Provides an AI-native search platform that combines semantic understanding, multimodal indexing, and real-time relevance optimization to improve search accuracy and user experience. By automating query evaluation, fine-tuning, and embedding management, it enables developers to integrate advanced search capabilities in days, reducing the need for manual tagging and in-house infrastructure.
Funding
$13M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Many applications struggle to provide accurate and relevant search results due to limitations in understanding user intent and the semantic meaning of data. Traditional search methods often rely on manual tagging and keyword matching, which can be time-consuming, inaccurate, and difficult to scale. This results in poor user experiences and hinders effective information retrieval.
Solution
Objective offers an AI-native search platform designed to enhance search accuracy and user experience through semantic understanding, multimodal indexing, and real-time relevance optimization. The platform automates query evaluation, fine-tuning, and embedding management, enabling developers to integrate advanced search capabilities quickly. By leveraging ensemble models and AI-powered finetuning, Objective ensures that search results align with user intent and adapt to evolving data. The platform's transparent embedding management and automated relevance evaluation streamline the development process, reducing the need for manual intervention and in-house infrastructure.
Target Audience
The primary target audience includes product and engineering teams building search and discovery experiences, particularly those in e-commerce, content management, and knowledge management.
Features
- Semantic text search that understands the meaning behind user queries
- Image search capabilities that analyze image content to match search intent
- Multimodal search that combines text and image analysis for comprehensive results
- Ensemble models that blend best-of-breed technologies for enhanced accuracy
- AI-powered finetuning that automatically optimizes search indexes based on user behavior
- Automated relevance evaluation using the Anton API to validate and experiment at scale
- Transparent embedding management that handles data transformations in real-time
- Geofiltering to refine search results based on location
- TypeScript and Python SDKs for rapid integration