Alternatives to Semantee
Compare Semantee alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Semantee in 2026. Compare features, ratings, user reviews, pricing, and more from Semantee competitors and alternatives in order to make an informed decision for your business.
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Couchbase
Couchbase
Couchbase’s operational data platform for AI is a scalable foundation for enterprise operational, analytical, mobile and AI workloads that replaces legacy infrastructure and data services. Bring your data to life in new ways with Couchbase’s enterprise data partnership: launch game-changing customer experiences, explore the infinite possibilities of AI, scale your global operations, and move your data from the cloud to the edge, and beyond. Couchbase’s operational data platform for AI eliminates fragmented tech stacks, so teams can stay innovative and agile, with less risk and lower cost of ownership. With enterprise partnership and scalable, AI-ready technology, Couchbase turns your data into the foundation for your next breakthrough. -
2
Pinecone
Pinecone
The AI Knowledge Platform. The Pinecone Database, Inference, and Assistant make building high-performance vector search apps easy. Developer-friendly, fully managed, and easily scalable without infrastructure hassles. Once you have vector embeddings, manage and search through them in Pinecone to power semantic search, recommenders, and other applications that rely on relevant information retrieval. Ultra-low query latency, even with billions of items. Give users a great experience. Live index updates when you add, edit, or delete data. Your data is ready right away. Combine vector search with metadata filters for more relevant and faster results. Launch, use, and scale your vector search service with our easy API, without worrying about infrastructure or algorithms. We'll keep it running smoothly and securely. -
3
Qdrant
Qdrant
Qdrant is a high-performance, composable vector search engine built in Rust for production-grade semantic, hybrid, and agentic workloads. Combine dense vectors, sparse vectors, metadata filters, multi-vector representations, and custom scoring as primitives at query time. Written in Rust for memory efficiency, SIMD optimization, and predictable performance without garbage collection pauses. No wrappers, no bolt-ons, no legacy compromises — just a custom HNSW implementation and storage engine built specifically for vector workloads. -
4
Find specific answers and trends from documents and websites using search powered by AI. Watson Discovery is AI-powered search and text-analytics that uses innovative, market-leading natural language processing to understand your industry’s unique language. It finds answers in your content fast and uncovers meaningful business insights from your documents, webpages and big data, cutting research time by more than 75%. Semantic search is much more than keyword search. Unlike traditional search engines, when you ask a question, Watson Discovery adds context to the answer. It quickly combs through content in your connected data sources, pinpoints the most relevant passage and provides the source documents or webpage. A next-level search experience with natural language processing that makes all necessary information easily accessible. Use machine learning to visually label text, tables and images, while surfacing the most relevant results.Starting Price: $500 per month
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5
Mistral AI
Mistral AI
Mistral AI is a pioneering artificial intelligence startup specializing in open-source generative AI. The company offers a range of customizable, enterprise-grade AI solutions deployable across various platforms, including on-premises, cloud, edge, and devices. Flagship products include "Le Chat," a multilingual AI assistant designed to enhance productivity in both personal and professional contexts, and "La Plateforme," a developer platform that enables the creation and deployment of AI-powered applications. Committed to transparency and innovation, Mistral AI positions itself as a leading independent AI lab, contributing significantly to open-source AI and policy development.Starting Price: Free -
6
Azure AI Search
Microsoft
Deliver high-quality responses with a vector database built for advanced retrieval augmented generation (RAG) and modern search. Focus on exponential growth with an enterprise-ready vector database that comes with security, compliance, and responsible AI practices built in. Build better applications with sophisticated retrieval strategies backed by decades of research and customer validation. Quickly deploy your generative AI app with seamless platform and data integrations for data sources, AI models, and frameworks. Automatically upload data from a wide range of supported Azure and third-party sources. Streamline vector data processing with built-in extraction, chunking, enrichment, and vectorization, all in one flow. Support for multivector, hybrid, multilingual, and metadata filtering. Move beyond vector-only search with keyword match scoring, reranking, geospatial search, and autocomplete.Starting Price: $0.11 per hour -
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Zilliz Cloud
Zilliz
Zilliz Cloud is a fully managed vector database based on the popular open-source Milvus. Zilliz Cloud helps to unlock high-performance similarity searches with no previous experience or extra effort needed for infrastructure management. It is ultra-fast and enables 10x faster vector retrieval, a feat unparalleled by any other vector database management system. Zilliz includes support for multiple vector search indexes, built-in filtering, and complete data encryption in transit, a requirement for enterprise-grade applications. Zilliz is a cost-effective way to build similarity search, recommender systems, and anomaly detection into applications to keep that competitive edge.Starting Price: $0 -
