AI-ready data integration 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.
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.
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.
Retail data integration: one place for your sales, customers and stock
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.
Before/after example
Data in separate systems
What were net sales of our classic denim jacket last week?
$18,600
Stores only
POS
$9,400
Online only, returns not deducted
E-commerce
$31,200
Counts every unit that left stock, transfers included
Inventory
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.
Нour 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 hold up, because they come from one place and are counted your way.
Marketing
Know your customers, not just your sales
"Which regulars haven't been back since the spring promo?"
See who your best customers are, what they buy together and whether a promo brought in new shoppers or just discounted your regulars. Build bundles and offers from real baskets, not hunches. No loyalty program yet? Your sales data is enough to begin, and we'll help you start capturing customer data when you're ready.
Merchandising
Reorders based on real stock
"Which regulars haven't been back since the spring promo?"
AI sees sales and stock across every store and channel, back rooms included. Reorders start from what actually sold and what you already have.
Store operations
Compare stores fairly
"Which regulars haven't been back since the spring promo?"
Every store is counted the same way, by your rules. A weak number points to a real problem, not a reporting quirk. You know where to send help while there's still time to fix the month.
Finance
One set of numbers for everyone
"Which regulars haven't been back since the spring promo?"
Every manager, every report and every AI tool gets the same number. No more stitching exports together the night before the meeting.
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.
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 any work starts.
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.
Your data stays under your control
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
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
We sign an NDA before we see any of your data
Don’t have an in-house engineering team, or have one that’s stretched thin
We sign an NDA before we see any of your data
Free · 30 minutes · NDA before we see any data
Find out what’s holding your AI back
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.
We fix the source, not the prompt
When AI answers go wrong, the usual fix is a new prompt or a new tool. We fix the data underneath, so every tool after that works from the same numbers.
We build it, you own it
No black box and no lock-in. Everything we build, and the docs, stay with you.
Works with the AI tools you choose
Microsoft 365 Copilot, ChatGPT Enterprise, Claude Enterprise or the AI in your BI. One place serves them all, so switching tools doesn't mean starting over.
Name...
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
.svg){kind=small}
They've had a quick grasp of what we are trying to do and delivered to our spec without a fuss. We are comfortable that we have a good product that will get traction.
.svg){kind=small}
They understood our requirements, translated into actions rapidly, and adapted to requests easily. DATAFOREST delivered the product on time. Moreover, their communication was excellent. They were understanding, fast, and flexible.
In the first year of cooperation we earned an extra $150,000 in profit from the information DATAFOREST’s work provides us. I really enjoy working with DATAFOREST and the products they’ve delivered. They’ve allowed us to grow our business exponentially!
DATAFOREST’s services are worth every penny. The team strives to create cost-efficient solutions to make the engagement worthwhile. Equipped with reliable data management skills, they supply me with marketable product.
.svg)
They have very intelligent people on their team — people that I would gladly hire and pay for myself. DATAFOREST has exceeded our expectations, playing a very important role as our technology partner.
DATAFOREST has exceeded our expectations. The team has delivered effectively and organized all communication via virtual meetings, email, and messaging apps. Their unique approach to organizing deliveries impressed us.
Qvist Sweden AB
Their data engineering expertise is definitely at the highest level. The team has clear communication and facilitates sprints smoothly. They're also highly transparent, resulting in an effective partnership.
How your team uses AI today
Where your sales, customer and stock data live
Have rolled out an AI tool company-wide, like Microsoft 365 Copilot, ChatGPT Enterprise, Claude Enterprise or the AI inside your BI
Where your AI’s answers go wrong, and why
We sign an NDA before we see any of your data
Ways to fix it, from quick wins to bringing all your data into one place
We sign an NDA before we see any of your data
A clear recommendation for your next step, even if it isn’t us
We sign an NDA before we see any of your data
Questions retailers ask us
Copilot and ChatGPT Enterprise are smart, but they only know what they can reach. Point them at five systems that count sales five different ways, and you get five different answers. We give them one place with your sales, customers and stock, plus your business rules, so the AI you already pay for gives answers your team can use.
AI-ready data is your sales, customer and stock data from every system, matched, cleaned and counted your way, so every AI tool reads the same numbers. It’s the difference between AI that guesses which system to believe and AI your team can trust. For the technical side, see AI-ready data infrastructure.
Use it. Built-in AI is good at questions inside its own system, like what sold in one store yesterday. But the questions that matter usually cross systems: which loyalty members stopped buying, what to reorder when other stores still have stock, how online returns hit store margin. Each vendor's AI sees only its own system, while most retailers keep sales, customers and stock in several. We bring them into one place, so the AI tools you use can answer across all three.
Look for four signs: different people get different numbers for the same question, someone still builds reports in Excel, AI can’t see your customers or stock, and nobody can say how margin or returns are counted. If two or more sound familiar, your data isn’t ready yet. It’s also why AI shines in demos: they run on clean sample data. Data quality for AI is the gap we close. Not sure where you stand? Data quality for AI is the gap we close. Not sure where you stand? That’s what the free AI data check is for.
Demos run on clean sample data. Real work runs on your POS, loyalty and inventory data, with all its gaps and conflicts. That gap is exactly what we close.
Yes. Plenty of retailers run stock, customer lists or store reports in Excel or Google Sheets. We bring those files in alongside your other systems, so nobody has to retype anything. If a spreadsheet has outgrown its job, we'll say so and suggest what to use instead.
Yes. Your sales data already shows what people buy together and when. We start there. When you're ready, we'll help you start capturing customer data, so every purchase also tells you who bought it.
No. We connect what you already run, like Shopify, Square, Lightspeed or NetSuite, plus your online store and spreadsheets. Your teams keep working the way they do today. We confirm your exact setup on the first call.
Keep it. A retail analytics platform or BI tool shows numbers. It doesn’t teach AI how those numbers are counted. We build the one place underneath, so your dashboards, reports and AI tools use the same sources and definitions, and they all agree. If you already have a data warehouse, we build on it.
Dashboards show numbers. They don't teach AI how those numbers are counted. We give your dashboards and your AI tools the same source and the same definitions, so they agree. If you already have a data warehouse, we build on it.
The ones you already use: Microsoft 365 Copilot, ChatGPT Enterprise, Claude Enterprise, the AI inside your BI tools and custom AI agents. Your data sits in one place that isn't tied to any of them, so a new tool reads the same numbers and rules from day one.
You don't need a data team. Updates run automatically, and your IT lead gets plain-language docs and a walkthrough. If you'd rather not manage it at all, we offer support plans.
It depends on how many systems you have and how messy the data is. After the AI data check, you get a clear scope, timeline and estimate before you commit to anything.
Dashboards show numbers. They don't teach AI how those numbers are counted. We give your dashboards and your AI tools the same source and the same definitions, so they agree. If you already have a data warehouse, we build on it.
No. That's exactly the kind of mess we fix, whether it comes from acquisitions or fast growth. We match every system to the same stores, products and rules.
Yes. Buy online, pick up in store, ship from store and returns made in another channel are each counted once, under rules your team agrees on. A shopper who buys in both places shows up as one customer.
Yes. We define waste, shrink and markdowns with your team, so AI counts them the way your stores do.
Yes, if your systems track it. We connect stock at the size-and-color level, so AI answers at that level, not just by style.
We’d love to hear from you
Share project details, like scope or challenges. We'll review and follow up with next steps.
