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AI agents for retailers, built on your data

Stop asking AI. Start assigning it work.

Put AI to work on recurring tasks, not one-off questions. We connect your sales, customer and stock data with your business rules and build an AI agent that takes weekly tasks off your team’s plate. Secure from day one, with your data under your control.

No data team needed. We connect your data, build the agent and hand it over.

Pick AI's first job

Free, 30 minutes. Bring one task your team repeats every week. We'll show you how AI could take it over.

Not ready to talk? See where AI can help your business in 3 minutes →

250+

projects delivered

35+

AI solutions delivered

92%

client retention

Your team already uses AI.
Just not for the work that matters.

Nobody waited for a rollout. Your people found ChatGPT, Claude or Gemini on their own, and it helps. It drafts emails, fixes formulas and answers questions, often in personal accounts with company data pasted in. But the weekly reports, lists and checks still get built by hand.

Marketing

AI guesses whether the promo worked

Someone exports last week's sales and asks AI if the spring promo paid off. AI can't see who bought, so it guesses from totals. Nobody knows if the promo brought in new shoppers or just discounted your regulars.

Merchandising

The reorder list still lives in three spreadsheets

AI helps with the formulas. It can't see stock in your other stores. So you reorder an item that's sitting in a back room across town.

STORE OPERATIONS

Every manager gets their own number

Each manager prompts AI their own way and gets their own answer. One counts returns, another doesn't. You can't compare stores, so you can't tell where to send help.

Owner

Your data lives in accounts you don't control

Sales reports and customer lists get pasted into personal AI accounts. Nobody knows where that data is now, or who keeps it when someone leaves.

1 in 2

It's not just your team. Half of Americans who use AI for work rely only on personal or free accounts. Just one in three uses AI their employer provides.

Source: Epoch AI / Ipsos national poll of 2,021 U.S. adults, published April 2026. Ipsos, 2026

Your team already proved AI is useful.
Now give it your data and a real job.

Your AI is smart. It just can't see your business.

AI in a personal account knows only what someone pastes into it. To do real work, it needs three things it doesn’t have.

None of them comes with a newer model.

The first two are about your data, so we start there.

Then the agent gets its job.

Your data

Sales from the POS, customers from loyalty, stock from inventory. All of it, not just this morning’s export.

Your rules

How your team counts margin, returns and shrink. AI can’t guess them from a spreadsheet.

A job

A weekly task to deliver, not a question to wait for.

The smartest first AI move isn't AI. It's your data.

Take AI from personal use to everyday operations, in two steps.

Connected data

POS, online store, loyalty, inventory and spreadsheets in one place, updated automatically.

Counted your way

Sales, margin and returns defined once, the way your team already counts them.

One clear job

One task, one schedule, one format. Agreed with your team before we build.

People approve

The agent prepares the work. Your team reviews it and makes the call.

Connected data

POS, online store, loyalty, inventory and spreadsheets in one place, updated automatically.

Counted your way

Sales, margin and returns defined once, the way your team already counts them.

One clear job

One task, one schedule, one format. Agreed with your team before we build.

People approve

The agent prepares the work. Your team reviews it and makes the call.

Before/after example

Asking AI

A manager's Monday, as a chain of steps:

$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

Assigning AI

Monday, 8:00 · Weekly priorities

From your data · Counted your way · Ready for your review

$25,850

How it's counted:
Net sales · stores + online · returns deducted · in-store pickups counted once · updated daily

Same work. Done before Monday's first coffee.

Your AI stops waiting for questions. It does the job on schedule, from your data, counted your way. Your team reviews it and decides what to do.

Four jobs your team can hand over first

Each one runs on your connected data. The agent does the legwork.

Marketing

Promo check and win-back list

Weekly



Who came back after the promo, who didn’t, and which regulars have gone quiet. The agent sees who bought, not just what sold, so the list comes from real purchases, not a guess from totals.

You decide which offer to send, to whom, and how to plan the next promotion.

Merchandising

Reorder draft

Weekly, before your order deadline


‍
A draft replenishment list based on what sold and what's in stock across every store, back rooms included. It flags items another store can transfer before you buy more.

Your buyer reviews the draft and places the order.

Store operations

Store scorecard

Weekly



Every store counted the same way, by your rules. The agent shows which stores fell behind on sales or margin, and by how much.

Your managers find out why and decide what to fix. The agent points to the gap. It doesn't guess the reason.

