AI-ready data integration for retailers
AI-Ready Data Layer for retailers
Boost AI efficiency with your sales, customers and stock in one place. We connect your POS, loyalty and inventory data and teach your AI how your business counts. Answers stay consistent, and you spend less on tokens. No data team needed. We build it, connect your AI tools and hand it over.
Free, 30 minutes. Bring one question your AI gets wrong. We'll show you why, and what to fix first.
.jpg)
250+
projects delivered
92%
client retention
18+
years building data and AI systems
Your team already uses AI.
Here's where it breaks.
You rolled out AI to save time. So far, it mostly writes emails. Ask it how last week went, and it either can't answer or gives you a number nobody trusts. Meanwhile, someone still builds the weekly report in Excel.
Marketing
AI doesn't know your customers
Marketing asks who came back after the spring promo. Your POS knows what sold, not who bought it. So AI guesses from sales totals.
Merchandising
AI can't see your stock
Ask AI what to reorder, and it looks at sales alone. It doesn't know three stores still have the item in the back room.
Store operations
AI doesn't count the way you do
Ask about margin, and AI picks a formula. Not yours. It doesn't know how you handle returns, markdowns or shrink.
Finance
Two managers, two numbers
Two store managers ask AI for last week's sales. They get two different totals. Nobody knows which one to trust.
It's a data problem, not an AI problem
Your AI can only work with what it sees. In most retail companies, that's three kinds of data that never talk to each other.
Sales
Who bought what, where and when. It sits in your POS and online store.
Customers
Profiles, loyalty points, purchase history. It sits in a loyalty app, a CRM or a spreadsheet. Sometimes nowhere at all.
Stock
What's on the shelf, in the back room and on order. It sits in your inventory system, or in yet another spreadsheet.
Each system counts things its own way. None of them knows how you count margin, returns or shrink. So every time someone asks a question, AI guesses which number to believe. A smarter model won't fix that. Neither will a better prompt.
AI needs what every new hire needs. The right information, your rules and clear limits on what it can see. That's onboarding.
We bring all three together, match them up and add your business rules. Your AI tools read from there, not from raw exports. We call it an AI-Ready Data Layer. Your team will call it the place where the numbers match.
Retail data integration: one place for your sales, customers and stock
Connected
Shopify, Square, Lightspeed, NetSuite, your loyalty app and spreadsheets in one place, updated automatically.
Clean
Duplicates removed. Every store, product and customer recognized across systems.
Counted your way
Net sales, margin, returns and shrink defined once, the way your finance team counts them.
Protected
Each team and each AI tool sees what it should. Nothing more.
Before/after example
Data in separate systems
What were net sales of our classic denim jacket last week?
POS
$18,600
Stores only
E-commerce
$9,400
Online only, returns not deducted
Inventory
$31,200
Counts every unit that left stock, transfers included
Your data in one place
What were net sales of our classic denim jacket last week?
One source · Same answer for every team
$25,850
How it's counted: Net sales · stores + online · returns deducted · in-store pickups counted once · updated daily
Same question. One answer.
Your AI stops guessing which system to believe. It reads from one place, so every team gets the same number and can see how it was counted.
What your teams can finally ask AI
Every team asks different questions. Now the answers…
Marketing
Know your customers, not just your sales
Our data engineering service draws on 18 years of…
Merchandising
Reorders based on real stock
Our data engineering service draws on 18 years of…
Store operations
Compare stores fairly
Our data engineering service draws on 18 years of…
Finance
One set of numbers for everyone
Our data engineering service draws on 18 years of…
Your AI’s onboarding, done for you
Not a slide deck. A working setup with everything your AI needs on day one: the right data, your rules and clear limits.
01
Your sales, customer and stock data connected
Firstly, you should formulate your idea into a wri…
02
One map of your stores, products and customers
Next, we start working in data engineering consult…
03
Your KPIs defined and written down
Our team makes detailed tasks with the optimal dat…
04
Access set for every team and AI tool
After alignment, we proceed with data system devel…
05
Your AI tools connected and tested
At the final stage of your data engineering servic…
06
Docs and handover
At the final stage of your data engineering servic…
Ready for what's next? Build dashboards, demand forecasts, personalized offers or AI agents on the same foundation, without starting from scratch.
Four steps. One point person on your side, a few short sessions.
You get a clear scope, timeline and estimate before…
01
AI data check
Our data engineering service draws on 18 years of…
02
Connect your AI tools
Our data engineering service draws on 18 years of…
03
Bring data together
Our data engineering service draws on 18 years of…
04
Handover
Our data engineering service draws on 18 years of…
What we need from you.
One point person on your side, access to your systems, and a few short sessions with someone from finance, merchandising or marketing to agree on how you count your key numbers.
Stays in your environment
We build in your cloud account or platform, not ours
You own it
Everything we build, plus the docs and access, stays with you
Access by role
Each person and each AI tool sees only what it's allowed to see
Customer details stay private first
AI can study customer groups and buying patterns without seeing…
NDA first
We sign an NDA before we see any of your data
Your AI is live. Your data isn't ready yet.
Built for U.S. retailers who
Run several physical stores, with or without an online shop
Have rolled out an AI tool company-wide, like Microsoft 365 Copilot, ChatGPT Enterprise, Claude Enterprise or the AI inside your BI
Keep sales, customer and stock data in different systems or spreadsheets, or don’t track some of it yet
Don’t have an in-house engineering team, or have one that’s stretched thin
Most AI vendors start with the tool. We start with your data.
We bring your sales, customers and stock together first, so your AI gets the right numbers from the start and keeps getting them as you grow.
Typical AI project
With Dataforest
Starts with
The AI tool
Your sales, customer and stock data
When answers go wrong
A new prompt or a new tool
Fix the data at the source
The next AI project
Data prep starts over
Builds on what's already there
What you keep
A tool tied to one vendor
Your data in one place, owned by you
How Tifa Chocolate & Gelato got one set of numbers across 34 states
The problem
The franchise was growing fast. Store data arrived in different formats at different times. Sales reports used different formulas, so dashboards didn't match, and leadership couldn't trust the numbers.
100%
of reporting issues resolved
11
executive dashboards with consistent, validated numbers
This project wasn't about AI. It was about getting every location to count sales the same way. That's the foundation your AI needs before its answers can be trusted.
Dataforest in numbers
250+
projects delivered
35+
AI solutions delivered
92%
client retention
18+
years building data and AI systems
100+
engineers
AWS & Databricks
partner
Start your AI’s onboarding with one call
What we’ll cover in 30 minutes
01
How your team uses AI today
02
Where your sales, customer and stock data live
03
Where your AI’s answers go wrong, and why
04
Ways to fix it, from quick wins to bringing all your data into one place
05
A clear recommendation for your next step, even if it isn’t us