Welcome to the API documentation for Objective Search. This site contains information about how to access and use the APIs. If you have questions, or find something is not covered in this doc, please let us know.

Objective Search empowers developers with a plug-and-play search API that works on multiple media types - in particular, complex Objects composed of embedded text and links to images.

To get an API key join the waitlist. To see more of what Objective Search can do, check out our live demos.


  • Indexing
    • Text, image & multimodal indexes - Index and search semantically on your text and image data using state of the art vector embeddings.
    • Real-time indexing
    • Document processing & image crawling
    • Schemaless - Index both structured or unstructured data.
    • High throughput indexing - Index 1000s of objects per second.
  • Relevance
    • Finetuning - Train your indexes to improve relevance based on user feedback or your specific business needs.
    • Auto-finetuning - Train your indexes using state of the art AI models when human feedback is not readily available.
    • Evaluations - Run evaluations and compare the search quality of your indexes and track the quality over time.
    • Result Cutoffs - Dynamically limit the number of results to only the most relevant.
  • Search
    • Semantic similarity - Return content-based recommendations to users
    • Filtering - Extensive and flexible syntax for dynamically filtering search results.
    • Geo-filtering - Filter search results based on geographic location.
    • Ranking Signals - Dynamically change or personalize search results at query-time using a robust and extensive syntax.
    • Highlights - Highlight specific elements in your search results based on their relevance to the user’s query.
    • Low latency - Average 40ms search request latency.
  • Platform
    • Horizontally and elastically scalable
    • REST APIs, Python and Typescript SDKs
    • Developer friendly - Go from zero to production grade search API in minutes.

Platform overview

At its core, the Objective platform stores your Objects and enables you to build Indexes from those Objects for the purpose of searching.

Objects are schemaless, and can contain both structured and unstructured data. You’ll use the Objects API to store and manage Objects in the Object Store.

Objects in the Object Store can then be added to one or more Indexes using the Create Index API. Being added to an Index makes an Object searchable. When creating an Index, you’re able to choose specific fields from your Objects to index, such as title, description and image_url. Indexes are kept up to date as you make updates to the underlying Objects in the Object Store.

Finally, after having added your Objects to one or more Indexes, you’ll use the Search API to issue search requests against your Indexes.

Objective Search API integration model

Objective inc architecture

Objective, Inc high level architecture

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Key concepts

The Object Store and Objects

All data added to the platform is stored in the Object Store. The Object Store is a collection of schemaless Objects, which are represented using JSON. An Object’s fields can be searchable text (represented as Strings), URLs to images that the platform should crawl (also represented as Strings) as well as other JSON data types (arrays, numbers, dates, booleans, and nested JSON).


Indexes are built from Objects in the Object Store, according to composition rules that you define. Adding Objects to an Index is what makes them searchable. Once an Index is built, you can query the Objects in that Index using the /search API.


When you search an Index, the API returns relevant Objects along with Highlights. A Highlight represents the most relevant portions of a matching Object, be it a section of text or an image.