Owner and finance

Monday brief, kept in-house

Monday, 8:00



One page across stores and online: sales, margin, stock risks and customer trends, counted your way. It runs in your company’s accounts, so nobody pastes your numbers into a personal AI account to get it.

You decide where to focus the week.

Your AI’s first job,
set up end to end

Not a chatbot and not a slide deck. A working setup: your data in one place and one AI agent doing one job your team agreed on.

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Your sales, customer and stock data connected
POS, online store, loyalty, inventory, even spreadsheets. Shopify, Square, Lightspeed or NetSuite keep running as they do today. Nothing gets replaced.
01
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Your numbers defined once
Net sales, margin and returns, counted the way your team counts them and written down, so anyone can check.
02
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One AI agent for one job
The task, the schedule, the data it can see and the format of the result, agreed with your team.
03
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Results delivered where your team works
Email, Teams or Slack. Nobody has to learn a new tool.
04
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Tested on your real data
Before handover, we check the agent's results against your own reports.
05
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Docs and handover
Plain-language docs and a walkthrough for your team. You own everything we build.
06

Ready for the next job? The next agent builds on the same connected data, without starting from scratch.

Get in touch

Four steps from first call to first finished job

You get a clear scope, timeline and 
estimate before any work starts.

Pick the first job


A free 30-minute call. We look at how your team uses AI today, which tasks repeat every week and where your data lives. Then we pick one job worth handing over.

Bring your data together


We connect your systems, match stores, products and customers, and agree with your team on how you count your key numbers.

Build and test the agent


We build the agent for that one job and run it on your real data. Then we compare its results with your own reports before your team starts using it.

Handover


Docs, a walkthrough and full ownership. Want us to keep it running or add the next job? We offer support plans.

Pick the first job


A free 30-minute call. We look at how your team uses AI today, which tasks repeat every week and where your data lives. Then we pick one job worth handing over.

Bring your data together


We connect your systems, match stores, products and customers, and agree with your team on how you count your key numbers.

Build and test the agent


We build the agent for that one job and run it on your real data. Then we compare its results with your own reports before your team starts using it.

Handover


Docs, a walkthrough and full ownership. Want us to keep it running or add the next job? We offer support plans.

What we need from you

One point person, access to your systems and a few short sessions with the person who does the task by hand today.

Stop sending your data to AI. Bring AI to your data.

Stays in your company’s accounts

We set everything up in accounts your company owns, not ours and not anyone’s personal one. The agent runs there too.

You own it

The agent, the data setup and the docs stay with you.

Access by role

Each person and the agent see only what they're allowed to see.

Customer details stay private

The agent can work with customer groups and buying patterns without seeing names, emails or phone numbers, unless a job needs them and you approve.

NDA first

We sign an NDA before we see any of your data.

Your team uses AI.
Your business doesn't
yet.

Built for U.S. retailers who

Run several physical stores, with or without an online shop

‍

Have people using ChatGPT, Claude or Gemini on their own, with no company-wide rollout

Have rolled out an AI tool company-wide, like Microsoft 365 Copilot, 
ChatGPT Enterprise, Claude Enterprise or the AI inside your BI

Repeat the same reports, lists or checks every week

We sign an NDA before we see any of your data

Keep sales, customer and stock data in different systems or spreadsheets

We sign an NDA before we see any of your data

Free · 30 minutes · NDA before we see any data

Find the first job
for your AI

We build the foundation first,

then the agent.

AI agents that actually know your business, because they work from your sales, customers and stock, counted your way.

Data first,
not a chat window

Most AI tools wait for questions and see only what you paste. We connect your data first, so the agent works from the full picture.

We build it, you own it


No black box and no lock-in. The agent, the data setup and the docs stay with you.

One foundation,
many jobs

The next agent builds on what's already there, not from scratch.

Name...

AI in a personal account

Your AI agent, built by Dataforest

Works when

Someone asks

On schedule

Sees

Whatever gets pasted in

Your sales, customers and stock, connected

Counts margin

Its own way

Your way, defined once

Your data

Sits in personal accounts

Stays in your company’s accounts

How a U.S. fashion retailer connected every store and grew sales 17%

Case study

Fashion retail

United States

What we did

We connected the cash registers in every store to one central system. It tracks sales deviations as they happen and notifies staff when their KPIs stay off target, with tips on what to improve.

17%

increase in sales

25%

improvement in employee KPI achievement rate

Not an AI agent, but the same pattern: connect every store, count it one way, flag what’s off and let people act.