8
Oracle AI Vector Search
Oracle
Oracle AI Vector Search is a capability within Oracle Database designed for AI workloads that enables querying data based on semantics or meaning rather than traditional keyword matching. It allows organizations to search both structured and unstructured data using similarity search, making it possible to retrieve results based on contextual relevance instead of exact values. It uses vector embeddings to represent data such as text, images, or documents, and applies specialized vector indexes and distance functions to efficiently identify similar items. It introduces a native VECTOR data type, along with SQL operators and syntax that allow developers to combine semantic search with relational queries on business data in a single database environment. This eliminates the need for separate vector databases and reduces data fragmentation by keeping AI and operational data unified. -
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Superlinked
Superlinked
Combine semantic relevance and user feedback to reliably retrieve the optimal document chunks in your retrieval augmented generation system. Combine semantic relevance and document freshness in your search system, because more recent results tend to be more accurate. Build a real-time personalized ecommerce product feed with user vectors constructed from SKU embeddings the user interacted with. Discover behavioral clusters of your customers using a vector index in your data warehouse. Describe and load your data, use spaces to construct your indices and run queries - all in-memory within a Python notebook. -
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TopK
TopK
TopK is a serverless, cloud-native, document database built for powering search applications. It features native support for both vector search (vectors are simply another data type) and keyword search (BM25-style) in a single, unified system. With its powerful query expression language, TopK enables you to build reliable search applications (semantic search, RAG, multi-modal, you name it) without juggling multiple databases or services. Our unified retrieval engine will evolve to support document transformation (automatically generate embeddings), query understanding (parse metadata filters from user query), and adaptive ranking (provide more relevant results by sending “relevance feedback” back to TopK) under one unified roof. -
11
txtai
NeuML
txtai is an all-in-one open source embeddings database designed for semantic search, large language model orchestration, and language model workflows. It unifies vector indexes (both sparse and dense), graph networks, and relational databases, providing a robust foundation for vector search and serving as a powerful knowledge source for LLM applications. With txtai, users can build autonomous agents, implement retrieval augmented generation processes, and develop multi-modal workflows. Key features include vector search with SQL support, object storage integration, topic modeling, graph analysis, and multimodal indexing capabilities. It supports the creation of embeddings for various data types, including text, documents, audio, images, and video. Additionally, txtai offers pipelines powered by language models that handle tasks such as LLM prompting, question-answering, labeling, transcription, translation, and summarization.Starting Price: Free -
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ZeusDB
ZeusDB
ZeusDB is a next-generation, high-performance data platform designed to handle the demands of modern analytics, machine learning, real-time insights, and hybrid data workloads. It supports vector, structured, and time-series data in one unified engine, allowing recommendation systems, semantic search, retrieval-augmented generation pipelines, live dashboards, and ML model serving to operate from a single store. The platform delivers ultra-low latency querying and real-time analytics, eliminating the need for separate databases or caching layers. Developers and data engineers can extend functionality with Rust or Python logic, deploy on-premises, hybrid, or cloud, and operate under GitOps/CI-CD patterns with observability built in. With built-in vector indexing (e.g., HNSW), metadata filtering, and powerful query semantics, ZeusDB enables similarity search, hybrid retrieval, filtering, and rapid application iteration. -
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Asimov
Asimov
Asimov is a foundational AI-search and vector-search platform built for developers to upload content sources (documents, logs, files, etc.), auto-chunk and embed them, and expose them via a single API to power semantic search, filtering, and relevance for AI agents or applications. It removes the burden of managing separate vector-databases, embedding pipelines, or re-ranking systems by handling ingestion, metadata parameterization, usage tracking, and retrieval logic within a unified architecture. With support for adding content via a REST API and performing semantic search queries with custom filtering parameters, Asimov enables teams to build “search-across-everything” functionality with minimal infrastructure. It is designed to handle metadata, automatic chunking, embedding, and storage (e.g., into MongoDB) and provides developer-friendly tools, including a dashboard, usage analytics, and seamless integration.Starting Price: $20 per month -
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Queryra
Queryra
