Background pattern
Semantico vs. In-House Build For Ecommerce Directors & Catalog Managers

Build It Yourself or Ship More Products Tomorrow?

Every month you spend evaluating an in-house build is another month your catalog is costing you revenue.

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The Real Cost

What "We'll Build It Ourselves" Actually Costs

The internal build sounds reasonable in a meeting room. Here's what it looks like on a spreadsheet.

AI Infrastructure Costs

LLM API calls at scale (GPT-4, Claude) across thousands of products, plus vector databases, embedding infrastructure, prompt versioning, model monitoring, and fallback logic. These costs compound as your catalog grows.

€2K–€8K/month

In AI infrastructure alone for a mid-size catalog

Engineering & Data Science Salaries

1 ML engineer (€70K–€110K), 1 backend developer (€55K–€90K), 1 data/QA specialist (€45K–€70K). That's before benefits, equipment, and management overhead — for a problem Semantico solves from €4K/year.

€170K–€270K/year

In salaries alone — permanent hires for a solved problem

Time to Build — The Hidden Revenue Loss

Industry benchmark: 6–12 months from kickoff to production. During that time, your team is still doing listings manually, SKUs are delayed, and revenue is deferred. If 500 delayed SKUs each generate €50/month, that's €150K–€300K in lost revenue.

6–12 months

Before your first listing goes live

Ongoing Maintenance & Technical Debt

AI models update constantly. Ecommerce platforms change their APIs. Brand guidelines shift, SEO rules evolve, new channels launch — every update is an internal ticket. With Semantico, updates ship automatically.

Ongoing

Maintenance burden that never ends

Opportunity Cost

Every sprint your engineering team spends on catalog tooling is a sprint not spent on your competitive advantage. The best retailers don't build their own ERP, logistics, or payments — they integrate best-in-class solutions.

You're an eCommerce business,

not a catalog tech company.

Quality & Multi-Brand Insights

We work with dozens of multi-brand retailers and iterate based on their feedback. Build alone, and you're in an echo chamber.

Your V1 won't match

day one — or the feedback loop we already have.

Risk

What happens when your key ML engineer leaves? What if the project is deprioritised mid-build? Who owns the institutional knowledge? With Semantico: zero key-person risk, zero project cancellation risk, SLA-backed delivery.

Zero key-person risk

SLA-backed delivery

Side-by-Side Comparison

How the Two Options Stack Up

Metric Build In-House Semantico
Time to first live listing 6–12 months 24 hours
Engineering headcount 2–3 FTEs 0
Monthly AI infrastructure cost €2K–€8K Included
Annual total cost €170K–€300K+ From €4K/year
Ongoing maintenance Your team Semantico's team
Platform integrations Build each manually Pre-built & maintained
SEO optimisation built in You build it Yes
Multi-language support You build it Yes
Model updates as AI evolves Your cost Included
Speed to listing Days to weeks Minutes
Risk if key person leaves High Zero
Focus on core business Diverted Protected
Multi-brand ecosystem insights Echo chamber — no external input Continuous improvement from market leaders
Proof It Works

The Alternative to Building It Yourself Is Already Working

+8,000

SKUs listed in just one week

Farma2Go launched an entirely new veterinary product vertical — 8,000+ SKUs with descriptions, images, and translations — in 7 days with a team of one.

90% Faster

Time per listing cut from 10 min to under 1 min

What would have taken 1,300+ hours of manual work was handled by Semantico's AI in a fraction of the time — no extra headcount needed.

+50,000

Translations, all on-brand and ready to sell

Every listing translated into five languages without losing brand voice — powered by Semantico's built-in auto-translation and localization engine.

Before You Decide

Before You Greenlight an Internal Build, Ask These Questions

1

Do we have an ML engineer who specialises in NLP and eCommerce product data on staff today?

If not, add 3–6 months of recruiting before the build even starts.

2

Can we afford 6–12 months of delayed listings while we build?

Every month of delay is revenue you're leaving on the table.

3

What happens to this project when the engineer who built it leaves?

Key-person risk is real. Institutional knowledge walks out the door.

4

Is building catalog tooling actually a core competency we want to own long-term?

You don't build your own ERP or payment stack. Same logic applies.

5

What is one month of delayed SKU launches costing us in deferred revenue right now?

Do the math. The number will make the decision for you.

If you can't answer all five confidently — you're not ready to build. You're ready to buy.

Stop Planning the Build. Start Shipping the Products.

Give us 5 EANs. We'll show you a complete, live-ready listing in 24 hours. No commitment, no engineering required.