Art. 22
GDPR compliance
Article 22 of the General Data Protection Regulation (GDPR) prohibits automated individual decisions about people without human intervention. We build the product so it can never even apply.
What Locari deliberately doesn’t do
Locari doesn’t rate people.
You set the criteria. Locari filters by your criteria — not by an algorithm’s guesswork.
There’s a small, technically crucial difference between “AI helps with letting” and “AI decides who moves in”. We chose the first option architecturally — not as a marketing tick-box. This page explains what that means in practice, how you recognise it in the product, and why it sets us apart from the tools currently driving the topic into the wall.
Anti-profiling in four numbers
Four markers — together, the architecture.
For us, compliance isn’t a clause the lawyers hide in an appendix. It’s the prerequisite without which the product wouldn’t have launched.
0
AI scores about people
No ranking, no matching score, no “top-match” label. If you want a score, you have to assign it yourself — Locari delivers none.
100 %
You decide
Who gets invited, who gets an offer, who moves in — the choice stays one hundred percent yours. Locari delivers preparation, not a verdict.
EU
Hosting + LLM stack
Sensitive applicant data is processed in the EU — hosting, database and language model (Mistral). Individual services for the landlord assistant sit in the US, secured via EU standard contractual clauses.
The four pillars
Anti-profiling, broken down into four structural guarantees.
No slogan. Four architectural decisions we made before the first line of code.
GDPR Art. 22-compliant
The decision on who gets invited and who gets the tenancy is made solely by the person who lets — you. We build the product so the question of automated individual decisions never even arises.
Rule-based pre-selection
Pre-selection runs on hard facts you define yourself — number of people, income multiple, pet tolerance, lease duration. Deterministic, traceable, changeable at any time. No hidden ranking.
Briefing, not a score
Before every viewing you get a briefing — what was said, which documents are on file, which of your criteria are met. What you don’t get: a score, a star rating, a recommendation. Information yes, the judgement is yours.
EU stack for sensitive data
European cloud infrastructure, an EU language model (Mistral) for processing sensitive applicant data, and the three-phase model of the German Data Protection Conference (DSK) 2024 with a database constraint. Individual services for the landlord assistant sit in the US, secured via EU standard contractual clauses.
The difference
Other tools rate applicants. We don’t.
Anyone scoring applicants via AI automates the discrimination question. We deliberately build the system differently. Click through our four steps — on the right you’ll see what happens instead under algorithmic scoring.
You set the criteria.
You determine the pre-selection criteria — number of people, income multiple of the base rent, pet tolerance, registration now or later, desired minimum lease duration. No machine learning decides what counts; you define the hard facts, and only those hard facts feed into pre-selection. The logic is deterministic, traceable and changeable by you at any time. What isn’t on your list isn’t checked.
Rule-based filter — no hidden ranking.
Locari checks every incoming application against your criteria and pre-sorts — rule-based, no “this applicant seems reliable”, no hidden ranking. An application that meets your criteria stays in. One that doesn’t goes into the sorted-out pile with a reason — and the reason reads “criterion X from your list isn’t met”, not “this person doesn’t fit”.
Briefing, not a score.
Before every viewing you get a briefing — what was discussed in the conversation, which documents are complete, which are missing, what you should know about the person in 60 seconds. What you don’t get: a score, a star rating, a “top-match” label, a recommendation. The briefing is preparation — the judgement itself, whether the person fits the flat, stays yours.
You decide — one hundred percent.
Who gets invited, who gets an offer, who moves in — the choice stays one hundred percent yours. Locari delivers preparation, not a verdict. The matches that meet your criteria are shown in the order they came in — so the order means nothing. You decide based on information, not on a ranking a machine handed you.
Locari
Other tools
Concrete, no marketing fluff
What Locari does. And what Locari deliberately doesn’t.
So you read this not as a values statement but as a description of practice: on the left, the activities Locari takes on. On the right, the ones we deliberately leave out.
What Locari does
Operations work, without judgement.
- Replies to applicant enquiries around the clock — in your tone, with your signature.
- Collecting mandatory details (number of people, income multiple, pets, desired lease duration) against your criteria.
- Receiving required documents and checking them for completeness — no credit interpretation.
- Filtering out off-topic, spam and hate messages, so you never have to see them.
- Coordinating viewing appointments, including reminders and reschedule links.
- A briefing per appointment — what was discussed, which documents are on file, what’s open.
- On critical actions, a check-back to you via WhatsApp — special slot, short-notice reschedule, guarantor.
What Locari doesn’t do
No algorithmic rating of people.
- Assign applicants a score, a ranking or a “top-match” label.
- Sort applicants by the likelihood of being a “good tenant”.
- Translate personality, language style, photo impression or soft factors into a recommendation.
- Algorithmically distil a creditworthiness verdict from income documents.
- Transfer data to third countries — not even for AI processing.
- Store applicant data longer than the letting requires.
- Reuse or sell aggregated applicant statistics internally.
Legal context
Anti-discrimination law prohibits discrimination. An algorithm can’t override that.
An AI model that learns from historical letting data will very likely also learn the discriminatory patterns of the past — even when the protected characteristic itself doesn’t appear in the training set. Models find proxy variables: postcode, name, linguistic style. Innocuous-looking input data turns into a score that systematically disadvantages certain groups in the distribution.
The only reliable way to stay compliant with anti-discrimination law is to put no person-rating algorithm in between. That’s exactly what we don’t do. Locari checks hard facts against your criteria — and nothing beyond that. What isn’t rated can’t discriminate either.
