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Solvios is the leading IT company in the business to give you growth, revenue, and a global platform.
We build custom retail and eCommerce software from Shopify and Magento storefronts and custom eCommerce platforms to POS systems, omnichannel retail infrastructure, inventory and order management, and AI-integrated personalisation and analytics for brands, retailers, and commerce businesses that need software built around how their customers actually shop, not around the default settings of a platform template. We have built an AI-powered Shopify store, a curated multi-vendor Magento marketplace, and a custom multi-hardware POS system. The retail technology spectrum runs wider than most development shops cover and we cover it end to end.
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Solvios is a retail and eCommerce software development company building custom eCommerce storefronts, Shopify and Magento implementations and customisations, POS and in-store systems, omnichannel retail platforms, inventory and order management systems, and AI-integrated personalisation and analytics for brands, direct-to-consumer retailers, multi-location retail businesses, and commerce technology companies. We work across the full retail technology stack from the customer-facing storefront through the operational systems that fulfil the order and the analytics layer that tells you what to stock, how to price it, and who to market it to next.
Bespoke eCommerce storefronts built around the specific product catalogue, purchasing behaviour, and brand experience requirements of the retailer rather than adapted from a platform template that was designed for a different merchant type and a different customer.
Shopify and Magento store builds, theme customisation, app and extension development, platform migration, and the performance and conversion optimisation work that turns a functional store into a high-converting one.
Custom point-of-sale systems covering sales transactions, inventory management, employee access, customer management, and multi-hardware integration for retail businesses that need a POS built around their specific operational model rather than constrained by what a commercial POS vendor offers.
The integration and data architecture that connects online, mobile, in-store, and third-party channel commerce into a unified view of inventory, orders, customers, and performance so the retailer and the customer experience the brand as one operation regardless of which channel the transaction happens through.
Custom inventory management systems, order management platforms, and fulfillment workflow tools for retailers managing stock across multiple locations, channels, and fulfillment models with the real-time stock visibility, demand forecasting, and replenishment logic that prevents both stockouts and excess inventory.
Retail software has a specific failure mode: the gap between the customer experience the brand wants to deliver and the operational reality the technology currently supports. An eCommerce platform that cannot show accurate stock levels. A POS that runs on one hardware but not the hardware the new location uses. An online store and a physical store that share no customer data. An analytics setup that generates reports but cannot tell the merchant which product to reorder before it sells out. We have worked across this entire landscape and here is what we actually see.
Most eCommerce platforms impose their design constraints, checkout flows, and product data models on the merchant and most merchants spend their first year of platform operation discovering what the platform cannot do rather than what they wanted to build. Custom product configurators that the platform templating system cannot support. Checkout flows optimized for conversion that conflict with the platform's default checkout behaviour. Subscription and bundle logic that requires third-party apps that each add latency, cost, and a single point of failure. The commerce platform should serve the brand. Most brands end up serving the platform.
The inventory accuracy problem in retail is one of the most persistently underestimated operational challenges. Online inventory, warehouse inventory, in-store inventory, and inventory in transit all need to be reconciled in real time for a retailer to make accurate promises to customers and most retailers are running these across multiple disconnected systems with manual reconciliation processes that work until they don't. Overselling on the eCommerce site. Stockouts on products that are physically present in a warehouse. Allocation decisions made on yesterday's stock count rather than today's reality.
The customer who bought in-store three times and never online is not in the eCommerce customer database. The customer who browsed the website repeatedly before buying in-store is not attributed to any digital marketing spend. The loyalty programme does not recognise the transaction if it happened on a different channel. Retail businesses that operate across multiple channels: physical stores, eCommerce, marketplace, mobile typically have a customer data picture that is fractured by channel rather than unified by customer. The result is marketing that repeats itself, loyalty that is channel-specific rather than brand-specific, and a customer lifetime value calculation that is systematically understated.
Retail businesses spending on search, social, and email to drive traffic to their eCommerce store consistently find that the conversion rate does not justify the acquisition cost. The problem is almost never the traffic quality; it is the site performance, the product page experience, the checkout friction, the returns policy visibility, or the trust signals that are either missing or poorly positioned. eCommerce conversion optimization is a distinct engineering and UX discipline, and most retail businesses are applying general web development practices to a problem that requires specific eCommerce expertise.
