NeuronSearchLab works best when it understands the structure and behavior of your content. Use this guide to connect the three core data feeds that power recommendations.Documentation Index
Fetch the complete documentation index at: https://docs.neuronsearchlab.com/llms.txt
Use this file to discover all available pages before exploring further.
Prepare your catalog
Your catalog describes every item that may be recommended. Each record should include a stable identifier and useful metadata so the platform can learn how to rank items.Gather item attributes
Gather key attributes such as title, description, price, category, tags, and thumbnail URLs.
Map fields to the API
Map your data fields to the attributes accepted by the
POST /v1/items endpoint.Choose an ingestion path
Use the console Items page for small batches or the API for automated pipelines.
The more descriptive your metadata, the easier it is to tune filters, boosts, and personalization rules later.
Define contexts
Contexts capture where recommendations appear in your product experience—home feed, detail page, email digest, and more. Provide enough information to personalize each surface.Create contexts by surface
Create a context for each surface and record the numeric console ID, such as
101.Configure retrieval behavior
Configure the model family and pre-query filters inside the console under Contexts.
Stream real-time events
Engagement events help the service understand what resonates with your users.Send engagement events
Send impressions, clicks, conversions, and other behavioral events using the
POST /v1/events endpoint.Include event context
Include user identifiers, item identifiers, context IDs, and timestamps in each payload.