How the Debugger Agent puts clarity back in merchandisers’ hands

Key highlights

• Merchandisers often face issues with unexpected search rankings and missing products, leading to significant time lost in understanding search performance.

• Traditional platforms provide search results but lack clarity on the reasoning behind them, making it difficult for merchandising teams to diagnose issues without technical support.

• The Netcore Unbxd Debugger Agent is an AI-powered tool embedded in the Search Preview that offers real-time explanations of search results, directly addressing ranking and missing product queries.

• B2B retailers using AI-powered debugging tools resolve search quality issues three times faster than those relying on manual processes.

Imagine spending two hours on a Tuesday afternoon trying to understand why a high-margin product is ranking 47th for the query your buyers use most. You open the search preview. You test the query. You see the result. But the platform offers no explanation, just the ranking, with no indication of how it was arrived at or what is suppressing the product you expected to see higher up.

Now imagine a different but equally common scenario: a product you know is in the catalog simply does not appear in the results at all. You have checked that it is live. You know it matches the query. But it is absent. The search preview shows you what is there, not why something is missing. To investigate, you need engineering support, access to backend logs, and time you do not have.

These two problems, unexpected rankings and missing products, have been the most persistent sources of frustration for merchandising teams in search quality management. Not because the platforms were bad, but because the reasoning behind search decisions was fundamentally opaque. The results were visible. The logic behind them was not.

Industry benchmarks suggest ecommerce teams can lose up to 15 hours per week diagnosing search quality issues. That is nearly two full working days per week, per team, spent not improving the buyer experience but trying to understand why it degraded in the first place.

For B2B retailers, the cost of an unexplained search failure extends beyond a single session. A buyer who cannot find a product they need does not just abandon the search; they may question the catalog's reliability entirely. When search fails silently, it fails expensively. Yet most platforms offered merchandisers nothing more than a query-testing interface: type a search, see the results, and guess what was causing them.

“We could always see what was happening. We never knew why. And finding out required pulling in engineers who had more urgent things to do.”

The Netcore Unbxd Debugger Agent was built to end that cycle entirely.

Netcore Unbxd- Debugger Agent

Explainability built into the search preview

The Debugger Agent is an AI-powered assistant that lives within the Search Preview in the Netcore Unbxd console. It is accessible whenever the preview is open, making it a natural part of the workflow merchandisers already use to test and validate search behavior. There is no separate tool to launch, no additional panel to configure. It is simply there, ready to answer questions about what the search results are showing and why.

It translates system decisions, ranking logic, retrieval conditions, and eligibility rules into clear, plain-language explanations that any merchandiser, business user, or support team member can understand without deep technical expertise. For the first time, the people responsible for catalog quality have a direct line to the reasoning behind every search result.

Why is this product ranked here?

The most common question the Debugger Agent answers is the ranking question: why is a product appearing at a specific position for a given query? It analyses the ranking-relevance decisions behind that result and explains them in plain language, describing how the system weighted relevance signals to arrive at the current order and surfacing what would need to change for a product’s position to shift.

This matters enormously to merchandising teams who need to validate that their configurations produce the intended results. Rather than running test query after test query and trying to infer the logic from the output, a merchandiser can ask the Agent directly and receive a clear, specific explanation.

The investigation that previously took hours and often required escalation to engineering now takes minutes.

Ecommerce teams spend up to 60% of their time managing search rules and relevance tuning., - Groupby

Why is this product missing?

Equally important is the second question the Debugger Agent addresses: why is a product not appearing in the results? Missing product investigations have historically been among the hardest debugging tasks for merchandising teams, because the absence of a product gives you nothing to look at, only the products that are there, with no signal about what is excluding the one you expected.

The Debugger Agent fills that gap directly by analysing the retrieval and eligibility conditions that govern whether a product enters the result set for a given query, and explaining why a specific product did not meet them. Is it a catalog attribute mismatch? A retrieval filter that excludes the product? An eligibility condition that was not met? The agent tells you precisely, in language that does not require a background in search engineering to parse.