Privacy, concretely
GDPR as practice, not as a tick-box in the appendix.
Privacy is one of those topics many tools handle with long clauses and short practice. We try it the other way around — short clauses, concrete practice.
- 1
The DSK-2024 three-phase model as an architectural rule
Initiation, selection and contract conclusion are separated in the data model. Data from an earlier phase isn’t automatically accessible in the next. What you don’t need in phase 1, you don’t see in phase 1.
- 2
EU hosting and an EU LLM for sensitive data
Sensitive applicant data is hosted in the EU and processed by an EU language model (Mistral) — not by OpenAI. Individual infrastructure services sit in the US and are secured via EU standard contractual clauses (SCC); the full list is in the Trust Center.
- 3
Data minimisation by default
We ask for as little as possible, as late as makes sense. No income documents before serious interest. No required documents before viewing status.
- 4
The landlord’s own signature in every conversation
Applicants see the conversation as a conversation with you — not as a dialogue with an unfamiliar third party. Brand continuity and a privacy lever in one.
- 5
Data control stays with the people whose data it is
Applicants can have their data deleted at any time — we offer the path right inside the conversation, not hidden in a privacy form. On request we provide a structured, readable and complete data export. Access, correction, deletion: a standard function, not a special procedure. No one should have to fight for their own data.
- 6
Retention only as long as the letting needs it
Once the letting is over and statutory retention obligations expire, applicant data is deleted. The exact periods per data category are in the privacy policy — billing-relevant records stay longer, rejected applications shortest.
What it’s about
What anti-profiling means in everyday letting.
Anti-profiling sounds good in a marketing text. Concretely it means three principles that make the difference in every letting.
The core
No algorithm decides about people. You always know why someone is up for selection.
Your criteria
Pre-selection runs on your criteria — income, number of people, pets. Not on an ML model no one can explain.
Briefing, not a score
A briefing says more than a score. You decide based on information — not on a number.
Side-by-side comparison
Where we differ from AI letting tools — and where we do so deliberately.
Comparison fields the way they actually come up in demo calls and sales pitches. Anyone choosing a different solution should do so on the basis of architecture — not on the basis of marketing obfuscation.
| Feature | Locari | Other AI letting tools |
|---|---|---|
| GDPR Art. 22-compliant | Anchored in the architecture — no automated applicant decision exists | Claimed, without naming the mechanisms |
| Pre-selection logic | Rule-based on landlord criteria (hard facts) | AI matching, ML scoring, black-box ranking |
| Briefing per applicant | Preparation document, no score, no recommendation | Score, ranking or “top-match” label |
| Anti-profiling as a position | Explicit brand foundation, named in marketing | No explicit anchor, hidden behind “intelligent selection” |
| Hosting + LLM stack | EU hosting, EU LLM (Mistral), DSK-2024 with DB constraint | Variable, often US LLMs via a US region |
| Final decision | The human (landlord) decides 100 % | AI-assisted with a recommendation |
| Data aggregation for training | Doesn’t happen | Often reserved as a possibility in the terms |
| Landlord signature in applicant dialogue | Per letting case, your signature | Platform signature, third party visible |
The table is deliberately sober. The competing tools were built by good people and are serious products — they made a different architectural decision. That decision has real consequences for landlords and applicants.
Frequently asked
What we get asked most often on demo calls.
These questions come up in almost every first conversation. We answer them here so you don’t have to ask.
Does “no scoring” also mean I get no comparative information at all?
No, quite the opposite. For every application you get a structured briefing — which documents are on file, what was discussed in the conversation, which of your criteria are met and which aren’t. What you don’t get is a ranking or a verdict. Information yes, the judgement is yours.
How can an AI product work without rating applicants?
Locari uses AI for the things AI is good at — understanding text, replying, extracting documents, coordinating appointments, summarising briefings. Not for the thing where AI is structurally problematic — judging a person. That’s a clear architectural separation, not magic.
How does anti-profiling relate to the economics of letting?
The thesis behind AI applicant scoring is that an algorithm could identify “better tenants” than a human. The empirical basis for that is thin — what the models actually identify are correlation patterns that are often proxy variables for protected characteristics.
With Locari, the letting runs on clear hard facts and your own assessment in the briefing-based selection step. A stable tenancy grows out of fitting criteria and a deliberate decision — not out of a score.
Who is liable if a letting process becomes problematic under anti-discrimination law?
The anti-discrimination risk sits with the landlord — in every letting, with or without a tool. What we do is not push you further into that risk by giving you non-explainable sorting recommendations.
If you later have to justify a rejection, you can do so on the criteria you defined upfront — they’re in writing, traceable, and you set them yourself. That’s a far better position than pointing to an algorithm that “ranked the applicant low”.
What happens to applicant data after the letting?
It’s deleted once the letting is over and the statutory retention periods have expired. The exact period depends on the data category — billing-relevant records stay longer, rejected applications shortest.
We stay qualitative here because we don’t want to write an exact figure into a marketing page that then diverges from the actual legal situation. You’ll find the exact periods in our privacy policy.
Anti-profiling as the foundationLocari doesn’t rate people.
Locari doesn’t rate people.
You set the criteria.
Flat fee from €39. 7-day money-back. No subscription.
You give Locari the key details of your flat and the criteria you want to apply to applicants. Locari writes the listing, answers applicant enquiries, coordinates appointments, checks documents. Before every viewing you get a briefing — information, not a verdict. You decide. Locari executes.
Questions? Write to us via the contact form.