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Set up your access

NeuronSearchLab is a hosted API service that provides real-time personalized recommendations through an API, SDK, and a web console. You do not need to deploy or install anything - just sign up and generate your API credentials.

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1. Register or log in

Go to console.neuronsearchlab.com/signup or login to create an account. You can invite teammates later from the User Management page in Settings.

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2. Generate client credentials

Once logged in, open SDK Credentials in Settings and create a new client. Copy the Client ID and Client Secret. They are required to authenticate your backend services.
Never expose the Client Secret in browser code or mobile apps. Store it in your server-side environment variables or a secrets manager.

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3. Add your first dataset

Navigate to Items in the Explore section and use the upload flow to add a handful of representative items. Include metadata such as category, price, tags, and thumbnails to improve downstream recommendations.

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Authenticate securely

Create a backend route that exchanges your client credentials for an access token. The token scopes enforce what each service can do. 
curl -X POST https://api.neuronsearchlab.com/auth/token \
  -H "Authorization: Basic <base64(client_id:client_secret)>" \
  -H "Content-Type: application/x-www-form-urlencoded" \
  -d "grant_type=client_credentials"
  1. Call the /auth/token endpoint from a trusted server environment.
  2. Cache the resulting access token until it expires (tokens default to 60 minutes).
  3. Forward the token to your frontend or edge workers via secure headers.
Rotate credentials regularly and prefer one client per application so you can revoke access without downtime.

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Make your first API call

With an access token you can request recommendations immediately. The following example retrieves homepage content for a known user using context ID 101: 
curl -X GET "https://api.neuronsearchlab.com/recommendations?user_id=user-123&context_id=101" \
  -H "Authorization: Bearer <your_access_token>"
Send optional query parameters such as limit, filters, or boosts to tailor the response. Responses include ranked items with associated metadata so you can render UI components quickly. If you prefer higher level abstractions, use one of the official SDKs from your backend:

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Explore the console

In addition to the API and SDK, you can manage your data and monitor performance through the NeuronSearchLab Console. Key areas include:
  • Dashboard — Usage overview, credit tracking, and setup checklist.
  • Context — Define contexts for each recommendation surface with retrieval settings and pre-query filters.
  • Rules Engine — Create business rules to boost, bury, pin, filter, cap, diversify, dedupe, randomize, reorder, group, or topic-weight results.
  • Pipeline Config — Control the multi-stage recommendation pipeline.
  • Explainability — Debug why a specific item was recommended to a specific user.
  • Analytics — Track recommendation volume, engagement events, and performance over time.
  • Items & Users — Browse your catalog and user embeddings.
  • A/B Testing — Split traffic between strategies and measure impact.
  • NeuronSearchLab AI — Conversational assistant for managing recommendations through natural language.

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Extend your integration

NeuronSearchLab supports rich documentation and examples to help you integrate quickly and effectively.

PHP SDK

Install the official PHP SDK with Composer for Laravel or any PHP service.

JavaScript SDK

Use the official npm package from Node.js or TypeScript services.

Serve Recommendations

Ship real-time personalized recommendations with context-aware request patterns.

Connect Catalog + Events

Keep item metadata and engagement signals flowing for recommendation quality.

Launch New Contexts

Roll out a new recommendation surface with measurable business outcomes.

Track Events

Log impressions, clicks, and conversions to power near real-time learning.

Submit Items

Send product or content metadata to build and refresh your catalog.

Get Recommendations

Retrieve personalized results that respect context, filters, and boosts.