Retail data & AI platform
AI-ready data, built for retail.
42 is a managed retail data and analytics platform built for brands. 42 unifies data sources into one data warehouse, so your team and your AI work from numbers you trust.
Already have a data warehouse?
See how 42 can help
Net Sales
$ 3,625,446
Goal
$ 3,528,470
Units Per Transaction
1.8
Visits
1,702,674
Net Sales Units
30,928
Average Order Value
$ 211
Inventory / On Hand
145,679
Conversion
3.2 %
Net Sales
July 1 – September 30
What products will stock out this week?
Trusted by global fashion and lifestyle brands,
built on 10+ years of retail data engineering.
The AI readiness gap...
Shopify
NetSuite“Every team walks into the room with a different version of the numbers.”
42 replaces that with one trusted foundation so that your team, equipped with AI, can make the right decisions.
A Unified Data Warehouse + Retail Semantic Layer
Omni-Retail Data Warehouse
analysis
analysis
analysis
vs. Promo
analysis
analysis
42 Visualization
Visualization for the whole organization – from 42's proprietary BI dashboard, to data warehouse mirrors, to scheduled Excel reports.
42 MCP Server
Structured, context-rich data to any AI platform though the 42 MCP Server (e.g. Claude, CoPilot, ChatGPT, and other AI applications).
What this semantic layer powers...
It makes your logic explicit.
Your definitions of sell-through, markdown and attribution live in one place, so every team works with the same context.
It turns that logic into working tools.
Workflows, skills, and agents, can be built on these definitions, so that teams do not have to rebuild the business logic each time.
It makes every AI tool specific to you.
Generic models have to guess at retail definitions. 42 has a semantic layer which means you get answers regarding your own channels, hierarchies, and history.
It feels good to be loved
“The ability to action things quickly, get to answers quickly, gives us all peace of mind that we’re making the best decision that we possibly can.”
Chief Executive Officer, Faherty
“42’s unified data platform is immensely beneficial - providing actionable insights that align with our unique needs. Plus, their responsive support team is always ready to help.”
Chief Operating Officer, FRAME
“That’s the strength of 42, over and above the technology, the ability to adapt and grow with us.”
Chief Information Officer, Moose Knuckles
“42 has been game changing for me and my team (merchandising, buying & planning)! We are able to quickly get answers that help us making better business decisions and move onto the next thing - fast.”
VP Merchandising & Planning, DOEN
50%+
faster business analysis
85%+
active users
10-25%
sales performance improvement
45-60%
lower total cost of ownership
Questions
42 Technologies connects to every source a retail brand runs on: ecommerce (e.g. Shopify, Magento, WooCommerce), point of sale (e.g. Shopify POS, NewStore, Teamwork Commerce), ERPs (e.g. NetSuite, Oracle, Apparel Magic), marketplaces (e.g. Amazon, Walmart), retail-partner sell-through (e.g. Nordstrom, Bloomingdale’s, Sephora), marketing and ads (e.g. Google Ads, Meta Ads, Klaviyo) and store traffic (e.g. RetailNext, Shoppertrak).
It doesn’t have to be an API: spreadsheets, retailer portals and scheduled file feeds all work. If your data lives somewhere else, ask us.
It can depend from brand to brand. Some have the warehouse but not the retail modeling; others have sources that never got wired up.
We connect what’s missing, and our retail semantic layer turns it into agreed metrics like sell-through and full-price ratio. Unified data can flow back into your warehouse and into the BI tools your team already uses (e.g. Tableau, Looker, Power BI), so the whole business works from one place. Where 42 fits depends on what you already have, so it’s worth a conversation.
Usually it’s what the agent is reading, not the model. Retail data sits across ecommerce, wholesale, POS and ERP with no shared definitions, so an agent picks up whatever one system holds and reports it confidently.
Unified, modeled data with agreed metrics is what makes AI useful. 42 does that first, then serves it through the 42 MCP server, so ChatGPT, Claude or your own agents read the same numbers your team sees in dashboards.
Usually, and the comparison worth making is total cost of ownership. In-house means hiring data engineers, building every connection and metric definition from scratch, then maintaining all of it as source systems change. The build is the smaller half; the upkeep never stops.
With 42 that work is already done. We have modeled retail data for over 100 brands across 10+ years, so the connections and definitions exist on day one and our engineers keep them running. You get a working platform for less than the team it takes to build one.
If you already have a data team, we can work alongside them. Retail-specific gaps are often where AI initiatives wait: a partner feed nobody has modeled yet, definitions that differ by channel. We bring retail expertise and added capacity to those, so your team can move faster on the goals it already owns.
Pricing follows the data sets and sources you need ingested, so it tracks your stack rather than your headcount. Fractional data engineering and implementation are included: our engineers build the connections, model your data and keep them running as your systems change, rather than billing it as a separate project.
Still unsure about how we can help? Talk to us about your data.
