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About Contact Us
AI-first engineering

AI App Development Company for Retail.

AI app development for retail ecommerce, shopping assistance, product discovery, and store operations. Build AI-powered retail web and mobile apps.

Get started

See Logiciel in action.

Tell us what you're building and we'll take it from there.

15+
Years building production software
120+
Engineers across delivery pods
75+
Clients served in North America
3K+
Successful product releases
Why Logiciel

Why Retail AI Apps Need More Than Product Suggestions.

Why Logiciel · 01

Shoppers describe needs in their own words while product catalogs organize information through attributes and categories.

Why Logiciel · 02

Product availability, prices, promotions, and delivery options can change faster than a model’s general knowledge.

Why Logiciel · 03

Customer context is spread across ecommerce platforms, loyalty programs, search behavior, and store systems.

Why Logiciel · 04

An appealing recommendation still disappoints if the product is unavailable or does not meet the shopper’s constraints.

Why Logiciel · 05

Retail teams need consistent experiences across mobile apps, websites, service channels, and in-store workflows.

Why Logiciel · 06

AI features can add friction when responses are slow, irrelevant, or disconnected from checkout and fulfillment.

Why Logiciel · 07

Production retail AI requires current data, business-aware ranking, clear handoffs, and measurement beyond demo quality.

What you get

What You Get From Logiciel AI App Development for Retail.

We combine retail product engineering, data integration, and applied AI to connect useful discovery with actual purchase and operating workflows.

01

More relevant product discovery

using catalog attributes, shopper intent, context, and available behavioral signals

02

Commerce-aware AI responses

respecting availability, price, eligibility, fulfillment options, and promotional business rules

03

Connected shopping journeys

embedding assistance in search, product pages, carts, support, and mobile experiences

04

Customer context with boundaries

using approved preferences and account information with appropriate consent and permissions

05

Support for retail teams

making product, order, and policy information easier for staff to retrieve and act on

06

Measurable shopping outcomes

evaluating discovery quality, engagement, conversion behavior, task completion, and latency

07

A reusable AI commerce layer

supporting new channels and experiences without duplicating catalog and workflow logic

Highlights

AI Applications Across Retail Experiences.

01

Conversational Shopping Assistants

What it meansHelp shoppers express needs, compare options, and discover relevant products using current catalog information.
02

Personalized Product Discovery

What it meansAdapt product suggestions and ranking to shopper behavior, preferences, context, and business constraints.
03

AI-Powered Mobile Shopping Apps

What it meansAdd contextual search, guided discovery, and account assistance to existing mobile commerce journeys.
04

Product Information Assistants

What it meansAnswer product questions using approved specifications, compatibility details, policies, and availability data.
05

Order and Service Applications

What it meansHelp customers check order information, understand policies, and route issues to supported service workflows.
06

Store Associate Copilots

What it meansGive associates faster access to product knowledge, inventory context, and approved service guidance.
07

Merchandising and Catalog Tools

What it meansSupport attribute enrichment, content review, category analysis, and repetitive catalog operations.
What we build

AI App Development Models Built Around Retail Teams.

01

Dedicated Retail AI Product Squad

A cross-functional team develops shopping UX, commerce integrations, AI features, evaluation, and rollout.

02

Retail AI Consulting and Team Extension

Product, data, and AI engineers extend your ecommerce or mobile team across architecture and implementation.

03

Outcome-Based Retail AI Engagement

A scoped initiative focuses on one journey, such as conversational search or product information assistance.

Under the hood

AI App Development Services We Deliver for Retail.

01

Retail AI Experience Discovery

We identify shopper friction, product data gaps, channel requirements, and the journey the AI feature should improve.

Included
02

AI Ecommerce and Mobile Development

We build intelligent interfaces within storefronts and mobile apps while preserving existing navigation and checkout flows.

Included
03

Catalog and Inventory Data Integration

We connect approved product attributes, availability, pricing, order context, and commerce APIs.

Included
04

Search, Retrieval, and Recommendation Engineering

We design context-aware discovery using suitable retrieval, ranking, recommendation, and model techniques.

Included
05

Commerce Rules and Personalization Controls

We apply eligibility, exclusions, inventory, privacy preferences, and other business constraints to AI outputs.

