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AI data analyst
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AI Data Analyst in Vienna

The best AI Data Analyst in Vienna, 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.

Vienna combines a large public and international sector, banks with networks across Central and Eastern Europe, a strong life sciences cluster and a growing startup scene backed by public funding agencies. Much of Austria's economy is made up of established, often family-owned industrial and service companies that buy carefully, value privacy and expect a supplier to explain exactly where data goes.

Industrial and service companies in Vienna keep years of orders, production and finance data in ERP systems. An analyst on a read-only replica answers questions in German or English, with the SQL shown and every query logged.

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.

Vienna, Austria

Who builds here

Banks with Central and Eastern European networksVienna BioCenter and life sciencesTU Wien and the University of ViennaInternational organisations, including the UN in Vienna
Best fit in Vienna

AI Data Analyst

Vienna's established companies have years of data in ERP and operational databases and few people who can query it. An analyst on a read-only replica inside their own environment gives answers quickly while keeping data where Austrian buyers expect it to stay.

You are on it
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 Vienna

What actually applies here.

Regulation and data

GDPR is enforced by the Austrian Data Protection Authority (Datenschutzbehörde), and Vienna is home to noyb, the privacy group founded by Max Schrems, whose cases shaped EU rules on transfers of personal data to the United States. Austria's NIS2 law, the NISG 2026, was adopted in December 2025 and applies from 1 October 2026, with a new Federal Office for Cybersecurity. Banks and insurers answer to the FMA, and DORA has applied to them since January 2025. RTR runs an AI service desk that advises on the EU AI Act, while Austria's formal designation of AI Act supervisors was still under discussion at the time of writing. Most EU AI Act high-risk duties are now due from December 2027.

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.

Is the NISG 2026 relevant to our AI project?

If your company is in scope of Austria's NIS2 law, from 1 October 2026 your suppliers fall under its supply chain security rules. We work with named access, infrastructure in your accounts and documented controls, which is what your NIS2 assessment of a supplier will look for.

Can answers come back in German?

Yes. Users can ask in German and receive answers in German, while the SQL, logs and technical documentation stay in English. We test German-language questions with your team before handover.

What overlap do we get with Vienna hours?

Four or more hours of daily overlap across your morning, Central European time, with same-day replies on working days. That leaves room for a weekly review with your team and quick calls whenever a decision is needed, all inside your normal morning.

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.