A retail operation that processes 100 orders a day manually can process 1,000 orders a day if the operational software is designed to automate the steps that do not require human judgment. Order routing, fulfillment instruction generation, shipping label creation, inventory reservation, customer notification, and returns processing can all be automated but only if the software architecture was designed for it. Retailers that scale into higher order volumes without operational automation invest in people instead of systems and find that the cost structure gets worse rather than better as volume grows.
Every retail and eCommerce engagement starts with the customer journey, the product catalogue architecture, the fulfilment model, and the channel mix not with a platform selection. The right technology choice follows from the commerce requirements, not the other way around.
The retail software market spans independent DTC brands at one end and multi-location retail chains at the other with very different technology requirements, commercial models, and operational complexity at each point. We have built for companies across this spectrum.
Direct-to-Consumer (DTC) Brands
DTC brands building or growing their own eCommerce channel where the product presentation, the checkout experience, the post-purchase communications, and the customer data infrastructure are direct drivers of the customer acquisition cost and lifetime value economics that determine whether the DTC model is commercially viable. We have built for DTC brands across product categories including specialty food and wellness products, where the brand story and the product quality signal are as important to conversion as the price.
Multi-Location Retail Businesses
Retailers operate physical stores alongside an eCommerce presence where the inventory, customer data, and operational systems need to work together across channels rather than running as parallel businesses under the same brand name. POS systems that share customer and inventory data with the eCommerce platform, loyalty programmes that work across every touchpoint, and the omnichannel infrastructure that makes buy-online-return-in-store work without operational friction.
eCommerce Operators Scaling Past Platform Limits
Online retailers who have grown to the point where the eCommerce platform they started on Shopify, WooCommerce, or a custom platform built at an earlier stage can no longer support the catalogue complexity, order volume, customisation requirements, or integration landscape their current operation demands. Platform migration, custom platform build, or targeted custom development to extend a platform that is otherwise working we make the recommendation based on the operational requirements rather than on what is most convenient for the development engagement.
Niche and Specialty Retailers
Specialty retailers in categories where the product catalogue structure, the purchasing experience, or the operational model differs from the generic retail template custom furniture and home furnishings, personalised products, subscription and consumable reorder models, B2B and trade accounts alongside consumer sales, or high-consideration purchases that require consultative rather than transactional eCommerce experiences.
Retail Technology and Commerce Platform Companies
ISVs and technology companies building retail software products POS systems, eCommerce platforms, retail analytics tools, inventory management systems, loyalty platforms where the end customers are retail businesses and the software must satisfy the integration standards, performance requirements, and operational reliability that retail operations demand.
Marketplace and Multi-Vendor Commerce Operators
Businesses operating curated multi-vendor commerce platforms where the retailer owns the customer experience and the brand positioning but relies on multiple suppliers or brands to provide the product catalogue. The technical requirements overlap with marketplace development but the commercial model is typically more controlled than an open marketplace; vendors are curated, the platform operator manages the brand experience, and the transaction economics are retail-style rather than marketplace-style.
We will map your channel mix, your integration requirements, and your customer experience goals and give you an honest architecture path before any code is written. Response within 24 hours.
These are the capabilities that retail and eCommerce software requires to convert traffic into sales, turn one-time buyers into loyal customers, manage inventory accurately across channels, and scale operational throughput without proportionally scaling the team that runs it.
Recommendation models trained on product attributes, browse behaviour, purchase history, and customer segment signals surfacing the right products to the right shopper at the right moment, across the homepage, product pages, category pages, cart, and post-purchase communications.
Unified inventory across eCommerce, POS, marketplace, and fulfillment locations with accurate available-to-promise at point of sale and checkout, channel allocation management, and the real-time stock picture that prevents overselling and enables BOPIS and ship-from-store fulfillment.
Cross-channel customer identity resolution, unified purchase history, loyalty points accrual and redemption across all channels, personalised communication based on channel behaviour, and the customer data infrastructure that makes every touchpoint aware of the complete customer relationship.
