AI That Knows Your Customer Better Than You Do.
Demand forecasting, dynamic pricing, and personalized recommendations that turn browsers into buyers and buyers into loyalists.
Retail Margins Are Under Pressure
Generic experiences, inventory waste, and pricing guesswork are eating into margins that were already thin.
Inventory waste from inaccurate demand forecasting
Unpredictable demand patterns across channels and seasons
Generic product recommendations that fail to convert
Pricing guesswork leaving margin on the table
High cart abandonment rates with no intelligent recovery
AI-Powered Retail Intelligence
From the warehouse to the checkout, AI optimizes every touchpoint in your customer journey.
Pain Point
Inventory waste from inaccurate demand forecasting
AI Solution
ML demand forecasting predicts sell-through rates across SKUs and channels — designed to cut both overstock and stockouts.
Pain Point
Unpredictable demand patterns across channels and seasons
AI Solution
Multi-signal forecasting models incorporate weather, trends, and economic data to predict demand shifts weeks in advance.
Pain Point
Generic product recommendations that fail to convert
AI Solution
Contextual AI recommendations adapt to each visitor in real time, using browsing behavior, purchase history, and lookalike signals.
Pain Point
Pricing guesswork leaving margin on the table
AI Solution
Dynamic pricing engine optimizes margins across thousands of SKUs simultaneously, factoring in competitor pricing and demand elasticity.
Pain Point
High cart abandonment rates with no intelligent recovery
AI Solution
Intelligent recovery sequences with personalized incentives, triggered by behavioral signals through email, SMS, and push.
The Full Commerce AI Stack
Eight AI capabilities that work together to maximize revenue and customer lifetime value.
Demand Forecasting
ML models designed to predict demand across SKUs, channels, and seasons — weeks ahead, not after the fact.
Dynamic Pricing
Real-time price optimization designed to maximize margin while staying competitive, adjusting across thousands of SKUs simultaneously.
Personalized Recommendations
Behavioral and contextual AI that serves the right product to the right customer at the right moment in their journey.
Supply Chain Optimization
AI-driven inventory allocation, reorder point optimization, and supplier performance analytics built to eliminate stockouts and overstock.
Conversion Optimization
ML-powered A/B testing, cart abandonment recovery, and checkout flow optimization engineered to lift conversion.
Customer Segmentation
AI clustering that discovers micro-segments in your customer base, enabling hyper-targeted campaigns and retention strategies.
Revenue Analytics
Real-time dashboards tracking basket size, LTV, churn risk, and cohort performance with AI-generated recommendations.
Abandoned Cart Recovery
Intelligent recovery sequences triggered by behavioral signals, with personalized incentives calibrated by customer value.
The Numbers We Engineer Against
We're a new company — no invented results. These are the design targets we set with you in the MAP phase and measure in PROVE.
0%
Real-Time Recommendations, By Design
0s
SKUs Priced Simultaneously
0 days
Target to Measurable Lift
0K+
Visitor Volumes Architected For
How We Deploy Retail AI
The RevSyn Engine — our four-phase methodology — from audit to compounding revenue systems.
Commerce Audit
We analyze your product catalog, customer data, and conversion funnel to identify the highest-impact AI opportunities.
Personalization Engine
Custom recommendation models, pricing algorithms, and demand forecasting trained on your historical data.
Test Against Real Traffic
A/B-tested against your live funnel with evaluation suites and holdout groups — lift is measured, not assumed.
Revenue Optimization
AI-powered marketing automation, conversion optimization, and lifecycle management — reviewed against the targets we agreed.
Blueprint: AI Personalization Engine for a D2C Brand
A representative engagement scenario showing how we architect intelligent systems — an illustrative design, not a client claim.
A D2C brand with strong traffic but flat conversion — generic recommendations that treat every visitor the same and leave repeat-purchase revenue on the table.
The BlueprintOur design builds a real-time personalization engine serving contextual product recommendations, dynamic pricing, and personalized campaigns driven by behavioral signals.
- Recommendations that respond to live behavior
- Pricing informed by demand signals
- Campaigns triggered by intent, not calendars
- Architecture designed for six-figure visitor volumes
Real-time personalization
Start a ConversationAI Agents for Retail & E-Commerce
Intelligent agents that power marketing, sales, and operations across your retail stack.
AI Marketing Agent
Automates campaigns, audience targeting, and content generation to drive traffic and conversions.
Learn moreAI Sales Agent
Powers conversational commerce, product discovery, and personalized upsell recommendations.
Learn moreAI Operations Agent
Manages inventory optimization, supply chain coordination, and operational workflow automation.
Learn morePrivacy-First Personalization
All customer data is handled with the highest security and privacy standards.
GDPR-Aligned
Built to General Data Protection Regulation requirements, with consent management and data subject rights.
CCPA-Aligned
Designed to California Consumer Privacy Act requirements, with automated opt-out and data deletion handling.
PCI DSS-Aligned
Transaction and payment data processing designed to Payment Card Industry security standards.
SOC 2-Aligned Controls
Security controls for data handling, access management, and availability aligned with SOC 2 requirements.
Frequently Asked Questions
Common questions about AI for retail and e-commerce.
We design for measurable signal within the first 2-4 weeks of deployment. The recommendation engine starts working from day one using collaborative filtering, and improves over the first 90 days as it learns from your specific customer behavior patterns — with lift measured against holdout groups, not assumed.
Yes. We integrate with Shopify, Shopify Plus, BigCommerce, Magento, WooCommerce, and custom platforms. Our APIs are designed for easy integration with any headless or traditional commerce stack.
Our pricing engine optimizes for margin, not just volume. It considers competitor pricing, demand elasticity, inventory levels, customer segment willingness-to-pay, and your minimum margin thresholds. It will never price below your defined floor.
At minimum, we need product catalog data, 6-12 months of order history, and website analytics. The more behavioral data available (browse history, search queries, email engagement), the faster the models reach peak performance.
Absolutely. Our demand forecasting models are designed for seasonality, promotional periods, and external factors like weather and economic indicators. They learn from your historical patterns and adapt to anomalies in real time.
Transform Your Retail with AI
Tell us where your funnel or forecast hurts. We'll show you exactly what we'd build — and how we'd prove it works.
No spam. No sales decks. Just a conversation about outcomes.