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AI-Native Order Management System
Built for today and the future of retail operations
AI-Native Order
Management System

A modular OMS where every function and interaction is powered by AI with RANDEM-ED

RANDEMRETAIL Ed AI Agent is here to solve complex operational challenges and optimize your inventory and supply chain management driving customer loyalty and cost optimization RANDEMRETAIL was built AI-first to solve the limits of legacy retail systems.

2x

Faster Order Processing

AI-assisted order routing reduces manual handling and decision delays.

AI-driven routing reduces manual handling.

3x

Smarter Order Assignment

Orders are assigned to the best location in real time.

AI-assisted assigning orders based on real-time inventory availability.

43%

Reduction in operational expense Operational cost savings

Orders are assigned to the best location in real time.

Fewer touches. Fewer exceptions. Lower operational overhead at scale.

150%

Increase in revenue overall sales Increase in overall revenue

Speed and precision across fulfillment translate directly into revenue lift.

Fewer touches, fewer exceptions, lower overhead.

Ed is not just a tool. Not a Layer. Built Into the OMS.
AI That Adapts to Your Operations

RANDEM-ED is the AI embedded directly inside the RANDEMRETAIL Order Management System designed to support real retail operations, not replace them.

How RANDEMRETAIL Started with AI

AI entered retail surrounded by uncertainty complex, hard to trust, and often misunderstood. Instead of resisting it, We asked a simple question: what if AI could work alongside people, not replace them?

That belief became the starting point for building intelligence directly into retail operations.

AI arrived in retail surrounded by uncertainty. Complex. Hard to trust. Often feared as something that would replace people. At RANDEMRETAIL we felt that hesitation too. Instead of resisting AI, we asked a different question:

What if AI could think with us, not for us?

That question changed how we approached technology. We believed AI shouldn’t live in a lab. It should live where the work happens shaped by real operations and real teams. And that belief set everything else in motion.

How we turned AI uncertainty into opportunity

At RANDEMRETAIL, we didn’t add AI as a feature. We treated it as a new way work gets done.

We applied AI to real decisions; forecasting demand, improving fulfillment, and understanding operations as a system. Teams stopped fighting data and started acting on it. The uncertainty didn’t disappear. It became momentum.

Every era of progress starts with doubt. The industrial revolution. The digital age. And now AI.

At RANDEMRETAIL, we didn’t treat AI as a feature to add. We treated it as a shift in how work gets done.

We began applying AI to real decisions. Forecasting demand, improving fulfillment, understanding operational signals not in isolation, but as part of how the business runs. Over time, teams stopped fighting data and started acting on it. The uncertainty didn’t disappear. It turned into momentum.

Meet Ed: Your Thinking Partner

ED was designed to operate inside the OMS, learning how orders move, inventory behaves, and rules interact.

Not as a replacement for people but as a partner that helps teams decide faster and with confidence.

Ed began as a question, not a product. As retail operations grew more complex, teams found themselves surrounded by data but still making decisions the hard way.

We wondered what would happen if intelligence could live inside the work itself learning how the business runs, adapting with every decision, and offering support without taking control. Ed was created from that curiosity, shaped by real retail challenges, and designed to think alongside people, not replace them.

The RANDEMRETAIL AI Blueprint

Reliable AI doesn’t happen by accident. We built a Blueprint to prepare data, train ED, and embed governance. So intelligence remains consistent, safe, and trusted.

This is how AI earns its place in daily operations.

Every era of progress starts with doubt. The industrial revolution. The digital age. And now AI.

At RANDEMRETAIL, we didn’t treat AI as a feature to add. We treated it as a shift in how work gets done.

We began applying AI to real decisions. Forecasting demand, improving fulfillment, understanding operational signals not in isolation, but as part of how the business runs. Over time, teams stopped fighting data and started acting on it. The uncertainty didn’t disappear. It turned into momentum.

Ed’s First week at RANDEMRETAIL

ED joined the team by learning the basics orders, stores, and fulfillment.

With each interaction, ED adapted to how teams communicate and decide. That’s when ED became less of a system and more of a teammate.

When Ed joined the team, he started like everyone else. Learning order statuses, Understanding store assignments, Figuring out how fulfillment really works.

He asked questions. He made adjustments. And with every interaction, he got better. Not just faster, more human. Ed learned how teams communicate, how context matters, and how decisions are actually made.

That’s when Ed stopped feeling like a system and started feeling like a teammate.

The Next Evolution of Retail AI

From Ed’s intelligence came something new. Edette is designed to connect — not people, but intelligence. She enables AI systems to communicate with context, translate intent, and collaborate across platforms. Edette doesn’t act alone. She amplifies.

She extends Ed’s reach, allowing intelligence to move across ecosystems opening the door to conversational commerce and AI-to-AI collaboration.

This is where intelligence stops working in silos. Stay tuned!

Every era of progress starts with doubt. The industrial revolution. The digital age. And now AI.

At RANDEMRETAIL, we didn’t treat AI as a feature to add. We treated it as a shift in how work gets done.

We began applying AI to real decisions. Forecasting demand, improving fulfillment, understanding operational signals not in isolation, but as part of how the business runs. Over time, teams stopped fighting data and started acting on it. The uncertainty didn’t disappear. It turned into momentum.

Ed in Action: AI-Driven OMS Delivering Better Results

Ed isn’t just a concept, he’s delivering measurable outcomes inside the RANDEMRETAILl Order Management System.