How a global luxury retailer saved $142M with store-by-store forecasts

Case study

Luxury retail

3,000+ stores

The problem

The retailer needed to cut inventory costs across 3,000+ stores without running out of stock and hurting its premium brand. Customers in each market buy differently, so one assortment couldn’t fit every store.

$142M

saved by cutting excess inventory

88%

forecast accuracy

Same idea, at your scale. Your AI agent reads sales and stock across every store and drafts what each one needs. Your buyer decides.

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

Reviews

Blake Fausett

Blake Fausett

Principal Systems Architect at Sagis Diagnostics
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Dmitri Nedelchev

Dmitri Nedelchev

Head of Risk Management at ICU
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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.

Stuart Theobald photo

Stuart Theobald

Chairman Intellidex, Financial Services and Consulting company
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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.

Josef G. photo

Josef Ganim

Founder & CTO Dropship.io
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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!

Jonathan Lien photo

Jonathan Lien

CEO Advanced Clear Path, Inc., E-commerce Company
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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. 

Enrico Cattabiani photo

Enrico Cattabiani

Founder & CEO IDN, Infrastructure Deals Network
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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.

Robert P. photo

Robert P.

CTO Cybersecurity
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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.

Kate Shcherbak

Kate Shcherbak

Product Marketing Manager, Software Development Company

Qvist Sweden AB

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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.

Darleen Lydia

Darleen Lydia

Partner, Qvist Sweden AB

Give your AI its first job

A free 30-minute call. Bring one task your team repeats every week, and we'll show you how an AI agent could take it over.

Pick a time

What we’ll cover
in 30 minutes

Not ready to talk?
See where AI can help your business in 3 minutes

Pick a time

How your team 
uses AI today

‍

Which tasks repeat 
every week

Have rolled out an AI tool company-wide, like Microsoft 365 Copilot, 
ChatGPT Enterprise, Claude Enterprise or the AI inside your BI

Where your sales, customer 
and stock data live

We sign an NDA before we see any of your data

Which job to hand over first, and 
what your data needs for it

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

Yes. You don't need a rollout to start. You need one task worth handing over and the data behind it. We start with one job, prove it on your real numbers, and then you decide what's next.

It's a good sign. They've found where AI helps. The risk is where your data ends up: sales and customer lists pasted into personal accounts leave your control. We give that work a safe home. The agent runs in your company’s accounts, on your data, with access you set.

No. The agent doesn't depend on a company-wide AI license. If you already have one, or buy one later, it can read from the same data. We'll walk you through any AI usage costs before we start.

AI with a job description. It knows its task, its schedule, the data it can use and who gets the result. A chatbot waits for your question. An agent does the work on schedule and hands it to a person to review.

Use it. Built-in AI is good at questions inside its own system. But weekly work usually crosses systems: sales from the POS, customers from loyalty, stock from inventory. Each vendor's AI sees only its own piece. Your agent works from all three.

That's why people approve its work. Before handover, we test the agent on your real data and check its results against your own reports. After that, every result shows how it was counted, so anyone can check it. If something looks off, your team catches it before it goes anywhere.

No. It takes over the repetitive part of a job, like pulling exports and building the same report every week. Your people still make the calls: what to reorder, which offer to send, where to send help.

Your data stays in your company’s accounts, and each person and tool sees only what it’s allowed to. Customer names, emails and phone numbers stay out of the agent’s reach unless a job needs them and you approve. We use the business versions of AI services, which don’t train on your data. And we sign an NDA before we see anything.

One your team repeats every week, that follows the same steps and that someone checks by hand today. Weekly priorities, a reorder draft or a promo check are good first jobs. We'll pick yours together on the first call.

No. That's exactly the kind of mess we fix, whether it comes from acquisitions or fast growth. We connect each system and match every store, product and customer to the same rules. The agent sees one business, not five systems.

Yes. Reorder drafts and store scorecards run on sales and stock data alone. Jobs about specific customers, like win-back lists, need customer data from loyalty or your online store. When you're ready to capture it, we'll help.

Yes, if your systems track the detail. For grocery, we define waste, shrink and markdowns with your team, so the agent counts them the way your stores do. For apparel, we connect stock by size and color, so reorder drafts go below the style level.

Yes. We bring those files in alongside your other systems, so nobody retypes anything. If a spreadsheet has outgrown its job, we'll say so and suggest what to use instead.

You don't need a data team. Data updates and the agent's schedule run automatically. Your point person gets plain-language docs and a walkthrough. If you'd rather not manage it at all, we offer support plans.

It depends on your systems, your data and the job. After the first call, you get a clear scope, timeline and estimate before you commit to anything.

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.

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