miso.ai Product / Content APIs API

Miso's Product / Content APIs let you upload, read, and delete Product / Content records that represent your site's catalog. ### Product / Content records Miso analyzes your Product / Content records to provide personalized search and recommendations that connect users with products or content on your site or application. Much of Miso's search and personalization capability relies on understanding your catalog in-depth and drawing correlations between your catalog and your users' consumption or purchasing behaviors. In other words, Miso discovers that, with high correlation, users who are interested in certain product attributes would also be interested in other products with similar or related attributes. (For simplicity, we will often overload the word "products" to mean items for purchase if you are an eCommerce business, and content to consume if you are a content marketplace.) To fully optimize your search and recommendations, it is important to provide Miso with Product / Content records that are complete and accurate. We define a set of common attributes that capture the basics of most eCommerce and content media products, such as `title`, `description`, `categories`, `tags`, `material`, `authors`, etc. If your products' characteristics cannot be fully captured by these fields, we recommend that you specify `custom_attributes`. For Miso, the more complete the product information is, the better its personalized search and recommendations become.

Business capability
Item Master Data Management BC-2370.10

Operations 5

POST /v1/products Product / Content Upload API #
GET /v1/products/{product_id} Product / Content Read API #
DELETE /v1/products/{product_id} Product / Content Delete API #
GET /v1/products/_ids Product / Content ID List API #
POST /v1/products/_delete Product / Content Bulk Delete API #

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OpenAPI Specification

misoai-product-content-apis-api-openapi.yml Raw ↑
openapi: 3.2.0
info:
  title: Miso Product / Content APIs API
  description: '# Overview

    Miso’s approach to personalization is to train machine learning Engines on three core data sets:


    1.'
  version: 1.1.4
servers:
- url: https://api.askmiso.com
tags:


# --- truncated at 32 KB (43 KB total) ---
# Full source: https://raw.githubusercontent.com/api-evangelist/misoai/refs/heads/main/openapi/misoai-product-content-apis-api-openapi.yml