XPndAI builds the Beauty Commerce AI platform for cosmetics brands, D2C beauty e-commerce, and omnichannel beauty retailers — AI virtual try-on (AR lipstick, eyeshadow, foundation shade matching), AI skin analysis (acne detection, hydration scoring, tone mapping, personalised routine recommendation), beauty personalisation engine (product recommendations from selfie + quiz), and WhatsApp beauty advisor AI. Integrates with Shopify, WooCommerce, and custom storefronts. India, UAE, UK, USA, Southeast Asia. From $12,000.
The #1 conversion barrier in online beauty is uncertainty about how a product will look on the customer's skin. Virtual try-on removes this barrier. XPndAI's virtual try-on module: lip colour try-on (upload selfie or use live camera; select any lipstick/lip gloss/lip liner from the product catalogue; AI renders the product accurately on the customer's lips in real time — accounts for lip shape, skin undertone, and lighting; compare shades side-by-side; add to cart directly from the try-on view); eye makeup try-on (eyeshadow — single shade and full palette looks; eyeliner; mascara intensity preview; brow shaping and tinting visualisation); foundation and concealer shade matching (customer uploads selfie or takes live photo; AI analyses skin undertone (warm/cool/neutral), depth (light/medium/dark/deep), and surface texture; recommends the best foundation shades from the brand's product range; side-by-side comparison of top 3 recommended shades applied to the customer's photo); blush and bronzer simulation (product placement simulation — cheek placement per face shape; intensity adjustment slider); integration (web embed — JavaScript widget for Shopify, WooCommerce, Magento, Webflow, custom; no app download required — works in mobile browser; selfie upload or live camera; product try-on linked to product pages; try-on results shareable — WhatsApp, Instagram Stories, email); mobile-first — optimised for Indian, UAE, and Southeast Asian mobile users on mid-range Android devices. From $15,000 for virtual try-on module.
Skincare is the fastest-growing beauty category — customers want personalised routines, not generic "normal/dry/oily" type recommendations. XPndAI's AI skin analysis: skin analysis from selfie (customer uploads a selfie or takes a live photo; AI analyses: skin type — dry, oily, combination, normal; skin concerns — acne and blemish detection, hyperpigmentation and dark spots, uneven skin tone, pores, fine lines and wrinkles, redness, dark circles; hydration scoring — skin texture analysis for surface moisture; melanin distribution — for undertone and foundation matching; environmental damage markers — sun damage, dullness indicators); personalised routine builder (based on skin analysis results, AI builds a morning and evening skincare routine using only the brand's products; step-by-step routine — cleanser, toner, serum, moisturiser, SPF; targeted treatment recommendation — e.g. niacinamide for hyperpigmentation, salicylic acid for acne, retinol for anti-ageing; explanation of why each product was recommended, in plain language); quiz complement (optional skin quiz — lifestyle questions (diet, sleep, pollution exposure, stress) combined with the AI skin photo analysis for deeper personalisation; quiz + photo analysis gives higher accuracy than either alone); progress tracking (customer re-analyses skin after 4–8 weeks; improvement score vs. baseline analysis; product effectiveness feedback — informs future recommendation tuning); email and WhatsApp delivery (personalised routine card delivered by email and WhatsApp; PDF routine download; reminder to re-analyse skin at 4-week mark). From $12,000 for AI skin analysis module.
Generic "you might also like" recommendations don't work for beauty — the right foundation depends on skin tone, the right serum on skin concern, the right lipstick on undertone. XPndAI's beauty personalisation engine: profile-based recommendations (customer profile built from: skin analysis results + quiz + purchase history + browsing behaviour; product recommendation algorithm trained on beauty-specific signals — shade matching, skin type compatibility, concern targeting, ingredient preference); shade group recommendations (customers grouped into shade families — fair/light/medium/tan/deep — with product recommendations scoped to compatible shades; prevents "bought the wrong shade" returns); seasonal personalisation (SPF and lightweight formulas surfaced in summer; richer moisturisers and warming lip shades in winter; Eid/Diwali/Christmas gift sets surfaced in the relevant seasons); cross-category recommendations (skincare → makeup compatibility: "This serum pairs well with our mineral foundation because both are silicone-free"; foundation → concealer shade matching; lip liner → lipstick pairing); replenishment prediction (AI predicts when a customer is about to run out of a consumable product — a 30ml serum typically lasts 45 days — and sends a WhatsApp replenishment reminder at day 38); WhatsApp beauty advisor (ongoing AI conversation on WhatsApp — customer asks "what's good for my dark circles?"; AI accesses the customer's skin analysis profile and purchase history; recommends the most relevant product with the reason; links to product page). From $12,000 for personalisation engine.
