Product · AI Integration
Empty or boilerplate product cards don’t rank and don’t sell, and copywriters take months to fill a catalog. We connect an AI pipeline to your store: 10 K SKU descriptions overnight. 1C-Bitrix stays, no CMS migration. Live in 2–4 weeks.
Frontbox · core
SSR · ISR · edge cache · facets · synonyms · auth
Stores we set up AI automation for
What changes
A background queue generates descriptions in batches while your managers focus on sales. Templates are tuned to each category and your brand tone. One run fills an empty catalogue or refreshes an outdated one.
100× faster than manual copywriting
Every description passes a model confidence threshold and a uniqueness filter. Texts that fail go into a manual review queue, not to production. You set the quality rules, we run the pipeline.
75% auto-approval rate
Bitrix, Magento, custom backend in PHP or Python — we connect via API or direct database access. Your 1C integration stays intact. Pricing logic is not touched.
no CMS or backend replacement
Elasticsearch with Russian morphology, synonyms and facets. A user types "black jacket for mountain hiking" — the catalogue shows the right result. Connects on top of your existing backend in 1–2 weeks.
< 100 ms with facets at 100 000+ SKU
Content generation, search, "similar products" recommendations and a basic AI support chatbot under one contract with one team. No need to assemble four different SaaS tools and wire them to your store manually.
content + search + recommendations
Case studies
We show projects with real numbers when they are available from the CMS: generated content volume, SEO outcome, and reduced load on the content team.
Benchmarks
How it works
We do not touch your backend. We work with what you have: catalogue, data, CMS.
We review your catalogue structure, data formats and existing descriptions. For each category we build generation templates that take into account what the product, brand and positioning already say about themselves. Output: an agreed set of prompts and quality rules.
We connect to your API or database. We run a test generation on 100–500 products. We review the results together and refine the templates. After sign-off we launch across the full catalogue.
Descriptions are loaded to production, the queue runs in the background. We set up a quality dashboard: auto-approval rate, review queue, uniqueness metrics. From there we maintain the pipeline and update templates when the catalogue changes.
Your backend stays unchanged. AI pipeline is a separate layer.
source
CMS / 1C / DB
→ → →
queue
AI pipeline · background jobs
→ → →
output
Descriptions to prod
Quality control
Before descriptions go to production, every batch passes a quality checklist.
Every text is run through a deduplication algorithm — no duplicate descriptions within the catalogue.
The model does not invent product attributes. If the product card has empty fields, the description goes to manual review, not to production.
Templates are validated for brand voice compliance.
Title and description stay within character limits, key phrases appear in the right positions.
The pipeline does not load the frontend or block site operations.
Everything is generated in staging before going to production. Batch rollback is available in one click.
Comparison
We compare against the two main paths stores choose: build it yourself with the OpenAI API or buy a ready-made SaaS. Honest — no omissions about the weak spots.
Two engagement formats
Both formats start with a catalogue and data audit. The difference is the scope of AI features.
Generation · Your data
For stores with 5 000+ SKU catalogues that need to fill or refresh product descriptions without hiring a copywriting team.
Clarify your budget at the audit — we will calculate for your catalogue size
Extended · All AI capabilities
For stores that need more than descriptions: smart search, recommendations and a basic AI assistant.
Includes everything from AI Content plus search, recommendations and chatbot
| Parameter | AI Content | AI Pilot |
|---|---|---|
| Description and SEO meta tag generation | Included | Included |
| Elasticsearch semantic search | No | Included |
| AI recommendations (similar / cross-sell) | No | Included |
| AI support chatbot | No | Included |
| Time to first result | 2–4 weeks | 4–8 weeks |
| Retainer for pipeline development | Optional | Included |
Formats can be combined. Start with AI Content and add search and recommendations in a subsequent iteration without rewriting the integration.
FAQ
Before launch we build prompts for each catalogue category: we use real attributes from your data, brand voice from examples of your best texts, and a list of forbidden constructions you specify. AI works with data already in the product card — it does not make things up.
Yes. If you have a corpus of good descriptions we use them as few-shot examples or for fine-tuning. Minimum for fine-tuning: 500 examples. Agreed at the audit stage.
1C-Bitrix (any edition), Magento 2, custom backends with REST API, direct PostgreSQL/MySQL connections. Non-standard stack — we discuss it at the audit and check available APIs before estimation.
Every description passes four filters: (1) model confidence threshold, (2) uniqueness filter, (3) structure and length validator, (4) optional manual review for new categories. Fail any filter — goes to the review queue, not to production.
Fixed integration cost starts from 250 000 ₽; the extended AI pilot starts from 450 000 ₽, plus an optional retainer for template maintenance and development. Principle: ROI-positive from the first month with a 5 000+ SKU catalogue.
Audit and templates: 1–2 weeks. Test run: 1 week. Full catalogue processing: usually 2–5 background days depending on batch size and queue settings. Total: 4–5 weeks from kick-off to a filled catalogue.
The API is just the model. You also need: prompt engineering (2–4 weeks of iteration), a background queue, CMS and 1C connection, QA filters, monitoring, and maintenance when the catalogue changes. That is 1–3 months of developer work. We take that on with an already-calibrated pipeline.
Yandex and Google penalise low-quality and duplicated content, not AI content as such. Our pipeline controls uniqueness, structure and informativeness. Text that is useful and unique ranks like any other.
Message us on Telegram with your catalogue size, current stack and goal. We run a free audit in 1–2 business days and give you a preliminary estimate.
