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Blue

Your face, understood.

AI skincare diagnosis — from a single selfie to a regimen built for your skin.

Product & Pitch Overview · 2026

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THE PROBLEM

Skincare is guesswork — and it's expensive.

$300+

wasted per year

Shoppers buy by trend and packaging, not by what their skin actually needs.

70%

use the wrong actives

Mismatched ingredients trigger irritation, breakouts, and wasted spend.

1 in 3

have a sensitivity

Allergens and reactive ingredients hide in plain sight on labels.

Zero

real diagnosis in-aisle

A dermatologist visit is costly and slow; shelves offer no personalization.

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THE SOLUTION

A dermatologist-grade skin read

in the time it takes to take a selfie.

LUMÉ turns one front-camera photo into a complete, personalized skincare regimen — analyzing your skin, accounting for your sensitivities, and recommending the exact products and the order to use them.

Instant

Personalized

Sensitivity-aware

No appointment

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HOW IT WORKS

Five steps. One selfie. Zero guesswork.

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Take a selfie

Guided front-camera capture with lighting checks.

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Facial analysis

Computer vision maps 200+ facial zones.

3

Detect concerns

Identify acne, redness, pores, lines, texture, tone.

4

Add sensitivities

Flag allergens & ingredients to avoid.

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Get your regimen

A ranked AM/PM routine matched to your skin.

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STEP 1 — CAPTURE

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No forms. No quizzes. Just look at your phone.

A selfie is the only input

Guided capture

On-screen framing, lighting, and distance checks ensure a clean, analyzable image every time.

Works on any phone

Standard front camera — no special hardware, attachments, or lab kit required.

Private by design

Images are processed securely and never sold; users control retention and deletion.

3 seconds to result

From shutter to analysis, the experience feels instant and effortless.

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STEP 2 — ANALYSIS

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Computer vision reads the skin the way a clinician's eye would.

Automatic facial analysis

200+ facial landmarks

We segment the face into zones — forehead, cheeks, T-zone, under-eye, jawline.

Multi-signal models

Texture, tone, oiliness, hydration, and pigmentation are scored per zone.

Calibrated for lighting

Color-correction normalizes for ambient light and camera differences.

Trained on diverse skin

Models validated across skin tones, ages, and conditions to reduce bias.

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STEP 3 — CONCERNS

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We translate pixels into the concerns people actually care about.

Recognition of skin concerns

Detects what matters

Acne, redness, enlarged pores, fine lines, dark spots, uneven texture & tone.

Severity scoring

Each concern is rated and ranked so the routine targets the biggest wins first.

Visual skin map

Users see exactly where each concern appears — on their own face.

Progress tracking

Re-scan over time to watch concerns improve and measure what's working.

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STEP 4 — SENSITIVITIES

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Personalization that protects, not just prescribes.

Input of product sensitivities

Flag known reactions

Fragrance, alcohol, retinoids, acids, essential oils, and specific allergens.

Smart ingredient filter

Every recommendation is screened against the user's avoid-list.

Pregnancy & condition safe

Surfaces flags for rosacea, eczema, and other context-specific needs.

Conflict detection

Warns when two products shouldn't be layered together.

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STEP 5 — REGIMEN

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A complete routine — products, order, and timing.

Personalized regimen

Ranked product matches

Specific products matched to concerns, budget, and sensitivities.

AM & PM routines

Step-by-step order of application, with frequency guidance.

Why each step

Plain-language reasoning so users trust and stick with the routine.

Reorder & restock

One tap to buy, with reminders timed to when product runs out.

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THE DATA MOAT

Recommendations grounded in science

Every ingredient we recommend is backed by an automatically-built knowledge base. Our literature-ingestion pipeline reads a product's ingredient list and enriches each ingredient with chemical data and peer-reviewed evidence — no manual data entry.

Self-building database

Point it at any product label and the knowledge base grows itself.

Evidence-backed

Each ingredient links to PubMed studies and PubChem chemical descriptors.

Deduplicated & canonical

INCI names are normalized and matched so every compound is stored once.

Compounding moat

The more products ingested, the smarter every recommendation becomes.

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AUTOMATIC LITERATURE INGESTION

From an ingredient list to a living database

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Parse INCI list

Split & normalize the raw ingredient declaration into ordered, deduped ingredients.

2

Resolve compound

Match each ingredient to a canonical compound — or create it — via INCI + aliases.

3

Enrich

Pull INCI properties, PubChem chemical descriptors, and PubMed research articles.

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Status & store

Track enrichment state (complete / partial / review) and persist the linked graph.

Built today — a Django pipeline (formulation_ingest) that turns any product label into structured, evidence-linked ingredient data, fully tested.

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UNDER THE HOOD

The intelligence behind the glow

Vision

Facial segmentation & dermatological feature detection on-device + cloud.

Knowledge

Ingredient graph linking 10k+ products to actives, concerns & conflicts.

Matching

Ranking engine scores products against the user's skin profile & avoid-list.

Reasoning

LLM generates clear, personalized explanations and routine guidance.

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MARKET OPPORTUNITY

A massive market hungry for personalization

$190B

Global skincare market

$13B+

Beauty-tech & diagnostics

28%

Annual growth in AI beauty

Consumers already shop for skincare online and crave guidance. LUMÉ captures intent at the exact moment of decision — turning diagnosis into purchase.

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BUSINESS MODEL

Three ways to monetize one selfie

01

Affiliate & commerce

Revenue share on recommended products users buy in-app.

02

Premium subscription

Progress tracking, unlimited re-scans, and pro routines.

03

Brand partnerships

Sponsored placement and anonymized skin-trend insights for brands.

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WHY WE WIN

Diagnosis + sensitivity + commerce — in one flow

Capability

LUMÉ

Typical apps

Selfie-based diagnosis

Quizzes only

Sensitivity-aware filtering

Generic suggestions

Per-zone severity mapping

One-size scores

Routine order & reasoning

Product lists

Progress re-scans over time

No follow-up

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ROADMAP

Where we're headed

NOW

Core flow live

Selfie → analysis → concerns → sensitivities → regimen.

NEXT

Tracking & commerce

Progress re-scans, in-app checkout, restock reminders.

SOON

Body & brands

Expand beyond face; brand partner portal & insights.

FUTURE

Clinical-grade

Derm partnerships, telehealth referrals, predictive skin health.

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Skincare that finally

knows your skin.

LUMÉ — Your face, understood.

Let's build the most personal skincare experience in the world.

weilan@chariotmove.com