Free GDPR assessments that find what you didn't know to ask

Better than an AI chat

A chat answers the question you ask and builds on your assumptions. NyTid asks the questions you didn't think of, tests your assumptions against the law, and gives you a document you can show your data protection authority.

Better than starting with a lawyer

A business lawyer charges around €350 an hour, also for finding out what you need. NyTid does that groundwork for free, so your lawyer only has to review and approve.

AI speed, a lawyer's method, and a lawyer's final say.

Free · About 15 minutes · Built on EDPB Guidelines 1/2024

See what's included ↓
NyTid · AssessmentDemo

How NyTid compares

AI chat (ChatGPT, Claude)

Cost
Free or low cost
Finds what you didn't ask about
No, answers what you ask
Tests your assumptions
Often builds on them
Checks every required point
Can miss points
Checks your policies
Only what you paste in
Document for your data protection authority
No
Final legal approval
No

Lawyer

Cost
Around €350 per hour
Finds what you didn't ask about
Yes
Tests your assumptions
Yes
Checks every required point
Yes
Checks your policies
Yes, billed by the hour
Document for your data protection authority
Yes
Final legal approval
Yes

NyTid

Cost
Free
Finds what you didn't ask about
Yes, guided questions for each purpose
Tests your assumptions
Yes, checks each legal basis against the law
Checks every required point
Yes, point by point with the article
Checks your policies
Yes
Document for your data protection authority
Yes, dated, versioned and ready to sign
Final legal approval
Send to a lawyer (coming soon)

Sources: Alrajeh, Do LLMs Fabricate Legal Citations? (2026), on national data protection law; study of LLM-written privacy notices under GDPR Articles 13–14, University of Michigan (2026); study of legal AI systems on false-premise questions, arXiv (2026); Luleå District Court on reasonable hourly fees (4,000 kr, about €350), reported by Realtid (July 2026).

Built on how the law is actually applied

Every assessment follows the method in the EDPB's guidelines on legitimate interest. NyTid uses AI to write the draft, but only inside this structure and only with approved sources.

  • EDPB Guidelines 1/2024: the three-step test for legitimate interest
  • The GDPR and the EU AI Act, with links to the article behind each conclusion
Built on

GDPR · EU AI Act · EDPB guidelines · ICO guidance · EU data protection authorities

How it works

  1. 01List what you use personal data for.
  2. 02Answer questions about each purpose. Tap the question mark if a word is unclear, or ask NyTid.
  3. 03NyTid checks your privacy policy and other documents against what the law requires.
  4. 04You get the assessment, a list of what's missing and a to-do list.
  5. 05Send it to a lawyer for review. (Coming soon)

An example report

This is what the first part of a report looks like for a company training a support chatbot on old tickets.

How to read this

Demo · not legal advice

Legal position as of today · Draft for legal review

MEDIUM RISK, You can probably do this, but not yet. Three things need fixing first.

GDPR: Proceed with safeguardsAI Act: Limited risk · ProviderAutomated decisions: Not applicable

Using support tickets to train your own AI assistant

In short

You can probably use past support tickets to train your assistant. First, tell your customers and give them an easy way to say no. Right now you do neither.

What we relied on

You told us: the tickets come straight from your customers; you first collected them to give support; your privacy notice does not mention AI training; people cannot ; you remove names and email addresses before training; you tried synthetic examples and they were too thin; the helpdesk tool stores the data in the EU.

Assumed: the tickets rarely contain sensitive details, because you answered "Not sure" (see gap 1 below).

Still unknown: whether removing names also catches personal details written in free text.

The question

Can you use support tickets, collected to give support, to train your own assistant, and on what basis?

The rules

  • 1 Law · GDPR Art. 5(1)(b): data collected for one purpose can be used for another only if the new purpose is with the first.
  • 2 Law · GDPR Art. 6(4): five things decide whether a new purpose is compatible: the link between the purposes, the context and what people would expect, the kind of data, the possible consequences, and the safeguards.
    What does this rule say?

    If you want to use data for something new, ask five questions. How close is the new use to the old one? Would people expect it, given how they gave you the data? How sensitive is the data? What could go wrong for the people involved? What protections do you have? If the answers mostly point the same way, that tells you whether the new use fits.

  • 3 Law · GDPR Art. 6(1)(f): you can rely on if you have a real reason, you need the data for it, and it does not outweigh people's rights.
  • 4 Law · GDPR Art. 13(3): tell people before you use their data for a new purpose.
  • 5 Law · GDPR Art. 21(1): when you rely on legitimate interests, people can object, and you must stop unless you can show compelling grounds.
    What does this rule say?