Guest and account checkout, one-page checkout design, address validation, saved payment methods, buy now pay later integration, multiple payment gateways, digital wallets, and the checkout performance optimization that reduces abandonment from both friction and load time.
Automated order routing to the optimal fulfillment location, fulfillment instruction generation, shipping label creation, carrier integration, customer notification at each fulfillment milestone, and the exception management workflow for orders that cannot be automatically routed.
On-site search with relevance ranking, faceted filtering by product attributes, autocomplete, zero-results handling, and the search analytics that tell the merchandising team which queries are returning poor results before the customer bounces to a competitor.
Sales transactions, inventory management, employee access control, customer lookup, loyalty balance checking, gift card processing, multi-tender payment, end-of-day reconciliation, and the back-office retail management tools that in-store operations depend on.
Revenue, conversion, average order value, customer acquisition cost, customer lifetime value, category performance, campaign attribution, and the operational analytics fulfillment cost per order, return rate by product, stockout frequency that give retail leadership the full picture rather than just the top-line metrics.
AI in retail and eCommerce is not about adding a recommendation widget that surfaces the same ten bestsellers to every visitor. It is about building systems where machine learning improves every stage of the customer journey from the first product discovery moment through the purchase decision, the fulfillment experience, and the retention communication that determines whether the customer comes back. We have built AI-integrated eCommerce products and we understand where AI creates genuine commercial value in retail versus where it creates impressive feature demonstrations that do not change conversion, retention, or operational cost.
Recommendation models built on the full behavioural and transactional data available to the retailer browse history, purchase history, product attribute affinity, price sensitivity signals, time-of-day and season patterns, and explicit customer preferences that surface products the customer is genuinely likely to buy rather than the popularity-ranked alternatives that most recommendation widgets default to. Personalisation extended across every surface: homepage, category pages, product pages, cart upsell, email, and push notifications with a consistent signal that learns from each interaction.
Highlights:
Recommendation models built on the full behavioural and transactional data available to the retailer browse history, purchase history, product attribute affinity, price sensitivity signals, time-of-day and season patterns, and explicit customer preferences that surface products the customer is genuinely likely to buy rather than the popularity-ranked alternatives that most recommendation widgets default to. Personalisation extended across every surface: homepage, category pages, product pages, cart upsell, email, and push notifications with a consistent signal that learns from each interaction.
Highlights:
Retail software development fails most often not because the engineering is wrong but because the customer journey was not mapped before the architecture was designed, the integration requirements between the eCommerce platform and the operational systems were underestimated, or the performance optimisation that eCommerce conversion requires was treated as a post-launch activity rather than a first-sprint requirement. Our retail and eCommerce development process addresses these problems before they affect conversion, operations, or the customer experience.
Here's exactly how it works.
We map the customer journey, the product catalogue structure, the channel mix, the fulfilment model, and the integration landscape and make the platform and architecture recommendations that follow from the commerce requirements rather than from platform preference. Output is a project scope with platform selection rationale, integration architecture, performance requirements, and the conversion and retention goals the platform is being built to achieve.
eCommerce architecture designed with page performance, SEO requirements, and the integration complexity of the retail technology stack in mind. UI/UX design built around the specific purchasing behaviour and product discovery patterns of the target customer not generic eCommerce templates adapted to the brand.
Two-week sprints with working eCommerce software delivered each cycle. Core purchase flow product discovery, product page, cart, checkout, payment, and order confirmation ships first. Personalisation, loyalty, AI features, and operational integrations are layered on the transactional foundation that everything else depends on.
Core Web Vitals testing and optimisation, checkout flow conversion testing, payment integration end-to-end testing, inventory accuracy validation, search relevance quality assessment, mobile performance testing across device range, and load testing at peak traffic volumes comparable to promotional periods.
Staged launch with DNS cutover, SEO redirect mapping implementation, analytics and conversion tracking validation, post-launch monitoring, and the rapid response capability for any conversion or performance issues that surface in the first 48 hours of live traffic.
Post-launch conversion rate optimization, AI feature training and improvement as order data accumulates, integration maintenance, new feature development, seasonal performance preparation, and the continuous improvement cycle that keeps the platform improving rather than stagnating after launch.
