An OMS with real time commerce orchestration + AI Native automation + proven operational impact powered by RANDEM-ED
RANDEM-ED works inside our Order Management System to support the decisions your teams make every day from where to fulfill an order to how to resolve exceptions faster.
No new tools. No workflow changes. Just smarter execution across operations.
AI-assisted order routing reduces manual handling and decision delays.
AI-driven routing reduces manual handling.
Orders are assigned to the best location in real time.
AI-assisted assigning orders based on real-time inventory availability.
Orders are assigned to the best location in real time.
Fewer touches. Fewer exceptions. Lower operational overhead at scale.
Speed and precision across fulfillment translate directly into revenue lift.
Fewer touches, fewer exceptions, lower overhead.
RANDEM-ED is the AI embedded directly inside the RANDEMRETAIL Order Management System designed to support retail operations, not replace them.
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.
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 our everyday working processes and decisions. Our core outcomes being defined for AI to work with us not for us, then to develop AI into our products with a purpose to achieve real business outcomes. The uncertainty didn't disappear. It turned into momentum and a new way of working.
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 data itself, learning how the business runs, adapting with every decision, and offering support without taking control. RANDEM - Ed was created from that curiosity, shaped by real retail challenges, and designed to think alongside people, not replace them.
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.
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.
We didn't build the Blueprint for the technology. We built it for the people using it. Because when AI is woven into the way a team works — carefully, responsibly, with full visibility — it stops feeling like a system and starts feeling like support. That's the difference between AI that gets adopted and AI that gets abandoned.
From Ed’s intelligence came something new. Edette is designed to connect — not people, but intelligence.
Edette enables AI systems to communicate with context, translate intent, and collaborate across platforms. Edette doesn’t act alone. Edette amplifies. Edette 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!
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 Study2.0 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.
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.
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.
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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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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Learn why a structured AI methodology matters. RANDEM-ED’s native AI-enabled OMS drives operational efficiency, inventory intelligence, and scalable retail growth.
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See how AI works inside the RandemRetail OMS with Ed supporting real order,
fulfillment, and inventory workflows in real time.
A guided walkthrough of real OMS scenarios. No setup required.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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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