    If you rely on legitimate interests, people can object to your use of their data. Once they do, you must stop, unless you can show a very strong reason that outweighs their interests.

  • 6 Official guidance · ICO on legitimate interests: guidance suggests working through three questions, purpose, necessity and balancing.

Applying the rules

Does the new use fit the old one (Art. 6(4))? 2

  • Link between the purposes: training a support assistant is close to giving support. Points toward compatible.
  • What people expect: customers wrote tickets to get help, and many would not expect their messages to train a model. Points against.
  • Kind of data: mostly free text, which can hold personal details. Mixed.
  • Consequences: low for individuals if personal details are removed, higher if the model repeats them. Mixed.
  • Safeguards: you remove names and email addresses. Points toward, but untested on free text.

Do work as the basis (Art. 6(1)(f))? 3 6

  • Purpose: improving your support is a real business interest.
  • Necessity: you tried synthetic examples and they were too thin, so real tickets are needed.
  • Balancing: this holds only if people are told and can opt out.

Strongest argument against

"Customers wrote for help, not for training, and free text may hold private details your filter misses."

Why it does not change the result: it lowers our confidence, and it is exactly why the notice, the opt-out and a test of the filter are conditions.

Conclusion

Proceed with safeguards.

Confidence: Medium

Because we cannot see how well your filter catches personal details in free text.

This would change if: the tickets hold health or other at scale (then Art. 9 applies and legitimate interests cannot carry it alone 7), or customers were promised their tickets would only ever be used for support.

What to do

  1. 1.Tell current and new customers about the AI training before it starts. You can fix this yourself
  2. 2.Add an easy opt-out and honour it. You can fix this yourself
  3. 3.Test that your filter catches personal details in free text. You can fix this yourself
  4. Gap 1 (from the data map): find out whether the tickets contain sensitive details.
  • Where the data is stored: no problem, it stays in the EU.
  • Automated decisions about people: not relevant, the assistant does not decide anything about a person.
  • AI Act: limited risk, so people must be told they are talking to an AI 8. You are the .

Sources

  1. [1] GDPR Art. 5(1)(b) · Law
  2. [2] GDPR Art. 6(4) · Law
  3. [3] GDPR Art. 6(1)(f) · Law
  4. [4] GDPR Art. 13(3) · Law
  5. [5] GDPR Art. 21(1) · Law
  6. [6] ICO, legitimate interests in practice · Official guidance
  7. [7] GDPR Art. 9 · Law
  8. [8] EU AI Act Art. 50 · Law

Every conclusion shows its sources, so your lawyer can check it. The responsibility stays with your company.

Who uses NyTid

Startups

You're adding AI features to your product and want the documentation right from the start.

Larger companies

You have many systems and data flows, but no privacy lawyer in the product team.

Legal and compliance teams

You want a structured first draft with sources to review, instead of starting from a blank page.

The NyTid Mark

The NyTid Mark shows that a company has documented its reasoning with NyTid, and when. It is not a certification and doesn't mean the company follows GDPR. Anyone can check a mark below.

Verify a NyTid mark

If a company shows you a NyTid mark, you can confirm it's real here.

Nicki Jose Farschi, founder of NyTid
Nicki Jose Farschi, Founder

Why I built NyTid

I'm Nicki Jose Farschi, a law student and Impact member at Norrsken House Stockholm. I kept seeing companies build with personal data and AI without knowing which rules apply to them, and lawyers getting involved only when something had already gone wrong. I built NyTid so companies can do the groundwork themselves and bring their lawyer a clear draft instead of a blank page.

Pricing

Assessment

Free

  • Legitimate interest assessment with sources
  • Check of your policies
  • List of what's missing
  • To-do list
  • PDF

NyTid Plus

Coming soon

  • Unlimited re-assessments when things change
  • Your whole team on one account
  • Quarterly follow-up reminder
  • Alerts when an important rule changes

Leave your email and we'll tell you when Plus opens.

Questions

AI chats know the text of the GDPR well. But they answer what you ask, tend to build on your assumptions, can miss points the law requires, and are weakest on national rules. NyTid asks the questions you wouldn't think of, tests your assumptions, checks every required point and gives you a dated document you can sign and show your data protection authority.

Start with one purpose and see what your report looks like.