Beauty brands, AI-native.
AR try-on, shade-match AI, personalized commerce, and sustainable supply-chain software — engineered for brands whose customers shop on taste, moved by trends, and expect personalization on arrival.
A category re-platforming in public.
US online beauty sales moved from $51.4B toward $72B in 2025 — and the winners are the brands whose software keeps up with the trend cycle. We build that software. See the wider context on our industries index.
US online beauty sales trajectory — reshaping how brands ship features, content, and promotions.
Consumers who bought environment-friendly beauty brands in 2021. Clean ingredients and traceability now drive category leadership.
Shade, scent, skin type, hair type — customers expect a product tuned to them. Static catalog browsing is eroding fast.
Five forces
reshaping the category.
The brands investing here are pulling ahead. The brands waiting are watching the DTC upstarts eat share in real time.
Personalization at scale
Shade, skin, hair, scent — every customer wants a product tuned to them. Data-driven personalization is the new baseline, not a differentiator.
Sustainability is table stakes
Sixty-seven percent of consumers bought environment-friendly beauty brands in 2021. Clean ingredients, traceable supply chains, and refill commerce are now non-negotiable.
Category competition keeps rising
DTC upstarts, celebrity launches, and retailer private labels compress every legacy brand's moat. Product velocity is a survival metric.
Consumer behavior moves fast
TikTok trends ship faster than your next campaign. Content, merchandising, and inventory systems have to adapt in hours, not seasons.
Operational efficiency under pressure
Rising CAC, thinning margins, and fragmented omnichannel ops force brands to automate the back office to fund the front one.
Community-driven commerce
The shift from transactional e-commerce to platforms where creator tutorials, peer reviews, and community interactions drive the final checkout.
Systems that make
beauty commerce hum.
Software we ship for beauty and lifestyle brands — each block shown below compounds with the others. Pair it with our AI & ML engineering practice to accelerate the AI-heavy pieces.
- 01
E-commerce & headless storefronts
Next-gen, composable commerce tuned for beauty SKUs, variants, and subscriptions.
- 02
AR try-on & virtual mirrors
Real-time lipstick, foundation, hair-color, and eyewear try-on across web and mobile.
- 03
Shade & skin-match AI
Computer-vision models trained on diverse skin tones to replace guesswork with fit.
- 04
Loyalty & subscription engines
Tiered programs, refill cadence, gifting — wired to your POS, storefront, and CDP.
- 05
Mobile brand apps
iOS and Android flagships with AR, content, and shoppable looks in one surface.
- 06
Content & creator platforms
UGC moderation, influencer workflows, and shoppable editorial at magazine quality.
- 07
Personalization engines
Product-discovery and recommendation AI tuned on behavior, preference, and skin data.
- 08
Omnichannel OMS & inventory
Unified inventory, order orchestration, and store fulfillment across DTC and retail.
- 09
Supply-chain traceability
Ingredient provenance, batch lineage, and sustainability reporting your audit team can defend.
- 10
BI & category analytics
Cohort, SKU, and channel dashboards — the signals your merchandising team needs hourly.
- 11
Integration & automation
PIM, ERP, 3PL, CRM, and marketing-cloud glue so every new channel ships in days.
AI, tuned for
the beauty shopper.
Generic models underperform on this category — skin tones, shade variance, and trend velocity break off-the-shelf. We build vertical-tuned AI that ships to production.
Virtual try-on
Photorealistic AR rendering calibrated to skin tones, lighting conditions, and device cameras — shot-level accurate.
Shade-match intelligence
CV models that recommend foundation, lipstick, and hair color across every Fitzpatrick skin type.
Content personalization
On-page copy, imagery, and offer targeting that adapts to first-party signals without cookie dependency.
Creator & influencer analytics
Measure true performance, detect fraud, and optimize spend across thousands of creator partnerships.
Demand & trend forecasting
Signals from social, search, and marketplace data feed inventory and launch planning.
Conversational commerce
On-site beauty advisor bots that route complex SKU questions to real stylists at the right moment.
Partner who's already
shipped in your category.
Vertical depth compounds. Our beauty and lifestyle engagements draw on patterns we've shipped with Cosmopolitan, Plum Perfect, and Zinzi — faster to working software, fewer wrong turns.
Domain playbook, day one
We've shipped for Cosmopolitan, Plum Perfect, Zinzi, and MyTrax — your system is a variation, not a greenfield guess.
AI that converts, not demos
Try-on and shade AI wired to add-to-cart and repeat purchase — measured in incremental revenue, not installs.
Compliance-aware architecture
GDPR, CCPA, ingredient-disclosure rules, and regional labelling built into the data model from the start.
Composable over monolith
Headless commerce + content + AI services — swap vendors without replatforming every three years.
Speed to market
Working POC in weeks. Production pilot in one quarter. Global rollout with follow-the-sun teams.
Margin-aware delivery
Every engagement is wired to the CAC, contribution margin, or repeat-rate line your CFO tracks.
Five brands,
in production.
A slice of what we've shipped in beauty and lifestyle. Browse the complete portfolio for the full set.
Plum Perfect
AI shade-matching that turned selfies into personalized beauty picks.
Zinzi
Jewelry + lifestyle commerce tuned for European omnichannel operations.
MyTrax
Wellness tracking and lifestyle-guidance platform for an always-on audience.
Cosmopolitan
Publishing-grade content platform that bridged editorial and shoppable beauty.
ENRITSCH
Premium nutrition-led beauty brand — storefront, loyalty, and content in one system.
Answers for
category leaders.
01Can you build AR try-on that works across devices and skin tones?
02How do you handle data privacy for AI-driven personalization?
03Do you integrate with existing PIM, ERP, and marketing-cloud tools?
04How quickly can we see a working AI prototype?
05Who owns the AI models and data you train on?
Let's build your AI-native brand.
One discovery call, a vertical audit on your catalog and customer data, and a working prototype inside four weeks. From there, full production delivery on our standard method.