Retail and eCommerce projects range from a targeted Shopify customisation to a full omnichannel platform build. The right engagement model depends on the scope, the operational integration complexity, and how quickly the retail business needs to move.
You are building a full custom eCommerce platform or omnichannel retail infrastructure, scaling an existing platform into new channels or international markets, or augmenting an in-house team with retail technology engineering expertise without the cost and lead time of full-time hires.
Hand-picked engineers with retail technology experience, a QA specialist, and a technical lead working exclusively on your platform. Sprint planning and merchandising demos run on your calendar. eCommerce, POS, AI personalisation, and operational integrations are all handled in-house.
Monthly retainer. No surprise invoices, no scope-creep billing. Team composition flexes as your retail technology roadmap evolves.
3–10 engineers
6-month minimum
Scales with 30-day notice
Most retailers start with Fixed Cost for a defined platform build and move to Time and Material as the optimisation and integration work that follows launch reveals what the platform needs next. Let's figure out the right starting point together.
Retail technology is one of the most covered software categories. There are hundreds of agencies that will build a Shopify store. Very few cover the full retail technology spectrum from the customer-facing storefront through the POS, the inventory management, the omnichannel infrastructure, and the AI personalisation layer. Here is what makes the difference in practice.
Full Retail Technology Stack Coverage
We have built at every layer of the retail technology stack custom eCommerce storefronts, Shopify and Magento implementations, a custom POS system, a curated multi-vendor commerce platform, and AI-integrated personalisation. The Solvios retail case studies are not all eCommerce web builds labelled as retail, they represent genuinely different parts of the retail technology problem, and the experience from each informs how we approach the others.
AI-Integrated Retail Architecture from Day One
Product recommendations, visual search, demand forecasting, dynamic pricing, and customer churn prediction all require a data architecture and event tracking infrastructure designed to support them from the first order. We address the AI architecture in the commerce strategy phase so that the intelligence features can be deployed and improved as the customer and order data accumulates rather than requiring a data layer rebuild before the first recommendation model can be trained.
Conversion as an Engineering Discipline
Core Web Vitals, checkout friction, mobile performance, product page information architecture, search relevance, and site speed are all engineering problems that have measurable conversion impact. We treat conversion optimization as a first-sprint requirement rather than a post-launch activity because the cost of re-engineering a poorly performing checkout or a slow product page after launch is always higher than designing it correctly at the start.
Platform Selection Advice You Can Trust
We work across Shopify, Magento, and custom platforms and we make platform recommendations based on the commerce requirements rather than on which platform we happen to prefer to build on. Shopify is the right answer for many retail engagements. It is not the right answer for all of them. We will tell you which it is before we start building rather than discovering the platform limitations six months into a project.
Operational Integration Depth
The eCommerce platform is one system in a retail technology stack. Connecting it to the inventory management system, the POS, the ERP, the 3PL, the marketing automation platform, and the customer data platform and keeping those integrations reliable as each system evolves is the ongoing engineering work that determines whether the retail operation runs efficiently or runs on manual workarounds. We build and maintain integrations as part of the engagement rather than leaving integration maintenance as an afterthought.
US-Based Communication, Retail Calendar Awareness
Retail businesses operate on a trading calendar where the timing of a deployment matters as much as its quality. A go-live that slips into peak trading season is a higher-risk deployment than one that launches six weeks before it. Project management and client communication on US business hours and the awareness that retail deadlines are driven by the trading calendar, not by software development convenience.
Honest answers to the questions every retail technology leader, eCommerce manager, and DTC brand founder asks before choosing a retail software development company. If something is not covered here, our team will walk you through it on a discovery call no sales pitch, no fluff.
Cost depends on scope and platform. A custom Shopify theme build with app integrations typically starts at $15,000–$40,000. A mid-complexity Shopify or Magento implementation with custom app development and third-party integrations ranges from $40,000 to $120,000. A custom eCommerce platform built from scratch is typically $80,000–$250,000 depending on catalogue complexity, functionality scope, and integration requirements. A custom POS system covering sales, inventory, employee management, and multi-hardware integration starts at $60,000–$150,000. An omnichannel integration connecting online and in-store systems typically starts at $40,000–$100,000. Solvios provides fixed-price proposals after a commerce strategy and architecture discovery session.
