AIMM builds a model of who you are across three interlocked layers — relational, cognitive, and attraction. Then it computes fit: not who looks like you want, but who actually works with how you are. No swiping. No forms. No self-report bias.
No social login. No data sold. Ever.
Every other app takes your stated preferences at face value. AIMM detects the gap — and closes it.
An LLM conducts a natural conversation — not a quiz. It builds your psychological model: values, emotional patterns, attachment style, communication preferences, relationship expectations.
Real-world situations with no right answer. Reveals instinctive behaviour under social and emotional pressure — what you actually do, not what you'd say you'd do.
You react to images. AIMM extracts visual features — face geometry, style signals, social cues — building your attraction vector. Each reaction updates confidence scores across the feature distribution.
Similarity search finds candidates whose vectors align with yours. The behavior layer tracks likes, replies, ghosting, feedback — adapting your model over time. Strict on high-confidence features only.
Every user is a rich multi-dimensional representation — not a profile card.
type UserVector = {
psych_vector: float[] // psychological model
attraction_vector: float[] // weighted, confidence-scored
body_profile: float[] // self-perception calibration
behavior_vector: float[] // adaptive real-world learning
}
type FitScore = {
alignment: number // shared foundation
complementarity: number // dynamic balance
tolerance: number // friction capacity
adaptability: number // long-term viability
}
// Fit(A, B) — not similarity. Two people who look
// different on paper can function exceptionally well.
const match = computeFit(userA, userB, {
confidence_gate: 0.75,
strategy: "fit-over-similarity"
})LLM interview extracts values, attachment style, communication patterns. The foundation everything else is scored against.
Image reactions → visual feature extraction → weighted distribution. Confidence scores gate which features are fixed in the match pool search.
Life stage, goals, proximity, schedule alignment. Filters incompatibilities before vector similarity is even computed.
Tracks real interactions — likes, replies, ghosting, feedback. Updates the model continuously so matches improve with every engagement.
You react. The system scores. Only high-confidence features are fixed. Low-confidence features stay flexible — letting the system broaden your real pool.
All outputs presented as approximations, not verdicts. You are not reduced to a score.
Clear disclosure of how image analysis works and what data is retained. You control deletion at any time.
Active monitoring to prevent attraction vector bias from narrowing suggestions to a single archetype. We audit for fairness.
Data portability from day one. Export or delete your full model at any time. No data brokering, ever.
AIMM is the only system built around fit — not similarity. Two people who look incompatible on paper can function exceptionally well together. The model captures that. No other platform does.
We're onboarding a limited cohort to calibrate the model with real-world data. No swiping. No algorithms you can game. Just matches that make sense.
No spam. Unsubscribe any time. GDPR-compliant.