Recommendation systems
Recommendation engine API
What is a recommendation engine API?
The value of the API form is that the ranking becomes a service rather than a library. Your application asks a question and renders an answer; the model, the features, the retraining schedule and the serving infrastructure sit on the other side of one stable contract. That contract is the thing worth scrutinising, because it is what you are actually buying.
The NeuronSearchLab recommendation API
The API base is https://api.neuronsearchlab.com. Authentication is OAuth 2.0 client credentials against https://auth.neuronsearchlab.com/oauth2/token, which returns a bearer token carrying the neuronsearchlab-api/read and neuronsearchlab-api/write scopes. There are JavaScript and PHP SDKs, a Vercel integration, an MCP server and a ChatGPT plugin over the same platform.
A single recommendation model gives you one fixed way of ranking. NeuronSearchLab trains and compares several architectures on your own data, keeps the winner behind one unchanging API, and gives you evaluation, experimentation, explainability and editorial control over whatever is serving.
The endpoints
Four core endpoint groups, plus the platform API behind the console. Full reference in the API documentation.
Catalogue
POST /v1/items, GET /v1/items, GET /PATCH /DELETE /v1/items/{item_id} - create, list, read, update and remove catalogue items with their metadata and any embeddings you attach.Events
POST /v1/events, GET /v1/events, GET /v1/events/{event_id} - record and inspect interactions. Event types and signal templates are configurable, so a custom event such as a completion or a subscription counts as a first-class signal rather than being flattened into a click.Recommendations
GET /v1/recommendations - the ranked slate, for a user, an item or a context. A context is a named surface with its own pipeline configuration and rules, so the same integration serves a homepage rail and a product detail page differently without branching in your code.Search
POST /v1/search - personalised search over the same catalogue and the same signals, so search and recommendation results do not disagree about what a user is interested in.Platform
What an integration involves
Four steps, in this order. The first ranked result usually arrives on the same day as the first event.
01 · Credentials
02 · Catalogue
03 · Events
04 · Request
What to check before you integrate
Six questions that are cheap to ask now and expensive to discover later. Worth asking of every vendor in this category, us included.
The data contract
Latency and where it runs
Filtering and rules at request time
Idempotency and failure behaviour
Whether the model behind it can change
What you can read back
What sits behind the endpoint
A recommendation API is only as good as what you can do to the thing answering it. These are the platform capabilities NSL exposes behind the same integration.
- Several recommender architectures trained on your data and compared like for like, with the winner serving behind an unchanged endpoint
- Your own embeddings attached to items and used for retrieval and ranking, from any provider
- A rules engine covering boost, bury, pin, filter, cap, dedupe, reorder and group, scoped per context and applied at request time
- Shadow and canary releases with conditional promotion and automatic rollback
- Per-result explainability: scores, rules and pipeline stages for one item in one slate
- A/B testing of ranking strategies, with results attributed to the variant
- Segments defined from behaviour, demographics and item interactions
- Analytics across relevance, engagement, coverage, diversity, novelty, latency and cost
The NSL Recommender Leaderboard is the public version of the model-comparison work: complete recommender systems measured on ten public datasets, with methodology, downloadable results and every caveat published.
Other recommendation APIs
Six products commonly evaluated alongside NSL, on the dimensions that matter to an integration. Sourced from each vendor’s public documentation.
| Product | Recommendation API | Editorial controls | Explainability | Real-time updates | Deployment options |
|---|---|---|---|---|---|
| NeuronSearchLabRecommendation platform: build, evaluate, operate | Documented | Documented | Documented | Documented | Partly |
| RecombeeRecommendation-as-a-service API | Documented | Documented | Not documented | Documented | Partly |
| Amazon PersonalizeManaged recommendation service on AWS | Documented | Partly | Not documented | Documented | Partly |
| Algolia RecommendRecommendation add-on to a hosted search index | Documented | Documented | Not documented | Partly | Partly |
| Dynamic YieldPersonalisation and experimentation suite | Documented | Documented | Not documented | Documented | Partly |
| BloomreachCommerce search, merchandising and marketing suite | Documented | Documented | Partly | Partly | Partly |
| NostoCommerce experience platform | Documented | Documented | Not documented | Documented | Partly |
How to read this table
- Documented - the vendor’s own public documentation describes this as a capability.
- Partly - documented, with a material limit named in the cell.
- Not documented - we could not find it in the public documentation. That is not the same as it not existing. Ask the vendor.
- Out of scope - the documentation says it is not part of the product.
Compiled from public documentation on 19 September 2026. Products change; every claim links to the page it came from, so check the source before you rely on it. Nothing here is scored, ranked or totalled.
Frequently asked questions
What is a recommendation engine API?
What endpoints does a recommendation API normally have?
What is the NeuronSearchLab API base URL?
How fast should a recommendation API be?
Can I filter or override what a recommendation API returns?
Can an AI agent call a recommendation API?
Related reading
Make your first request
Create a key, push a catalogue, send events, call the endpoint. The free tier includes 1,000 recommendation requests a month and needs no card.