Retail software development for stores and omnichannel teams

Ryz provides retail software development through senior Latin American engineering teams and AI pods that build the systems behind physical stores and omnichannel operations: POS software development and integrations, store inventory and RFID, associate apps on handheld devices, loyalty programs, pricing and promotions, and replenishment. Our engineers are the top 1% of the tens of thousands we interview, work on US business hours so store issues found in the morning get fixed the same day, and Fortune 500 engineering teams trust them with production systems.

Store systems carry constraints web software does not: lanes that must keep selling when the network drops, payment terminals in PCI scope, thousands of devices to update without closing a store, and inventory counts that drift every hour. If your focus is the online storefront (Shopify, Adobe Commerce or headless), see our ecommerce development page.

What we build for retail teams

• POS software and integrations. Extensions and integrations for Oracle Retail Xstore, NCR Voyix, Toshiba, Shopify POS, Square and Lightspeed, plus custom POS front ends with offline transaction queues that sync when connectivity returns.
• Store inventory and RFID. Real-time stock positions per store, cycle count apps, receiving and transfers, and RFID programs built on GS1 EPC standards that make store inventory accurate enough to promise online.
• Associate and store operations apps. Android apps on Zebra and Honeywell handhelds for picking, price checks, markdowns, task management and planogram compliance, managed through MDM tools.
• Omnichannel fulfillment. Buy online pick up in store, curbside, ship-from-store and endless aisle, with store-level inventory reservations and pick lists that fit how a store actually runs.
• Loyalty and customer identity. Points, tiers and offers that work the same at the register, in the app and online, with one customer profile across channels.
• Pricing, promotions and shelf labels. Promotion engines that calculate identically at the POS and online, and price updates pushed to electronic shelf labels so the shelf matches the register.
• Self-checkout and kiosks. Self-checkout flows, scan-and-go mobile apps, and kiosk software with exception handling for age-restricted items and weighted produce.
• Replenishment and allocation. Store-SKU forecasts, order proposals, and allocation tools that feed buyers and distribution centers.

Where AI pods help in retail

Retail AI succeeds or fails on data quality: inventory records that are wrong, promotions that distort history and products with no sales yet. Our AI pod teams start there.

• Demand forecasting at store-SKU level. Models in Databricks or Snowflake that handle promotions, weather, local events, stockouts that hide true demand and new items with no history. The output feeds replenishment and buyer tools, with forecast accuracy tracked per category.
• Shelf and out-of-stock detection. Computer vision on shelf images from fixed cameras, robots or associate phones to spot gaps and planogram errors. The challenge is lighting, occlusion and thousands of look-alike packages, so models are trained and evaluated on images from your own stores.
• Loss prevention at the POS. Scoring refunds, voids, discounts and self-checkout exceptions for patterns such as refund fraud and sweethearting, with explainable reasons and a review queue for asset protection teams. One of our pods built fraud detection for a global fleet company that confirmed $5.94M in fraud, validated by the client's fraud team; the same approach applies. See the case studies.
• Associate assistants. A handheld assistant that answers "how do I process this return" or "where is this item" from your SOPs, planograms and live inventory, with answers that cite the policy so associates can trust them.
• Personalized offers. Loyalty offer selection based on purchase history across channels, with guardrails on margin, frequency and fairness, measured with holdout groups.

Regulations and constraints our engineers work within

• PCI DSS v4.0.1 and PCI P2PE. Point-to-point encrypted terminals and tokenization keep card data out of store systems. Our engineers have experience designing POS integrations that keep scope small.
• Privacy laws. CCPA/CPRA and other state privacy laws for loyalty and customer data, including deletion and opt-out requests that must reach every system holding a profile.
• Biometric privacy. Illinois BIPA and similar state laws restrict in-store facial recognition and other biometric capture, which matters for any camera-based AI.
• Accessibility. ADA expectations for kiosks, self-checkout and associate-facing tools, plus WCAG 2.1 AA for customer apps.
• Sales tax and payments programs. Tax calculation at the register through Avalara or Vertex, and SNAP/EBT acceptance rules for grocery retailers.
• Age-restricted sales. ID verification flows at the POS and self-checkout for alcohol, tobacco and other restricted products.

Our engineers work within your security program and your auditors' controls. Ryz does not claim PCI DSS or SOC 2 certification for its teams.

Integrations and data

• Merchandising and ERP: Oracle Retail Merchandising, SAP S/4HANA, Microsoft Dynamics 365 Commerce and NetSuite.
• Supply chain: Manhattan Associates and Blue Yonder for warehouse and replenishment, EDI 850, 856 and 810 with vendors, and ASN-driven store receiving.
• Store hardware standards: UnifiedPOS (OPOS and JavaPOS) for scanners, printers, scales and cash drawers, and Zebra DataWedge for handheld scanning.
• Workforce: UKG and Zebra Workcloud for scheduling and tasks.
• Data: transaction logs streamed into Snowflake, BigQuery or Databricks, modeled with dbt for sales, shrink and inventory accuracy. Our data engineering teams build these pipelines.

How teams engage Ryz

• Staff augmentation. Add senior Java, Android or data engineers to your store systems team ahead of a rollout or peak season. See hire Android developers.
• Dedicated development team. A Ryz team owns a scoped system, such as a POS upgrade, an RFID program or a new associate app, and ships it with your product owner and store operations team.
• AI pod. A pod with a tech lead, an ML engineer and backend engineers builds forecasting, shelf detection or loss prevention models in your cloud and runs them to production.

Cost is team size × duration × monthly rate. Typical rates are $7,000 to $15,000 per engineer per month: mid-level at $7,000 to $10,000, senior at $10,000 to $15,000, and leads from $15,000. Four senior engineers at $12,000 a month for six months comes to $288,000. You get a plan, a price and the names of the people before you start.

When Ryz isn't the right fit

If a packaged POS or retail platform already does what you need, configure it before building custom software. If you need on-site hardware installers in stores, a field services firm fits better. And if you want a self-serve freelance marketplace or engineers in European or Asian time zones, other providers suit you better.

Related

• Guide: fraud detection engineering teams
• Mobile app development
• Machine learning development
• Manufacturing software development

FAQ

How do your engineers handle payment and customer data in store systems?

They work in your environment, under your access controls, logging and change management, and design integrations so card data stays inside P2PE terminals and tokenized flows. Customer data stays in your accounts. Ryz does not claim PCI DSS or SOC 2 certification; our engineers have experience working within those standards and your auditors' requirements.

Can you build POS software that works offline?

Yes. Our teams design POS and store apps to keep selling when the network drops: local transaction queues, cached prices and promotions, and conflict rules for when the store syncs back with central systems.

How is this different from your ecommerce work?

This page covers stores and the systems that connect them: POS, store inventory, associate apps, loyalty and supply chain. Online storefronts on Shopify, Adobe Commerce and headless platforms are covered on our ecommerce page. Most retailers need both, joined by one inventory and customer record.

What does a retail software development team cost?

Typical rates are $7,000 to $15,000 per engineer per month, depending on seniority. Three senior engineers at $11,000 a month for five months is $165,000. Quotes are scoped per team.

Can you roll changes out to hundreds of stores safely?

Our teams plan store rollouts in waves: pilot stores first, device management for staged app updates, feature flags by store or region, and rollback plans agreed with store operations before anything ships.

Questions we didn't answer? Email info@ryzlabs.com.