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Answers and forecasts for your store, from the data you already have

Connect any data your store has: your online store, point of sale, ad accounts, inventory, accounting, spreadsheets or your own database. Ask a question in plain English, get a number your finance team agrees with, and approve the next step. You don’t need to write code or hire a data team.

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  • Shopify
  • Meta Ads
  • Google Ads
  • GA4
  • QuickBooks
  • + any other source you use

Optialy

  • Forecast refreshedRain shell: 412 units next month
  • Reorder draftedRain shell, 240 units. Needs OK
  • Field fix proposedMeta renamed purchase_value
  • Budget recommendationMove $4K from social to search

Who uses Optialy

Small online shops, retailers selling on several channels, and larger teams with their own analysts.

Online stores and DTC brands

The answers are somewhere in Shopify, Meta and your spreadsheets. Nobody has time to dig them out.

Ask in plain English and get the number in minutes, with the next step already drafted.

Multi-channel retailers

Your store, Amazon, wholesale and ads each count sales differently, so the totals never match.

One set of definitions across every channel, so everyone works from the same numbers.

Retailers with a data team

Your analysts spend the week on report requests and fixing broken pipelines.

Optialy takes the routine questions and the upkeep, so your analysts can spend their time on bigger projects.

Three jobs you would otherwise hire for

Optialy does the data engineering, analysis and machine learning work behind your reports and forecasts.

Data engineering

  • Connects to any system, database or file your store uses, without copying the data
  • Cleans and joins orders, ad spend, stock and finance records
  • Keeps reports working when a platform changes a field

Usually a data engineer. In Canada that’s about CAD 113K a year.

Analysis

  • Answers questions that need several systems at once
  • Finds out why a number went up or down
  • Works out margin, ad return and repeat buyers on every order

Usually a data analyst, or hours of someone’s week.

Machine learning

  • Builds a demand forecast for each product
  • Keeps a model only if it beats a simple benchmark on weeks it hasn’t seen
  • Retrains as new sales come in and reports how accurate it is

Usually a data scientist or machine learning engineer.

Salary: Indeed Canada, average data engineer base salary, October 2026. See it working

Ask it the way you’d ask a colleague

Type a question. Optialy reads the systems involved, works out the answer and suggests what to do next.

ReadingShopifyNetSuite
3 products

Rain shell (navy) runs out Thursday, wool beanie and trail socks on Friday, at this week’s pace.

Draft reorders

Setting it up takes three steps

You don’t need to write code or SQL, or bring in a data team.

  1. 1

    Connect

    Sign in to your store, ad accounts, inventory and accounting tools, or upload a spreadsheet. Your own database works too. Optialy reads the data without copying it anywhere.

  2. 2

    Confirm

    Optialy suggests what your key numbers mean. Tick the ones that are right and fix the rest.

  3. 3

    Ask

    Type a question here, in Slack or in ChatGPT. Approve the suggested action with one click.

Why not just use ChatGPT?

ChatGPT writes and summarises well, but it doesn’t know how your company counts sales, and it often works from a sample of your data. You can still use ChatGPT, because Optialy works inside it.

“What was our net revenue last month?”

ChatGPT with a sales export$1.42M

Counted wholesale orders and used totals from before refunds. No sources shown.

Optialy$1.18M

Your finance team’s definition, applied to every Shopify and NetSuite record, with sources linked.

Illustrative example.

ChatGPT on its ownOptialy
Knows how your company counts revenue, margin and stockGuesses from column namesUses definitions your team confirmed
Reads your store, ads, ERP and finance togetherExports, or one connector at a timeAll of them at once, live
Does the mathInside the language model, often on a sampleIn code, on every row
Shows where each number came fromRarelyEvery figure linked to its source
Keeps reports working when a platform changes a fieldNoSpots it and proposes a fix
Forecasts you can plan withDraws a trend lineTested on past data before you see it
Takes the next stepWrites a suggestionDrafts the reorder or budget change for you to approve

On 500 real questions from our pilot retailers, Optialy answered 90% correctly. General AI assistants with the same data managed 60 to 68%. How we tested

Get answers without waiting on the data team

A simple report request often takes days of messages. With Optialy, the person who asks gets the answer directly.

Without Optialy4 days, 5 messages

  1. MarketingCan you pull ad return by campaign, with repeat buyers?

  2. Data teamWhich dates? Net or gross revenue?

  3. MarketingLast 30 days, net.

  4. Data teamHere’s the spreadsheet.

  5. MarketingCan you split it by new and returning customers?

With OptialyAbout 3 minutes

  1. MarketingAd return by campaign last 30 days, net, split by new and returning customers.

  2. OptialyDone. Search leads at 5.1×, and returning customers from search reorder 2.4× as often. Chart and sources attached.

Our lead customer got answers drawn from four systems, with sources, in two to three minutes.

What data requests cost you now

195 hours a month go into pulling and checking numbers

CAD 129K a year in staff time

Hiring a data engineer instead costs about CAD 113K a year in Canada. Optialy is priced per user and per connected system, and answers routine requests in minutes.

Your estimate, from your inputs. Salary: Indeed Canada, October 2026.

What the engineering and forecasting work looks like

This runs in the background. You only see it when something needs your OK.

FieldProposed meaningOwnerStatus
net_salesOrder total minus refunds, discounts and gift cardsFinanceConfirmed
wholesale_orderWholesale order. Left out of online revenueFinanceConfirmed
qty_availableOn hand minus committed, across both warehousesOperationsConfirm
conv_valueRevenue Google reports, not matched to ordersMarketingConfirmed
+0%

return on ad spend for our first customer within two months.

0%

of 500 real retail questions answered correctly.

0 min

for our lead customer to get an answer drawn from four of their systems, with sources.

Read how our first customers use it

See it on your own store

In a 20-minute call we connect two of your systems and answer a question from your business.

Book a demo