Fan intelligence without exposing fan identity.
Detect, mask, and analyze football fan messages with a GDPR-safe AI pipeline. Raw PII stays protected. Only anonymized text reaches the LLM.
- 0%
- PII leakage target
- EN · DE
- languages supported
- 1 msg
- pipeline mode
Fan messages are full of insight — and sensitive data.
Football clubs receive an enormous volume of fan communication. Useful signal is mixed with personally identifiable information that must never leak into a third-party model.
PII risk
Raw messages contain names, emails, phones, IDs. Sending them to an LLM leaks personal data.
Manual review doesn't scale
Clubs receive thousands of messages weekly across email, app, social, and forms.
Multilingual complexity
English, German, and code-switched messages confuse off-the-shelf detectors.
Insight buried in text
Without structure, sentiment, urgency, and recommended actions stay invisible.
Privacy first. Intelligence second. Always in that order.
Five deterministic stages. PII detection runs locally before any text reaches the LLM, and a second safety gate verifies the masked payload.
- 01
Input
Single fan message ingested via API or form.
- 02
Detect
Presidio + regex find PII locally — names, emails, IDs.
- 03
Mask
Replace each entity with a stable placeholder token.
- 04
Verify
Second safety scan rejects anything still leaking.
- 05
Analyze
Only masked text reaches the LLM for insight.
Anonymization preserves meaning, not identity.
The masked payload retains enough context for accurate sentiment, topic, intent, and urgency detection — without exposing a single private value.
Hi, I'm Lukas WeberNAME from BerlinCITY. My email is lukas.weber@gmail.comEMAIL. I waited 45 minutes at Gate C and want a refund for booking BK-92811BOOKING_ID.
Hi, I'm [NAME_1] from [CITY_1]. My email is [EMAIL_1]. I waited 45 minutes at Gate C and want a refund for booking [BOOKING_ID_1].
Structured insight from anonymized text.
The LLM analyzes only the masked message and returns a compact, structured payload your team can route, prioritize, and act on.
Summary
Fan reports a 45-minute wait at Gate C and requests a refund for one booking. Recommend: acknowledge delay, offer compensation per matchday-ops policy, escalate if repeated.
Designed to reduce sensitive-data exposure at every step.
Raw PII never reaches the LLM
Raw messages not stored by default
PII entity values are not stored
Second safety scan before LLM call
Final PII scan on AI output
PostgreSQL holds only safe results
Built around how clubs actually work.
Six concrete fan communication surfaces a club already operates — now with structured insight and zero PII exposure.
See the privacy pipeline in action.
Walk through a real fan message — from raw input to anonymized insight — in under a minute.