Included
06

Retail AI Evaluation and Testing

We test relevance, unavailable-item handling, product accuracy, user journeys, permissions, and performance.

Included
07

Production Monitoring and Optimization

We review engagement, discovery quality, latency, model costs, and business outcomes to refine the experience.

Included
Insights

Retail AI App Development Insights & Frameworks.

01

Retail AI Journey Prioritization Model

A method for selecting use cases by shopper friction, catalog readiness, transaction impact, and measurement potential.

Insights
02

Personalization and Business Rules Framework

A way to balance shopper relevance with availability, pricing, eligibility, exclusions, and privacy preferences.

Insights
03

Retail AI Experience Quality Model

An evaluation approach covering product relevance, factual accuracy, latency, engagement, and task completion.

Insights
How we work

Our AI App Development Framework for Retail.

01

Shopper Journey and Data Discovery

We map target journeys, catalog quality, available signals, commerce systems, and the desired customer outcome.

02

AI Experience and Commerce Architecture

We define interfaces, retrieval or ranking methods, data freshness, business rules, and success criteria.

03

Application Development and Integration

We build the AI experience and connect it to approved catalog, account, inventory, and commerce services.

04

Product and Journey Validation

We test relevant and irrelevant queries, availability changes, policy constraints, mobile flows, and performance.

05

Rollout, Experiment, and Improve

We measure discovery behavior, task success, latency, and user feedback to refine the application.

Selected work

Tailored engineering for your industry.

Zeme · Real EstateCut development costs 50% and launched 3× faster with dedicated dev teams.
Real Estate

Cut development costs 50% and launched 3× faster with dedicated dev teams.

Leap · ConstructionScaled to 7-figure ARR with AI-augmented software teams.
Construction

Scaled to 7-figure ARR with AI-augmented software teams.

KW · Real Estate56M+ workflows automated, saving agents 30% time with AI-powered tasks.
Real Estate

56M+ workflows automated, saving agents 30% time with AI-powered tasks.

Resources

Insights for tech leaders.

Whitepaper · PDF

The Model Evaluation Report

Read more
Whitepaper · PDF

The Economics of Model Evaluation

Read more
Whitepaper · PDF

Benchmarking Model Evaluation

Read more
In their words

What our clients say.

Teams that needed to ship fast, and did. Here's what partnering with Logiciel felt like from the inside.

Patrick Fingles

I would highly recommend them to anyone looking to scale quickly or needing support in engineering, product, or QA.

Patrick Fingles
Patrick Fingles
CEO, Leap
Elior Alayev

We don't just call them Logiciel; they're part of the Zeme team. Within the first week they were contributing meaningfully to our codebase.

Elior Alayev
Elior Alayev
Founder & CEO, Zeme
David Buzzelli

The Logiciel team worked tirelessly and built everything we needed, with security and best practices across our entire platform. It allowed us to become #1 in our industry, and we couldn't have done it without them.

David Buzzelli
David Buzzelli
Co-Founder, JobProgress
Questions

Frequently asked questions.

What does an AI app development company do for retail?

It builds AI-enabled shopping and retail operations experiences, including product discovery, contextual assistance, mobile features, and integrations with catalog and commerce systems.

Can AI improve product discovery in an existing ecommerce app?

Yes. AI can interpret natural-language intent and support ranking or retrieval, provided results are grounded in current catalog information and relevant business constraints.

Can AI-powered mobile apps use our inventory and pricing data?

They can when suitable integrations are available. The application should retrieve current values from approved systems rather than relying on model memory for stock or prices.

How do you handle customer personalization?

We use relevant, approved customer and behavioral signals while respecting permissions, consent preferences, and the retailer’s business rules.

Can AI assist store associates as well as online shoppers?

Yes. Staff-facing applications can help retrieve product details, approved policies, and inventory context within established store workflows.

How do you measure retail AI application performance?

Measures may include product relevance, search refinement, task completion, engagement, conversion behavior, latency, and customer-service outcomes.

How does a retail AI app development project start?

We start with the shopper or associate journey, available product and customer data, commerce integrations, and a specific outcome to improve.

Let's build

Make Your Retail App Easier to Shop and Use.

Share the shopping or store workflow you want to improve. We will help connect AI to the product data, commerce rules, and user experience it needs.