Compare MIAPI — Grounded AI Answers API to these popular alternatives based on real-world usage and developer feedback.

Elasticsearch is a distributed, RESTful search and analytics engine capable of storing data and searching it in near real time. Elasticsearch, Kibana, Beats and Logstash are the Elastic Stack (sometimes called the ELK Stack).

Our mission is to make you a search expert. Push data to our API to make it searchable in real time. Build your dream front end with one of our web or mobile UI libraries. Tune relevance and get analytics right from your dashboard.

Creating safe artificial general intelligence that benefits all of humanity. Our work to create safe and beneficial AI requires a deep understanding of the potential risks and benefits, as well as careful consideration of the impact.

Amazon Elasticsearch Service is a fully managed service that makes it easy for you to deploy, secure, and operate Elasticsearch at scale with zero down time.

It is a next-generation AI assistant. It is accessible through chat interface and API. It is capable of a wide variety of conversational and text-processing tasks while maintaining a high degree of reliability and predictability.

Swiftype is the easiest way to add great search to your website or mobile application.

It is an open source search and analytics engine derived from Elasticsearch 7.10.2, and is currently in an alpha state.

It makes it easy to build high-performance vector search applications. Developer-friendly, fully managed, and easily scalable without infrastructure hassles.

Amazon CloudSearch enables you to search large collections of data such as web pages, document files, forum posts, or product information. With a few clicks in the AWS Management Console, you can create a search domain, upload the data you want to make searchable to Amazon CloudSearch, and the search service automatically provisions the required technology resources and deploys a highly tuned search index.

It is a powerful, fast, open-source, easy to use, and deploy search engine. The search and indexation are fully customizable and handles features like typo-tolerance, filters, and synonyms.

It is Google’s largest and most capable AI model. It is built to be multimodal, it can generalize, understand, operate across, and combine different types of info — like text, images, audio, video, and code.

Azure Search makes it easy to add powerful and sophisticated search capabilities to your website or application. Quickly and easily tune search results and construct rich, fine-tuned ranking models to tie search results to business goals. Reliable throughput and storage provide fast search indexing and querying to support time-sensitive search scenarios.

It is a state-of-the-art foundational large language model designed to help researchers advance their work in this subfield of AI.

It is an open source, typo tolerant search engine that delivers fast and relevant results out-of-the-box. has been built from scratch to offer a delightful, out-of-the-box search experience. From instant search to autosuggest, to faceted search, it has got you covered.

It is a large multimodal model (accepting text inputs and emitting text outputs today, with image inputs coming in the future) that can solve difficult problems with greater accuracy than any of our previous models, thanks to its broader general knowledge and advanced reasoning capabilities.

It is a highly accurate and easy to use enterprise search service that’s powered by machine learning. It delivers powerful natural language search capabilities to your websites and applications so your end users can more easily find the information they need within the vast amount of content spread across your company.

It is the only cloud search service with built-in AI capabilities that enrich all types of information to easily identify and explore relevant content at scale. Formerly known as Azure Search, it uses the same integrated Microsoft natural language stack that Bing and Office have used for more than a decade and AI services across vision, language and speech. Spend more time innovating and less time maintaining a complex cloud search solution.

It offers an API to add cutting-edge language processing to any system. Through training, users can create massive models customized to their use case and trained on their data.

Your customers expect fast, near-magical results from your search. Help them find what they’re looking for with Bonsai Elasticsearch. Our fully managed Elasticsearch solution makes it easy to create, manage, and test your app's search.

It is a general-purpose speech recognition model. It is trained on a large dataset of diverse audio and is also a multi-task model that can perform multilingual speech recognition as well as speech translation and language identification.

It is a small, yet powerful model adaptable to many use cases. It is better than Llama 2 13B on all benchmarks, has natural coding abilities, and 8k sequence length. We made it easy to deploy on any cloud.

It makes it easy for you to perform interactive log analytics, real-time application monitoring, website search, and more. OpenSearch is an open source, distributed search and analytics suite derived from Elasticsearch.

It is an advanced language model comprising 67 billion parameters. It has been trained from scratch on a vast dataset of 2 trillion tokens in both English and Chinese.

