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How to Make Product Data AI-Shopping Ready in 2026
A 220-question study found factual conflicts in 86% of AI shopping answers. Here is a nine-step workflow to make your product data the source AI engines quote correctly.
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How to Make Product Data AI-Shopping Ready in 2026
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The Open-Model Trade: What You Own When You Self-Host
Self-hosting an open model is not a cheaper version of using an API. It is a different set of responsibilities. Here is what you actually take on, what you gain, and how to tell whether the trade is working.
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Building a Hybrid Stack: Laya Local, Jev Cloud
Run the cheap decisions locally and escalate only the hard ones. Here is the hybrid architecture, the routing question that makes it work, the cost model, and the failure mode that makes it dangerous.
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Laya vs Jev: An Honest Decision Guide
Laya is free and local. Jev is hosted and more accurate out of the box. Both of those statements are true, and the choice between them is not obvious. Here is the comparison with the baselines named, including the benchmarks that are not comparable.
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Guardrails: Using Laya to Check Your Own Agents
A local decision model is the right place to catch prompt injection, destructive actions, and stuck loops in your own agents. Here is how to build the guardrail layer, including the selective-coverage trick that raises accuracy where it matters.
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Laya for Internal Linking, and Where It Breaks
Internal linking is thousands of yes/no decisions, which is exactly what a decision model is for. It is also where Laya's wide-option weakness bites hardest. Here is the workflow, the limit, and the cascade that works around it.
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Laya for Content Audits: Keep, Update, Merge, Remove
A full content audit is a routing problem with four possible answers. Here is how to run every page through a local Laya decision, plan the throughput, and avoid the two ways this workflow produces confident nonsense.
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Laya for GEO Answer Scoring, Offline
Score what ChatGPT, Perplexity, and the other engines say about your category without sending any of it to a third party. Here is the offline GEO scoring workflow, the presence taxonomy, and how to set a threshold on a model whose confidence runs high.
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Laya as a Local Reranker for Internal Search and RAG
Similarity search finds passages that look related. It does not find passages that actually answer the question. Here is how to add a local Laya reranking stage, how to measure whether it helped, and where it fits in SEO work.
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Fine-Tuning Laya on Your Own SEO Labels
Fine-tuning is the one capability that makes an open decision model genuinely different from a hosted one. Here is how to build a label set from your own review decisions, train on a laptop, and avoid the trap that inflates every published benchmark.
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Laya for Search Intent Classification at Scale
Classify thousands of queries by intent with a local model, including the cascade design that works around Laya's twenty-option limit, the confidence threshold you set from your own data, and how to measure whether it is actually right.
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Running Laya Locally: Hardware, Latency, and What Free Actually Costs
Laya has no per-call cost, but self-hosting is not free. Here is the real cost model: latency by hardware tier, throughput planning, a break-even calculation, and the point where a hosted API is still the better choice.
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What Is Laya? The Open Decision Model SEO Teams Can Run Locally
Laya is a free, open-source decision model you can run on your own laptop. Here is what it does, how to install it, how to wire it into your agent, and the two failure modes that will bite you if you skip the setup.
