AI agents in your Netcore Unbxd console: one drafts your merchandising rules, one answers your data questions, one explains every ranking. Nothing goes live without your approval, so your team leads the strategy instead of running the execution.
Describe the campaign in plain English. The Copilot translates intent into the right boost, sort, pin, slot, filter, or freshness rule, sets the timeline, flags conflicts with your active campaigns, and shows the expected impact. You confirm to publish.
Ask natural-language questions across Search, Browse, Autosuggest, and Campaign reports and get instant, plain-language answers without dashboards, filter-building, or analyst tickets. Compare and drill deeper in the same conversation.
Ask why a product ranks where it does or why it's missing from results entirely and get a plain-English explanation plus the fix. Catalog mismatch, retrieval filter, eligibility condition: spelled out in seconds. No engineering ticket, no backend logs.
Operate confidently through high demand, growing complexity, and constant change. Stay responsive as systems scale, workflows expand, and execution pressure intensifies.
Run product, campaign, and pricing operations at scale without delay, regardless of catalog size or market scope. Built for millions of SKUs across multi-brand, multi-market, multi-currency environments.
Empower merchandising, growth, and data teams to act in parallel, with no wait time, blockers, or cross-functional dependencies.
Keep campaigns running continuously across assortments and markets, with a configurable approval workflow that governs launches without slowing them down.
Navigate intricate merchandising decisions with clarity and control. Adapt to evolving strategies, regional nuances, and edge cases without sacrificing accuracy or agility.
Surface answers to margin, AOV, and performance questions instantly, in plain language without deep diving dashboards.
Understand search behavior, uncover gaps in discovery, and explain and refine ranking logic against real-time shopper intent.
Balance conditional logic, personalization, and rule hierarchies across campaigns, segments, and geographies, no custom logic required.
Turn intent into live outcomes with no manual configuration or rule scripting and your team approving each step. Maximum speed, minimum lift, full control.
Describe the outcome; the agent builds the full rule, flags conflicts, and surfaces expected impact, drafted from a single instruction.
Move from prompt to draft to publish in one flow. You review the strategy of the agent, the signals behind it, and the exact products affected, then approve and publish.
Deploy, measure, and iterate in one console without relying on dev tickets, or multi-team reviews. Insights detects, Debugger diagnoses, Copilot executes, you approve.
Early-adopter results. Varies by catalog complexity, integration, and baseline maturity.
67%
Faster from brief to live
3x
More campaigns per quarter
28%
Inventory sell-through lift
< 48hours
Connect to your stack
Netcore Unbxd Agentic Ecommerce is an AI agent layer that sits on top of your existing ecommerce stack and automates high-volume merchandising, analytics, and search-relevancy work through specialized agents. Instead of manually creating rules, reports, and ranking tweaks, teams describe what they want in natural language and Agentic Ecommerce turns those prompts into live campaigns, experiments, and optimizations while respecting business guardrails.
The Merchandising Copilot is an AI merchandising assistant that converts plain-English instructions into production-ready campaigns, rules, and banners. You can ask it to boost a new collection, create a time-bound promotion, or set up an A/B test, and it will generate the right conditions, segments, and visual treatments in line with your existing merchandising setup. This lets business users launch and iterate on campaigns at real-time speed without waiting on developer or ops queues.
The Insights Agent is a conversational analytics layer that turns raw ecommerce data into direct answers, insights, and recommendations. Teams can ask questions such as which promotion drove the most margin or where AOV is dropping, and the agent analyzes performance data, segments, and trends to respond in clear language. It then suggests next actions, like adjusting a rule, refining a segment, or testing a different promotion, so decisions move straight from insight to execution.
The Debugger Agent is a real-time optimization layer that helps you continuously tune search and discovery based on live behavior, seasonality, and inventory signals. It flags issues such as zero-result searches or underperforming rules. Over time, this creates a self-optimizing product discovery system where shoppers see more relevant items and fewer dead ends without manual tuning.
Agentic Ecommerce is designed to plug into your existing stack rather than replace it. It connects to your product catalog, discovery layers, and analytics so it can orchestrate rules, campaigns, and optimizations on top of what you already run. This means you keep your current platform, integrations, and workflows, while offloading repetitive execution work to AI agents that act as an acceleration layer instead of a rip-and-replace project.
Agentic Ecommerce goes beyond simple rule schedulers or generic chat copilots by using specialized, ecommerce-trained agents that can both decide and do. Each agent understands ecommerce concepts like margin, inventory, segments, and ranking signals, then writes and executes the underlying logic for you. Instead of giving you a suggestion and leaving the work to your team, Agentic Ecommerce turns intent into live rules, tests, and campaigns while still keeping approvals and guardrails in your control.
Retailers using Netcore Unbxd’s AI suite typically see higher search conversions, better revenue per session, and faster campaign velocity as more ideas make it into production. Agentic Ecommerce is built to compound those gains by reducing execution delays, improving relevancy in real time, and ensuring promotions are always aligned with shopper intent and business goals. The outcome is more impact from the same team, less operational drag, and a more responsive discovery experience for shoppers.