a chart for, which is where the waiting happens. Teams that keep both end up using the dashboards for the standing numbers and the analyst for everything else.

How long before somebody can ask a real question?

Usually inside the first week of the build, on a narrow slice of the schema. The first domain being useful early is the point of doing it in checkpoints: you see it working on your own data before most of the money is committed.

What if our schema is a mess?

Most are, and it changes the shape of the work rather than ruling it out. Undocumented columns, legacy tables nobody dares delete and two spellings of the same idea are normal. The assessment tells you plainly how much of that has to be untangled first, and if the answer is that you need a data cleanup before an analyst is worth building, you will be told that instead of sold this.