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You can vibecode it in a week. Then spend a year making it work.

Thinking about building product enrichment with generic AI tools or your own agent? Every ecommerce team has this conversation. Here is how it actually plays out.
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Act 1

The Cost

Tom, CEO
Hey, talked to the board. They want to just build this product enrichment thing in-house. Dev said one week with Claude Code. 🚀
Mark, CTO
One week to a demo. Not one week to production.
Tom, CEO
What's the difference 😅
Mark, CTO
About 11 months and 2 engineers.
Also - did anyone price the API calls? Native Anthropic/OpenAI runs €1.20-1.60 per product. We have 80,000 SKUs.
Tom, CEO
…per product??
Mark, CTO
And translations - DeepL is roughly 10x more expensive than what Lasso charges. Google Translate API is not far behind.
Cost per product
Native LLM €1.20-1.60 · DeepL ~10x Lasso · Lasso €0.08-0.40
Run your numbers →
Tom, CEO
OK but we save on the subscription, right?
Mark, CTO
You're trading a predictable subscription for two senior engineers, six months of meetings, evals, prompt regressions, and an API bill that scales with your catalog. That's the actual trade.

What you actually pay

Native LLM APIsLasso
Cost per product€1.20–1.60€0.08–0.40
Setup timeMonthsDays
Engineering requiredSignificantMinimal (SDK/API)
Glossary supportNoneYes, with supplier context
Verification layerBuild it yourselfBuilt-in
Act 2

The Build

Tom, CEO
OK but we already have our own admin. The team built it last year. We can just bolt AI onto it.
Mark, CTO
We do not need to throw it away. Lasso has an SDK and an API - they enrich products into the system we already have.
Tom, CEO
Wait, really?
Mark, CTO
That's how most of their customers do it. Nobody rips out their PIM.
Tom, CEO
Fine - but we want speed. Our dev says they can parallelize it.
Mark, CTO
Parallelize against what rate limits? Anthropic gives you a few hundred concurrent calls before throttling. Lasso spawns thousands of agents in parallel - months of infra work we would be redoing.
Tom, CEO
Can't we just use Claude Code or ChatGPT for product enrichment?
Mark, CTO
Sure, if you want hallucinated specs, no glossary control, no supplier-file context, and a tool our merch team can't actually use.
Why generic agents fail on product data
Hallucinations · No verification layer · No glossary · Unstable for non-technical users · Token costs explode
Tom, CEO
What's the glossary thing again?
Mark, CTO
Translation exceptions. Brand terms, units, regional spellings, supplier quirks. Generic translators get them wrong every time. Lasso's uses your supplier files as context.

What you actually have to build

DIY architecture

You build all of this.

Your app
LLM provider
Translation API
Custom prompt layer
Eval scripts
Monitoring
Glossary system
Verification layer

With Lasso

We built this. You use it.

Your system
Lasso SDK / API
Done
Act 3

The Aftermath

Tom, CEO
Last thing the board asked - flexibility. They want something we can shape ourselves.
Mark, CTO
Lasso is modular. If we need a custom feature, they build it for us. We get flexibility without owning the codebase.
Tom, CEO
What about lock-in though?
Mark, CTO
The data is ours. Export it any time, switch vendors, bring it in-house later if we really want. That is in their terms.
Tom, CEO
Huh. That's the opposite of what I assumed.
Mark, CTO
And one more thing - if we build it, it is frozen on day one. Lasso ships updates every week based on customer feedback. Our DIY version gets whatever we have time to maintain. Which is nothing, because we will be busy.
Tom, CEO
Maintenance… right.
Mark, CTO
Supplier changes their feed format at 2am on a Sunday. Who fixes it? Me. Every time.
Tom, CEO
😬
Mark, CTO
With Lasso that's their problem. They've already seen it from 50 other catalogs.
What you actually own when you DIY
The bug list · The on-call pager · The roadmap nobody has time for · The API bill
Tom, CEO
OK. Let's just book the demo.
Mark, CTO
🎯

Twelve months from now

LassovsDIY
Day 1
Kickoff
Discovery
Week 2
Integration
1 month
Live
2 months
Enriching catalog
Prototype
4 months
Eval framework
6 months
Translation pipeline
8 months
Glossary system
10 months
Infra
12 months
Still debugging

Go live in weeks, not quarters.