Retail & e-commerce · Local & private AI
Local and private AI for retail and e-commerce
Commerce AI work is repetitive and huge. Descriptions, attributes, support triage, review summarization. These are exactly the tasks where per-token pricing turns a useful tool into a line item nobody can defend at the end of the quarter. Self-hosting changes the arithmetic.
- Service
- Local & private AI models
- Industry
- Retail & e-commerce
- Covers
- Jewelry & fine goods · Salon & beauty retail · DTC brands
- Architecture
- Unchanged from every other vertical — only the breaks differ
- Engagement
- A defined build, or run under management
What usually breaks
Before anything gets built.
The same failures recur across retail & e-commerce. Strygon maps the specific system before proposing anything, but these are the ones worth checking for.
Slow storefront
The store is slow enough that ranking and conversion both suffer, and every speed test is a lost sale.
Blind tracking
Attribution runs on client-side pixels that browsers now block, so no one trusts the numbers.
Manual orders
Custom orders and invoices run on emailed PDFs and memory. That works at ten orders and breaks at a hundred.
The approach
What Strygon does about it.
Local & private AI models, aimed at those failures specifically rather than at a generic checklist.
What gets built
Concrete deliverables.
Everything in local & private ai models, applied to how retail & e-commerce actually runs.
Also for this industry
Other parts of the same system.
Start
Start with what’s broken.
Send the situation in a paragraph. Strygon comes back with a read on what’s likely wrong and what it would take to fix, before anyone talks about price.
Most builds start withleads dying in an inbox., three half-finished pipelines., follow-up nobody owns., numbers that never agree., four vendors blaming each other.
Or email hello@strygon.com
- What to send
- A paragraph. What broke, and where it shows up.
- What comes back
- A read on what is likely wrong and what fixing it takes.
- Price
- The last conversation, not the first