This capability alone represents a step change in how merchandisers interact with their search platform. The ability to investigate a missing product and understand the root cause without opening a support ticket, directly in the Search Preview, in real time, is not a marginal improvement. It is a different way of working.

Shoppers who use site search are 2–3× more likely to convert than non-search users. Opensend

Query-Level debugging with follow-up support

The Agent supports ongoing, query-level debugging within a single session. A merchandiser can start with a ranking question for one product, follow up with a missing-product investigation for another, then ask a broader question about how the query is behaving overall, all without leaving the Search Preview or losing the context of the conversation. The agent maintains awareness of the active query and result set throughout the session, making it as useful for systematic audits as for one-off investigations.

This is what democratising search intelligence actually looks like: not a more powerful dashboard for engineers, but a conversational interface for the people who are most accountable for search quality and most affected when it breaks.

Moving from diagnostic to predictive

The Debugger Agent, as it exists today, is reactive and explanatory: it answers questions about what is happening and why. The next evolution is predictive. In the coming quarters, the Netcore Unbxd Debugger Agent will be able to identify the conditions that precede a search quality problem and surface an alert before buyers encounter it.

This means analysing patterns across queries and result sets to detect early warning signals: retrieval conditions that are beginning to exclude a widening set of products, relevance scoring patterns that are drifting from expected behaviour, or configuration states that have historically preceded ranking problems in similar catalog contexts. It will flag these proactively, allowing merchandisers to investigate and intervene before any buyer session is affected.

On the roadmap: Integration with A/B testing workflows

Netcore Unbxd Debugger Agent will not only explain ranking behaviour but also propose specific experiments to validate proposed changes. Rather than guessing at the impact of a configuration adjustment, merchandisers will be able to test it on a defined traffic segment, measure the result, and ship the winning approach with confidence backed by data.

The best debugging is the kind that happens before anything breaks. That is where the Debugger Agent is headed.

There is a longer vision here, too. As the platform evolves toward a fully ‘agents-ready’ architecture, the Debugger Agent becomes part of an intelligent quality layer that continuously monitors search behaviour, not just explaining problems when they are reported, but maintaining the health of the search and merchandising stack in the background.

The industry has produced debug panels, query testers, and log viewers. This platform built an agent that speaks to merchandisers in their language, answers the questions they actually have, and makes the invisible logic of search visible to the people who most need to see it. That is not an iteration on what existed before. That is a new category. And it is only the beginning of where it is going.

Learn more about the Debugger Agent here.

Frequently Asked Questions

What is the Unbxd Debugger Agent?

The Unbxd Debugger Agent is an AI-powered assistant that explains why search results behave the way they do. It translates ranking decisions, retrieval logic, and eligibility conditions into plain-language explanations helping merchandisers, business users, and support teams understand search behavior for any query without needing technical or engineering expertise. It is accessible within the Search Preview in the Unbxd console.

Where is the Debugger Agent located in the Unbxd console?

The Debugger Agent is available within the Search Preview in the Unbxd console. It is accessible whenever the Search Preview is open, making it a natural part of the workflow that merchandisers already use to test and validate search results. No separate tool, panel, or support ticket is required, the agent is present and ready to answer questions directly within the preview interface.

Can the Debugger Agent explain why a product is missing from search results?

Yes. One of the Debugger Agent’s core capabilities is investigating missing products. When a product does not appear in the results for a given query, the agent analyses the retrieval and eligibility conditions governing that result set and explains precisely why the product was excluded whether due to a catalog attribute mismatch, a retrieval filter, or an unmet eligibility condition, all in plain language.

Who is the Debugger Agent designed for?

The Debugger Agent is designed for merchandisers, business users, and support teams who need visibility into search behavior without deep technical expertise. It removes the dependency on engineering escalation for search quality investigations, enabling the people most accountable for catalog performance to diagnose ranking and retrieval issues directly, independently, and in real time.

Can I ask the Debugger Agent multiple questions about different products in the same session?

Yes. The Debugger Agent supports multi-turn, conversational debugging within a single session. You can investigate a ranking question for one product, follow up with a missing product investigation for another, and then ask broader questions about how a specific query is behaving overall, all without leaving the Search Preview or losing the context of the conversation.