Retail & E-commerce
AI applied to real retail decisions
The four most practical use cases in each category, focused on what an independent retailer or growing brand can actually put to work, not an enterprise wishlist.
AI Agents
Autonomous agents that complete multi-step retail tasks, not just answer questions.
Voice AI
Hands-free interaction for the store, the warehouse and the phone line.
Computer Vision
Cameras that turn the physical and digital storefront into structured, usable data.
Predictive & Forecasting AI
Models that tell you what's about to happen, before it shows up in the numbers.
Generative AI & NLP
Text and language work that used to take a team, done at SKU scale.
Recommendation & Personalization
Every customer sees a slightly different store, based on what they actually do.
Built on modern retail technologies
Computer Vision & In-Store
Forecasting & Pricing
Data Platforms
Power BI
Looker
Snowflake
dbt
Systems Integration
Shopify
NetSuite
SAP
POS Integration
From pilot category to chain-wide rollout
Data Audit
Map every system touching sales, inventory and customer data before building anything.
Pilot Category
Prove the model on one category or one store before rolling out chain-wide.
Systems Integration
Connect into POS, ERP and WMS so recommendations show up where staff already work.
Chain-Wide Rollout
Scale the validated pilot across stores and categories.
Continuous Tuning
Models are retrained as seasons, suppliers and assortments change.
Engineering that understands retail economics
We Think in SKUs and Margins
Models are built around retail economics — sell-through, margin and inventory turns — not generic ML benchmarks.
Built for Peak Season
Systems are load-tested for Black Friday-level traffic, not just steady-state demo conditions.
Integrates With Your Existing Stack
We connect into POS, ERP and WMS systems instead of asking you to replace them.
Data + Store Operations
The same team that builds the forecast also thinks through how store staff will actually use it.
Outcomes, not just deliverables
Illustrative case studies — to be replaced with verified client results.
Reporting Cycle Cut From 3 Weeks to 2 Days
Partnered with a Power BI consultancy to model and ship a full reporting layer for an Australian retail supply business.
Read case study →
Personalized Recommendation Engine for a Fashion Brand
Built a recommendation engine that personalizes homepage and product-page layout based on real browsing behavior.
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Shelf Monitoring Rollout Across 40 Stores
Rolled out camera-based shelf monitoring that flags empty sections and routes restocking tasks automatically.
Read case study →