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AI for Retail & eCommerce

AI that actually moves retail metrics that matter.

AI solutions for retail and e-commerce businesses — focused on the metrics that actually move revenue, not novelty features.

Talk to an AI Expert See Our Work
AI for Retail & eCommerce digitallyscaled
40+
Retail AI Projects
+32%
Avg. Conversion Lift
5–10 wks
Avg. Build Time
24/7
Support
Overview

Why retail AI needs to move metrics that genuinely matter to the business

Retail and e-commerce businesses face genuine pressure to adopt AI, but many implementations focus on impressive-sounding capability that doesn't actually move business outcomes that matter — conversion rate, average order value, inventory turnover, customer lifetime value. We focus AI investment specifically on use cases with a clear, demonstrable path to these genuine business metrics, rather than technology adoption for its own sake.

Personalized product recommendations, demand forecasting for inventory planning, and dynamic pricing represent some of the highest-value application areas we typically work on, though the right starting point genuinely depends on your specific business and current pain points. We're honest about data requirements upfront — some applications need substantial historical data to perform well, while others can deliver value with more limited data using reasonable fallback approaches. Inventory management applications extend well beyond customer-facing marketing, helping retailers avoid both costly overstock and disappointing stockouts through better demand prediction. Throughout any engagement, we build in clear measurement so you know definitively whether the AI investment is genuinely delivering the results it promised, not just assuming based on theoretical model performance.

What's Included

Everything this solution actually covers

Personalized Recommendations

Product recommendations built around real individual shopping behavior.

Demand Forecasting

Inventory forecasting grounded in real historical and seasonal patterns.

Dynamic Pricing

Pricing informed by real demand signals, applied thoughtfully.

Fraud Detection

AI-assisted detection of suspicious transactions without over-flagging good ones.

Visual Search

Search that lets customers find products by image, not just keywords.

Ongoing Optimization

We keep tuning models as catalog and customer behavior evolve.

Our Process

How we get there

01

Discover

We review your data, catalog, and where AI could realistically add value.

02

Design

We design the specific AI use case around your business goals.

03

Build & Test

We build and validate impact through structured testing.

04

Deploy & Optimize

We deploy and continue optimizing based on real results.

Tech We Use

Built on tools that scale with you

PythonPyTorchBigQueryRedis
Recent Work

A few projects we’ve shipped recently

Solantis Commerce
Retail

Solantis Commerce

A recommendation engine that noticeably lifted average order value.

View Case Study
Meridian Technologies
SaaS

Meridian Technologies

A demand forecasting model that reduced both stockouts and overstock.

View Case Study
Argenta Medical Group
Healthcare

Argenta Medical Group

A fraud detection system that cut chargebacks without over-flagging legitimate orders.

View Case Study
Brookhaven Capital
Finance

Brookhaven Capital

A visual search feature that improved product discovery on mobile.

View Case Study
Testimonial

What clients say

“I was skeptical this would actually work for us specifically. But +36% conversion rate within a few months, and the process to get there was more thoughtful than I expected.”

GT
Godfrey Terzian

COO, Solantis Commerce

FAQ

Common questions

What AI use cases work best for retail businesses?

Personalized recommendations, demand forecasting, and fraud detection tend to have the clearest ROI — we'll assess what fits your business specifically.

Do you need a lot of historical data to get started?

It helps, but we can also start with a lighter approach and improve as more data accumulates.

Can AI help with inventory management, not just marketing?

Yes, demand forecasting for inventory is one of the most common and impactful retail AI use cases.

How do you measure if the AI is actually working?

Through structured testing against clear business metrics like conversion rate, AOV, or forecast accuracy.

How long does a typical retail AI project take?

Most projects take 5–10 weeks depending on the specific use case and data readiness.

Can AI help reduce cart abandonment on our e-commerce site?

Yes, understanding and addressing patterns behind cart abandonment is a common and valuable AI-supported use case in e-commerce.

Do you work with businesses selling through multiple channels, not just one website?

Yes, we build systems accounting for multi-channel selling, since many retailers genuinely operate across web, marketplace, and physical store channels simultaneously.

Can this help identify which products are likely to become bestsellers?

Yes, trend and demand prediction to identify emerging bestsellers is a valuable application that helps inform inventory and marketing decisions.

Does this work for both B2C and B2B e-commerce businesses?

Yes, we adapt the specific approach to B2B or B2C dynamics, since customer behavior and purchase patterns genuinely differ between these models.

Can AI help with customer segmentation for more targeted marketing?

Yes, AI-driven customer segmentation based on genuine behavioral patterns is a common and valuable complementary application to broader retail AI work.

What's a reasonable first AI project for a retailer new to this technology?

We typically recommend starting with a focused, high-impact use case like recommendation or forecasting, building confidence before expanding into more ambitious applications.

Can AI help optimize product pricing dynamically?

Yes, dynamic pricing based on demand and competitive signals is a valuable application area for many retail and e-commerce businesses.

Do you help set up the analytics infrastructure needed to support this?

Yes, ensuring adequate analytics infrastructure is often a necessary early step, and we help address any gaps before deeper AI work begins.

Can this integrate with our existing e-commerce platform like Shopify?

Yes, we build integrations with common e-commerce platforms, keeping AI capability connected to the systems you already operate.

Can this help with personalized email marketing campaigns?

Yes, AI-driven personalization can extend to email marketing, tailoring content and offers based on genuine individual customer behavior.

Do you provide a clear ROI estimate before we commit to a project?

Yes, we provide a realistic ROI estimate based on your specific situation during initial scoping, before you commit to the full engagement.

Ready to explore AI for Retail & eCommerce?

Let's talk about your project — no pressure, just a straightforward conversation about what you need.

Talk to an AI Expert

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