Service · AI Commerce Automations
AI automation for eCommerce operations
We build AI workflows inside your platform that remove repetitive manual work: product descriptions, translations, marketplace content, data quality, reporting and support. One rule: if it doesn’t save time, improve quality or support sales, we don’t build it.
- Priced per workflow
- Inside the platform
- Measurable savings
−34 h / mo
Manual work removed in a typical setup
Per workflow
Add automations only where they pay back
PL → DE / EN
Descriptions and translations at catalog scale
Services in this line
Pick the exact scope you need
AI Product Descriptions
On-brand descriptions, generated and reviewed at catalog scale
02AI Catalog Translations
An always-translated catalog with native review built in
03Feed Automation
Feeds mapped, validated and monitored per channel
04AI Customer Service
Reply drafts with full order context, sent in seconds
05Listing Error Analysis
Offer scans, auto-fixed violations and error-cause trends
What we build
AI Workflows
4 active · 1 testingHow it goes
From kickoff to a working platform
Manual work map
We find where your team loses hours, content, translations, product data, reporting, and pick the workflows with the fastest payback.
Workflow pilot
The first workflow runs on your real data with a quality gate: a human reviews before anything is published.
Into the platform
Automations live in your admin panel, not in a separate tool. The team approves results instead of rewriting them.
Measure & extend
We count hours saved per workflow and add the next ones only where the numbers say they pay back.
When it makes sense
Content eats whole days
Descriptions and translations for several markets take days of your team’s week, every week.
Product data lives in spreadsheets
Attributes are incomplete, categories inconsistent, and nobody trusts the data fully.
Reports and fixes are manual
Feed errors get fixed by hand and reports are assembled one export at a time.
In practice
12,000 SKU described by workflows, approved by people
The example rollout below: 12,000 SKU described and translated by workflows inside a retailer’s existing platform, 58 hours back every month.
Example build · Multibrand retail
AI workflows dropped into an existing platform: descriptions, translations and feed localization with human review. Measured in hours saved, not AI hype.
An example build: it shows the scope, pace and delivery model of a typical BEAM engagement. The brand shown is illustrative, hence the blurred logo.
„Content for three markets used to take two days a week. Now the platform does it and we review before publishing."
FAQ
AI automation for eCommerce operations
Isn’t AI content bad for quality or SEO?
Not when it runs inside a clear process with review. We generate drafts at scale, apply your rules and tone, and keep a human approval step before publishing.
Do automations run inside our platform or as a separate tool?
Inside the platform, as controlled workflows in the admin, with triggers, run history and time saved, not a random tool bolted onto your checkout.
Which tasks can realistically be automated?
Repetitive, rule-based work: content, translations, attribute mapping, feed localization, listing checks and reporting. We pilot 2-3 workflows first.
How do you measure the value of an AI workflow?
In time saved and quality: each workflow reports how much manual work it removes per month. If it doesn’t save time or support sales, we don’t build it.
Where should a store start with AI automation?
Usually with content: product descriptions and translations. The volume is high, the quality gate is easy to set up and the payback is visible within the first month.
Does AI publish content without human control?
No. Every workflow has a review step, AI prepares, a person approves. That rule is why the output can go straight to your storefront and marketplaces.
Stack & integrations
Technology we build this on
Delivered on the BEAM framework: fixed scope, fixed price, a partner who stays.
Explore the framework →