It is composed of a series of code language models, each trained from scratch on 2T tokens, with a composition of 87% code and 13% natural language. There are various sizes of the code model, ranging from 1B to 33B versions.

Create your own fully managed and hosted Elasticsearch cluster. You get a dedicated cluster with reserved memory, giving you predictable performance. There are no arbitrary limits on how many indexes or documents you can store. Scale your clusters as and when needed, without any downtime.

It is a full-text search engine written in C++ and a fork of Sphinx Search. It's designed to be simple to use, light and fast, while allowing advanced full-text searching. Connectivity is provided via a MySQL compatible protocol or HTTP, making it easy to integrate.

It is the base model weights and network architecture of Grok-1, the large language model. Grok-1 is a 314 billion parameter Mixture-of-Experts model trained from scratch by xAI.

Yext's Answers Platform collects and organizes content into a Knowledge Graph, then leverages a complementary set of products to deliver relevant, actionable answers wherever customers, employees, and partners look for information.

We help your website visitors find what they are looking for. AddSearch is a lightning fast, accurate and customizable site search engine with a Search API. AddSearch works on all devices and is easy to install, customize and tweak.

It is an open-source library for fast LLM inference and serving. It delivers up to 24x higher throughput than HuggingFace Transformers, without requiring any model architecture changes.

Qbox is supported, dedicated, hosted Elasticsearch - the bleeding edge of full-text search and analytics. We provide an intuitive interface to provision, secure, and monitor ES clusters in Amazon EC2 and Rackspace datacenters everywhere.

It is an autoregressive Large Language Model (LLM), trained to continue text from a prompt on vast amounts of text data using industrial-scale computational resources. It is able to generate text in 46 natural languages and 13 programming languages.

It is a state-of-the-art LLM capable of generating code, and natural language about code, from both code and natural language prompts. It is built on top of Llama 2 and is available for free.

Try Grok 4 on GPT Proto. Access xAI’s most advanced 1.7T LLM with 130K context, multimodal support, and real-time data integration for dynamic analysis.

It is a set of models that improve on GPT-3 and can understand as well as generate natural language or code.

It is the next-gen search & analytics engine built for logs. It is designed from the ground up to offer cost-efficiency and high reliability on large data sets. Its benefits are most apparent in multi-tenancy or multi-index settings.
Easily add custom full-text search, without the cost or complexity of managing search servers
It is an embeddable super fast full text search engine. It can be embedded into MySQL. Mroonga is a storage engine that is based on it.

It is an open-source language model. It is trained with 1.5 trillion tokens of content. The richness of dataset gives StableLM surprisingly high performance in conversational and coding tasks.

It is a collection of open-source models for generating various types of media.
The web crawling, scraping, and search API for AI. Built for scale. Firecrawl delivers the entire internet to AI agents and builders. Clean, structured, and ready to reason with.

Millions of job postings through one simple API. Perfect for apps, AI agents, sales intelligence & HR tech.

It is a foundational large language model (LLM) with 40 billion parameters trained on one trillion tokens.

It is an intelligent site search solution designed to help eCommerce businesses increase onsite sales and improve the customer online shopping experience.

It is an open source Java wrapper for Elasticsearch, implementing an opinionated, fresh approach to implement new search/analytics enabled applications or enhance legacy software based on relational databases with powerful full text search capabilities.

It is an open-source project that has released a 7 billion parameter base model, a chat model tailored for practical scenarios, and a training system.

It represents a novel end-to-end trained large multimodal model that combines a vision encoder and Vicuna for general-purpose visual and language understanding, achieving impressive chat capabilities mimicking spirits of the multimodal GPT-4 and setting a new state-of-the-art accuracy on Science QA.

It is a state-of-the-art LLM for converting natural language questions to SQL queries. It has been fine-tuned on hand-crafted SQL queries in increasing orders of difficulty. It significantly outperforms all major open-source models and slightly outperforms gpt-3.5-turbo.

It is a next-generation large language model that excels at advanced reasoning tasks, including code and math, classification, question answering, translation, multilingual proficiency, and natural language generation.

It is a family of lightweight, state-of-the-art open models built from the same research and technology used to create the Gemini models.