Shopify is the right choice for most DTC brands and single-channel eCommerce operations it is fast to build on, well-maintained, and the App Store covers most standard eCommerce requirements. Shopify Plus extends it meaningfully for higher-volume operations. Magento 2 is appropriate for retailers with complex catalogue structures, B2B requirements, or multi-store needs that exceed Shopify's native capabilities. A custom platform makes sense when the business model or product catalogue structure falls outside what either commercial platform can accommodate without extensive customisation subscription and bundle commerce, complex configurator products, or B2B wholesale with customer-specific pricing and contract terms are common cases. We make the recommendation based on the commerce requirements, not on platform preference.
A standard Shopify theme build with core integrations takes 6-10 weeks. A mid-complexity Magento or custom eCommerce build takes 3-6 months. A full custom eCommerce platform with AI personalisation and omnichannel integration takes 6-12 months. A custom POS system takes 4-7 months. Platform migration from one eCommerce platform to another takes 8-16 weeks depending on catalogue size and data complexity. The biggest variable is integration scope; each third-party integration adds time and the sequence matters because some integrations depend on others being completed first.
AI-integrated retail and eCommerce development means building platforms where machine learning is part of the core commercial value improving discovery, increasing conversion, reducing inventory waste, and retaining customers more efficiently than rule-based approaches allow.
In retail this includes product recommendation engines that personalise every customer's experience across the storefront and all communications, visual search that enables image-based product discovery, demand forecasting models that improve inventory replenishment decisions, dynamic pricing that responds to competitive and demand signals, AI commerce assistance that handles product knowledge queries without human support, and customer churn prediction that identifies at-risk customers for proactive retention. These capabilities require an event tracking infrastructure and data architecture built from the first user session which is why we address the AI architecture during the commerce strategy phase rather than treating it as a later add-on.
Yes. We have delivered a custom POS system covering sales transaction processing, inventory management, employee and customer administration, multiple payment methods, and multi-hardware peripheral integration. Custom POS development makes sense when the operational model hardware variety, custom pricing and discount logic, specific inventory workflows, or the integration requirements with an eCommerce platform or ERP falls outside what commercial POS platforms can accommodate without significant compromise. The discovery process for a custom POS engagement maps the operational requirements, hardware environment, and integration landscape before any development begins.
eCommerce and POS integration typically covers real-time inventory synchronisation between channels, unified customer data across online and in-store, order management that handles both channel types in a single workflow, and loyalty points accrual and redemption across both surfaces. The integration architecture depends on the platforms involved: Shopify has native POS integration capability; Magento requires custom integration work; custom eCommerce platforms require custom API integration in both directions. We design the integration architecture before building the individual systems where possible, because systems designed to share data are significantly easier to integrate than systems built independently and connected after the fact.
Core Web Vitals Largest Contentful Paint, Cumulative Layout Shift, and Interaction to Next Paint are direct factors in both Google search ranking and eCommerce conversion rate. We treat performance as a first-sprint engineering requirement rather than a post-launch optimization because the architecture decisions that affect performance image delivery strategy, JavaScript loading sequence, server-side rendering versus client-side rendering, third-party script management are significantly more expensive to change after the site is built than before. Page speed targets and Core Web Vitals thresholds are defined during the discovery phase and tested throughout development rather than at launch.
Three models: Dedicated Retail Development Team for multi-quarter retail platform builds and ongoing product evolution; Time and Material for iterative development where the merchandising and integration requirements are evolving or the post-launch optimisation work is ongoing; and Fixed Cost for well-scoped retail software projects with a clear trading calendar deadline a platform launch before peak season, a POS deployment for a new store opening, or a platform migration where the go-live date is fixed. We recommend the right model based on scope clarity and the commercial timeline the retail business is operating against.
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Solvios is a leading software development company crafting innovative solutions for businesses. We Specialize in custom software, web & mobile app development, and digital marketing. Partner with us to transform your vision into reality and achieve digital success.
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