Good data before the model.
Attributes, specifications and existing content are the starting point. We define permitted sources and facts the model must not invent. Missing essential information should be flagged rather than filled in arbitrarily.
AI for eCommerce
Bring AI into real store workflows: descriptions, translations, search and catalogue processing. With reviewed data and explicit publishing boundaries.
Let’s discuss your projectTHE CHALLENGE
More possibilities.
With practical control.
Content, translation and search grounded in actual data and reviewed before publishing.
The final scope follows your systems, available access and the way your business operates.
CatalogueAI + ReviewContent
WHAT IS INCLUDED
The connections.
And what supports them.
Bring AI into real store workflows: descriptions, translations, search and catalogue processing. With reviewed data and explicit publishing boundaries.
- Product descriptions & enrichment
- Translation with consistent terminology
- Search across your actual catalogue
- Content review & approval workflows
FROM PLAN TO PRACTICE
The right decisions.
At every stage.
Draft, review, publish.
We design stages for generating and approving descriptions or translations. Terminology, tone and product facts are reviewed on a representative sample. Batch execution starts after quality criteria and a way to restore previous content are agreed.
Evaluate real cases.
For search and product discovery, we use real queries and available products. We assess failures, response time and workflow cost. The design can combine conventional rules and AI according to the result customers need.
HOW WE CHECK THE RESULT
Working is the start.
It has to work for you.
We use representative data to test successful runs and exceptions. Handover includes operating instructions, checkpoints and explicit responsibilities.
- Approved product data sources
- Evaluation sample and acceptance criteria
- Cost and batch execution limits
- Publishing permissions and rollback
RELATED PLATFORMS & WORKFLOWS
Your use case.
In more detail.
Explore individual capabilities and prerequisites. Feature support is confirmed for your installation before implementation.
AI product descriptions
Generate product descriptions and SEO metadata from verified attributes, with factual checks, approvals and controlled publishing.
AI catalogue translation
Translate descriptions, attributes and categories using a shared glossary, protected identifiers and editorial review.
Smart product search
Product search with Greeklish handling, typo tolerance and synonyms, combined with fresh catalogue data and meaningful filters.
AI content & SEO
Create buying guides, articles and SEO metadata with AI, genuine customer questions, verified sources and editorial approval.
FREQUENT QUESTIONS
Answers.
Clear from the start.
What working together involves, and what you need to know before we begin.
Will AI publish without review?
Generation and publishing are separate steps. We agree what needs approval and what can proceed through automated checks. Rules depend on the content and the risk of incorrect information.
Do I need to change platforms?
Not necessarily. We assess catalogue access and content update capabilities in your current platform. The integration approach follows a review of data, interfaces and team needs.
How are cost and timeline determined?
Scope, the state of your existing platform, dependencies and required checks. Before work begins, a specific proposal records deliverables, prerequisites and approval stages. Software licences, third-party charges and recurring services are separated so you understand what the engagement includes and what affects a later change.
What support will we have after handover?
We hand over the documentation and instructions included in the agreed scope. Responsibilities for daily operation, issue reporting and future requirements are defined. Ongoing support, updates and monitoring have an explicit, separately agreed scope rather than relying on an assumption that someone will take care of them.