Best Semantic Search APIs in 2024

What is Semantic Search?

Semantic Search API refers to a type of search that uses Natural Language Processing (NLP) and Machine Learning algorithms to understand the meaning behind a user's query, rather than just searching for matching keywords. It will take into account the context, intent, and relationships between words to provide more relevant and accurate search results. In other words, it focuses on the user's intent rather than just the specific words used in the query.

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Semantic Search APIs uses cases

You can use Semantic Search in numerous fields, here are some examples of common use cases:

• E-commerce: improve product search results by understanding the intent of users and returning more accurate product recommendations.
• Healthcare: help medical professionals find relevant research and clinical trial data quickly and easily.
• News and media: analyze news articles and provide more targeted search results to users.
• Legal: help legal professionals quickly find relevant cases, statutes, and other legal documents.
• Education: help students and researchers find relevant academic papers and research more easily, improving their ability to conduct research and write papers.

These are just a few examples of Semantic Search API uses case, it can be applied in any field where there's a need to understand the meaning behind a user's query and provide more accurate and personalized results.

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Best Semantic Search APIs on the market

While comparing Semantic Search APIs, it is crucial to consider different aspects, among others, cost security and privacy. Semantic Search experts at Eden AI tested, compared, and used many Semantic Search APIs of the market. Here are some actors that perform well (in alphabetical order):

• Cohere
• Google Cloud
• NLP Cloud
• Open AI
• Sapling.ai

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1. Cohere - Available on Eden AI

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Cohere's Semantic Search API allows users to search through large datasets using natural language. The API is based on advanced Machine Learning models, offering high accuracy and fast response time. Cohere's API also allows for customization, enabling companies to tailor their search results to their specific needs.

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2. Google Cloud - Available on Eden AI

Google Cloud's Semantic Search API utilizes advanced natural language processing and machine learning techniques to deliver more accurate and contextually relevant search results, enhancing the overall search experience for users.

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3. NLP Cloud

NLP Cloud provides a Semantic Search API powered by advanced natural language processing models, ensuring precise and relevant search results even for complex queries. Moreover, the API is highly customizable, offering the flexibility to tailor the search results to specific industries or use cases. Users can also create their own semantic search engine by leveraging NLP Cloud's API and integrating their own business data to improve search accuracy and relevance.

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3. Open AI - Available on Eden AI

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Open AI’s Semantic Search API uses advanced language models and Machine Learning techniques to understand the meaning behind user queries and to match them with relevant results. Thanks to its extensive training on vast amounts of diverse data, the API delivers highly accurate and comprehensive search results, even for complex queries. Additionally, OpenAI's solution is customizable, enabling users to fine-tune their search results to specific domains or topics.

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4. Sapling.ai

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Sapling.ai's API leverages sophisticated NLP methods to facilitate natural language-based information retrieval. This technology boasts high precision and quick response times, enabling it to handle intricate queries. Furthermore, Sapling.ai accommodates an extensive array of data sources, including structured and unstructured data. User experience is further elevated through features such as synonym recognition and auto-complete suggestions.

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Performance variations of Semantic Search APIs

For all companies who use Semantic Search APIs in their software: cost and performance are real concerns. The Semantic Search market is quite dense and all those providers have their benefits and weaknesses.

Performances of Semantic Search vary according to the specificity of data used by each AI engine for their model training. This means that some Semantic Search may perform great for some languages but won’t necessarily for others.

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Performance variations according to the languages

Semantic Search APIs perform differently depending on the language of the text. In fact, some providers are specialized in specific languages. Different specificities exist:

• Region specialties: some Semantic Search APIs improve their machine learning algorithm to make them accurate for text in a specific language spoken in particular countries or regions. For example, some APIs perform well in English (US, UK, Canada, South Africa, Singapore, Hong Kong, Ghana, Ireland, Australia, India, etc.), while others are specialized in Asian languages (Korean, Japanese, Chinese, etc.)

• Rare language specialty: some Semantic Search providers care about rare languages and dialects. You can find Semantic Search APIs that allow you to process text in Gujarati, Marathi, Burmese, Pashto, Zulu, Swahili, etc.

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Performance variations according to fields

Some Semantic Search APIs trained their engine with specific data. This means that some Semantic Search APIs will perform better for educational articles, while others will perform better on technical documents.

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Why choose Eden AI to manage your Semantic Search APIs

‍Companies and developers from a wide range of industries (Social Media, Retail, Health, Finances, Law, etc.) use Eden AI’s unique API to easily integrate Semantic Search tasks in their cloud-based applications, without having to build their own solutions.

Eden AI offers multiple AI APIs on its platform amongst several technologies: Text-to-Speech, Language Detection, Sentiment Analysis, Question Answering, Data Anonymization, Speech Recognition, Face Detection and so forth.

We want our users to have access to multiple Semantic Search engines and manage them in one place so they can reach high performance, optimize cost and cover all their needs. There are many reasons for using multiple APIs :

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• ‍Fallback provider is the ABCs: You need to set up a provider API that is requested if and only if the main Semantic Search API does not perform well (or is down). You can use confidence score returned or other methods to check provider accuracy.
• ‍Performance optimization: After the testing phase, you will be able to build a mapping of providers’ performance based on the criteria you have chosen (languages, fields, etc.). Each data that you need to process will then be sent to the best Semantic Search API.‍
• Cost - Performance ratio optimization: You can choose the cheapest Semantic Search provider that performs well for your data.
• ‍Combine multiple AI APIs: This approach is required if you look for extremely high accuracy. The combination leads to higher costs but allows your AI service to be safe and accurate because Semantic Search APIs will validate and invalidate each other for each piece of data.

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How Eden AI can help you?

‍Eden AI has been made for multiple AI APIs use. Eden AI is the future of AI usage in companies. Eden AI allows you to call multiple AI APIs.

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• Centralized and fully monitored billing on Eden AI for all Semantic Search APIs
• Unified API for all providers: simple and standard to use, quick switch between providers, access to the specific features of each provider
• Standardized response format: the JSON output format is the same for all suppliers thanks to Eden AI's standardization work. The response elements are also standardized thanks to Eden AI's powerful matching algorithms.
• The best Artificial Intelligence APIs in the market are available: big cloud providers (Google, AWS, Microsoft, and more specialized engines)
• Data protection: Eden AI will not store or use any data. Possibility to filter to use only GDPR engines.

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You can see Eden AI documentation here.

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Next step in your project

The Eden AI team can help you with your Semantic Search integration project. This can be done by :

• Organizing a product demo and a discussion to better understand your needs. You can book a time slot on this link: Contact
• By testing the public version of Eden AI for free: however, not all providers are available on this version. Some are only available on the Enterprise version.
• By benefiting from the support and advice of a team of experts to find the optimal combination of providers according to the specifics of your needs
• Having the possibility to integrate on a third party platform: we can quickly develop connectors

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