Big R, a long-time RandemRetail OMS user, became one of the first to adopt RANDEM-ED and has already seen real improvements in daily operations and team efficiency.

Read the Big R Case Study

Key Results from
our client Big R

2.0 seconds

Average processing time per request

100%

Task completion rate across all sessions.

100+ AI sessions

Operational commands completed without manual intervention.

We have enabled RANDEM-ED recently, and we’re very happy with the results and efficiency our team is seeing from using it. What used to take us hours to complete is now taking us minutes.

— Christine Pittman, Group Head of E-commerce, Big R

Read more on Big R Case Study

Built for all retailers

RANDEMRETAIL’s AI-driven OMS is trusted by retailers across a wide range of industries — each with different fulfillment
models, inventory challenges, and customer expectations.

Our platform is designed to adapt to the realities of each category, not force a one-size-fits-all workflow.

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No AI jargon. No IT burden. Just a smarter OMS.

You don’t need AI expertise or internal engineering teams to run an AI-driven Order Management Sytem.

RANDEMRETAIL is delivered as a fully managed OMS with built-in intelligence.

What We Handle

  • System configuration and setup
  • Integrations, updates, and performance
  • Security, reliability, and ongoing support

What Your Team Does

  • Use the OMS as they always have
  • Work with Ed inside existing workflows
  • Make faster, more confident operational decisions

What Doesn’t Change

  • Your existing operational processes
  • How teams manage orders day to day
  • Who stays in control of decisions

We’re Partners with Leaders Across the Retail Ecosystem

By connecting with leading commerce, fulfillment, and delivery partners, RandemRetail’s AI-Driven OMS enables retailers to integrate faster, operate smarter, and scale with confidence across channels.

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Resources & Insights

By connecting with leading commerce, fulfillment, and delivery partners, RandemRetail’s AI-Driven OMS enables
retailers to integrate faster, operate smarter, and scale with confidence across channels.

View All Case Studies

Experience AI-Driven Order Management

See how AI works inside the RandemRetail OMS with Ed supporting real order,
fulfillment, and inventory workflows in real time.

Book a live demo

A guided walkthrough of real OMS scenarios. No setup required.

FAQs about RANDEMRETAIL OMS

Learn how RANDEMRETAIL’s Order Management System helps retailers unify orders, inventory, and fulfillment across multiple
channels, ensuring faster deliveries and a seamless omnichannel experience.

What is an AI-Driven Order Management System (OMS)?

RANDEMRETAIL AI-Driven Order Management System is a platform that uses artificial intelligence to orchestrate orders, inventory, and fulfillment decisions across channels in real time.
It helps retailers process orders faster, reduce errors, and manage complex omnichannel operations more efficiently.

How does RANDEM-ED AI improve order management in retail?

RANDEM-ED AI improves order management by analyzing real-time inventory, location data, fulfillment capacity, and operational constraints to recommend the best fulfillment path for each order.
This reduces manual decision-making, minimizes delays, and improves order accuracy.

How is RANDEM-ED AI embedded inside the RANDEMRETAIL OMS?

RANDEM-ED AI is built directly into the core OMS workflows, not added as a separate layer.
It works inside order routing, fulfillment orchestration, and inventory intelligence processes to support daily retail operations while keeping teams in control.

Does an AI-Driven OMS replace human decision-making?

No. An AI-Driven OMS supports human decision-making rather than replacing it.
AI provides context-aware recommendations and insights, but retail teams remain responsible for final operational decisions.

What omnichannel capabilities does an AI-Driven OMS support?

An AI-Driven OMS supports buy online pick up in store (BOPIS), ship from store, same-day delivery, split shipments, dropshipping, and returns management.
AI helps determine the most efficient fulfillment option based on real-time conditions.

Can an AI-Driven OMS handle complex fulfillment scenarios?

Yes. AI-Driven OMS platforms are designed to manage complex scenarios such as backorders, partial fulfillment, multi-location sourcing, cross-channel inventory allocation, and reverse logistics at scale.

How does an AI-Driven OMS reduce operational costs?

By automating order routing and reducing manual handling, an AI-Driven OMS lowers operational overhead, reduces fulfillment errors, and minimizes exception management.
Fewer touches and smarter fulfillment decisions lead to measurable cost savings.

Is an AI-Driven OMS suitable for large or global retailers?

Yes. AI-Driven OMS platforms are built to scale across multiple regions, warehouses, stores, and channels.
They support global inventory visibility, region-specific fulfillment rules, and centralized orchestration for international operations.

Do retailers need AI expertise to use an AI-Driven OMS?

No. Retailers do not need AI expertise or internal engineering teams.
The AI operates within the OMS, allowing teams to work as they normally do while benefiting from intelligent automation behind the scenes.

How does AI help with inventory management?

AI analyzes inventory signals across stores and warehouses to improve availability, reduce stockouts, and prevent over-allocation.
This helps retailers balance demand and supply more effectively in real time.

Is AI in the OMS secure and reliable?

Yes. AI-Driven OMS platforms are designed with enterprise-grade security, reliability, and performance standards.
AI operates within controlled workflows and adheres to existing operational rules and permissions.

What results can retailers expect from an AI-Driven OMS?

Retailers typically see faster order processing, improved fulfillment accuracy, reduced operational expenses, better inventory utilization, and higher customer satisfaction driven by faster and more reliable delivery.

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