Scriptix
AI & Software Development for Retail
Retail software lives or dies on two things most other industries don't have to worry about as much: staying in sync across every channel, and holding up when traffic spikes ten times overnight.
What We Cover
What This Usually Means
Most retail businesses sell across multiple channels (a website, a marketplace listing, a physical store), and inventory needs to stay accurate across all of them in something close to real time. An out-of-sync stock count isn't a minor bug; it's a canceled order and a frustrated customer.
Traffic is also fundamentally spiky in a way most software doesn't need to plan for: a sale event or a viral moment can send load up by an order of magnitude for a few hours, and the system either handles it gracefully or falls over exactly when it matters most.
Personalization and recommendations are worth doing, but only when they're actually earning their keep. A generic "customers also bought" widget that doesn't reflect real purchase patterns is worse than no recommendation at all, since it signals the platform doesn't understand its own customers.
How Our Services Apply
Data Engineering
Inventory and order data kept in sync across every sales channel.
AI Automation
Recommendation and personalization models grounded in real purchase data.
Custom Software Development
Order management and POS integrations built around how you actually sell.
Cybersecurity Consulting
PCI-conscious payment handling and protection against fraud at checkout.
See what this looks like in practice: an illustrative scenario on building a recommendation engine from real purchase data →
Common Questions
Can you integrate with our existing e-commerce platform? expand_more
Yes. Whether that's Shopify, a headless commerce setup, or a custom-built platform, we typically integrate with what's already generating revenue rather than proposing a full replacement upfront.
How do you handle traffic spikes during sales? expand_more
Auto-scaling infrastructure and load testing before the event, not after a failure during it. We design for the peak load you expect, with headroom, rather than average-day traffic.
Is personalization worth it for a smaller catalog? expand_more
Sometimes simple rule-based merchandising outperforms a full recommendation model when the catalog is small, so we'll tell you honestly if a lighter-weight approach makes more sense than a model that needs data you don't have yet.
Building or scaling a retail platform?
Tell us about your channels and traffic patterns, and we'll help you think through what to prioritize.
Talk to Us