For cosmetics brands building their own D2C storefront, XPndAI builds the full e-commerce foundation with beauty-specific features: storefront (custom-designed Shopify or custom React storefront; shade selector with colour swatches; product ingredient list with concern-targeting tags — "good for: acne-prone skin"; before/after imagery per product; editorial content — skin type guides, application tutorials); beauty subscription and bundles (monthly beauty subscription box — subscriber curates or AI curates their box; bundle builder — "build your routine" with discount incentive; gift sets for seasonal campaigns); product discovery (AI search — customer types "something for dry skin" or "red lipstick for dark skin" and gets precise results, not generic text search; filter by shade range, skin type, concern, ingredient); influencer and affiliate management (creator affiliate links with commission tracking; gifting programme management — product gifting to creators, tracking content deliverables and resulting sales; UTM-based campaign attribution); inventory and fulfilment (inventory management with SKU-level shade/size/variant tracking; reorder point alerts; fulfilment integration — Shiprocket, Delhivery, Bluedart for India; Aramex/UAE logistics for UAE; Royal Mail/DPD for UK; USP/FedEx/UPS for USA; dropship integration for 3PL fulfilment partners); returns management (shade mismatch return processing — customer photos submitted for return; beauty-specific return policy engine). From $20,000 for D2C storefront build.
Beauty brand retention and repeat purchase depends on consistent, personalised outreach — not generic mass SMS blasts. XPndAI's marketing AI for beauty brands: WhatsApp marketing (WhatsApp Business API broadcast — segment-based campaigns: oily skin segment gets new mattifying launch; fair/light shade group gets new summer nude collection; dark spot concern segment gets new targeted serum launch; personalised offer — birthday month 20% off; cart abandonment recovery via WhatsApp — 3-message sequence with 10% discount; product launch announcement with try-on link and shop now CTA); email marketing (klaviyo or custom integration; skin profile-based email flows — welcome routine email, 4-week check-in email, 8-week re-analysis prompt; post-purchase email with application tips; product review request after delivery); loyalty and referral (points per rupee/AED/pound spent; referral programme — unique referral link; friend gets 15% off first order, referrer earns 200 points; redemption at checkout — points as discount); customer segmentation (segments by: skin type, shade group, purchase frequency, last purchase date, AOV tier, product category — skincare/colour/fragrance; used for targeted campaigns and personalised recommendations). From $10,000 for CRM and marketing AI module.
Beauty brands need analytics that go beyond generic e-commerce metrics — shade-level sell-through, concern-based product performance, and virtual try-on conversion data. XPndAI's beauty analytics: shade intelligence (sell-through rate per shade — which shades are flying, which are stagnant; shade group demand analysis — percentage of customers in each shade group; shade replenishment forecasting — based on sell-through rate and lead time; dead stock flagging per shade); category and concern performance (revenue by product category — lipstick, foundation, serum, moisturiser; performance by concern targeting tag — acne, brightening, anti-ageing, hydration; correlation analysis: concern search → recommended product → conversion rate); virtual try-on analytics (virtual try-on usage rate; try-on to add-to-cart conversion; most tried shades; try-on device and OS breakdown — important for performance optimisation on Indian mid-range Android); customer cohort analysis (repeat purchase rate by acquisition source; LTV by first product purchased — foundation first purchasers vs. serum; retention by skin type segment); content attribution (which influencer content drove which SKU sales — UTM-based; editorial content — "acne blog post" → serum conversion tracking). From $8,000 for analytics module standalone.
Virtual try-on accuracy: Lip colour try-on achieves highly realistic rendering under consistent lighting — colour accuracy is high for stable, opaque formulas; sheer and glossy formulas are accurate for colour but the finish rendering is approximate (glossy sheen is depicted, not photo-real light physics). Eye makeup try-on is accurate for defined looks (liner, eyeshadow) — softer blended looks are approximate. Foundation shade matching: shade family accuracy (fair/light/medium/tan/deep) is high; within-shade-family subshade (e.g. N20 vs. N30) is approximate — we recommend providing 3 closest shade options rather than a single "exact" recommendation, which is how the major beauty brands (L'Oreal, Fenty, MAC) also handle AI shade matching. Skin analysis accuracy: skin type classification (oily/dry/combination/normal) achieves 80–90% agreement with dermatologist classification under good lighting. Acne and blemish detection is accurate for visible surface acne. Fine line detection is accurate for pronounced lines; early fine lines in younger skin are less reliably detected. Analysis quality is highly dependent on photo quality — adequate lighting, front-facing, no heavy filter. XPndAI recommends in-app guidance on how to take an analysis-quality selfie to maximise accuracy. Contact: +91-9625368140.
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XPndAI · Beauty Commerce AI · Virtual Try-On Software · AI Skin Analysis · Cosmetics Personalisation AI · D2C Beauty Software · AR Makeup Try-On · Foundation Shade Finder · Beauty Recommendation Engine · WhatsApp Beauty Advisor · Shopify Beauty AI · Source Code Ownership · From $12,000 · +91-9625368140