Queryra is an AI-powered semantic search plugin for WordPress and WooCommerce. It replaces default keyword matching with intelligent search that understands what customers mean. When someone searches "gift for dad who likes gardening", default WooCommerce search returns 0 results. Queryra finds garden gloves, plant pots, and seed kits — even without exact keyword matches. How it works: Your products are converted into AI embeddings. When customers search, their query is understood semantically and matched by meaning, not just keywords. Key features: - AI semantic search trained on YOUR products, not generic ChatGPT - No OpenAI API key needed — everything included - WooCommerce support: SKU, price, categories, tags, attributes - Smart product boost controls for high-margin items - Live AJAX search with instant suggestions - Auto-sync when products are published - 5-minute setup with guided wizardStarting Price: $9/month -
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Vantage Discovery
Vantage Discovery
Vantage Discovery is a generative AI-powered SaaS platform that enables intelligent search, discovery, and personalized recommendations so retailers can deliver breathtaking user experiences. Harness the power of generative AI to create semantic search, product discovery experiences, and personalized recommendations. Transform your search capabilities from keyword-based to natural language semantic search where your user's meaning, intent, and context are understood and used to deliver exceptional experiences. Create completely new and delightful discovery experiences for your users based on their interests, preferences, intent, and your company's merchandising goals. Deliver the most personalized and targeted results across millions of items in milliseconds utilizing a semantic understanding of the user's query and personal style. Deliver delightful user experiences with powerful features delivered by simple APIs. -
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Cohere
Cohere AI
Cohere is an enterprise AI platform that enables developers and businesses to build powerful language-based applications. Specializing in large language models (LLMs), Cohere provides solutions for text generation, summarization, and semantic search. Their model offerings include the Command family for high-performance language tasks and Aya Expanse for multilingual applications across 23 languages. Focused on security and customization, Cohere allows flexible deployment across major cloud providers, private cloud environments, or on-premises setups to meet diverse enterprise needs. The company collaborates with industry leaders like Oracle and Salesforce to integrate generative AI into business applications, improving automation and customer engagement. Additionally, Cohere For AI, their research lab, advances machine learning through open-source projects and a global research community.Starting Price: Free -
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Actian VectorAI DB
Actian
Actian VectorAI DB is a portable, local-first vector database designed for AI systems that need to run close to their data, including edge, on-premises, and hybrid environments. It enables developers to deploy semantic search, retrieval-augmented generation (RAG), and AI-powered applications without relying on cloud infrastructure, avoiding latency, network dependency, and per-query costs. It provides native vector storage and high-performance similarity search using techniques such as approximate nearest neighbor indexing and algorithms like HNSW, allowing efficient retrieval across large embedding datasets while balancing speed and accuracy. It delivers low-latency search directly on devices ranging from laptops to embedded systems like Raspberry Pi, supporting real-time decision-making and autonomous behaviors without a network round-trip. -
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Embedditor
Embedditor
Improve your embedding metadata and embedding tokens with a user-friendly UI. Seamlessly apply advanced NLP cleansing techniques like TF-IDF, normalize, and enrich your embedding tokens, improving efficiency and accuracy in your LLM-related applications. Optimize the relevance of the content you get back from a vector database, intelligently splitting or merging the content based on its structure and adding void or hidden tokens, making chunks even more semantically coherent. Get full control over your data, effortlessly deploying Embedditor locally on your PC or in your dedicated enterprise cloud or on-premises environment. Applying Embedditor advanced cleansing techniques to filter out embedding irrelevant tokens like stop-words, punctuations, and low-relevant frequent words, you can save up to 40% on the cost of embedding and vector storage while getting better search results. -
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ArangoDB
ArangoDB
Natively store data for graph, document and search needs. Utilize feature-rich access with one query language. Map data natively to the database and access it with the best patterns for the job – traversals, joins, search, ranking, geospatial, aggregations – you name it. Polyglot persistence without the costs. Easily design, scale and adapt your architectures to changing needs and with much less effort. Combine the flexibility of JSON with semantic search and graph technology for next generation feature extraction even for large datasets. -
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3RDi Search
The Digital Group
Welcome to the era of Big Data where data-driven insights have the power to transform your business. You're about to discover the solution: a powerful, innovative and adaptive platform power packed with every feature you need for Search, Discovery & Analytics of your data. We have named it 3RDi "Third Eye". It's the semantic search engine your enterprise needs to help you take action, boost revenues and cut costs! Powered by NLP and semantic search, it is designed for multidimensional information analysis and easy search relevancy management. Discover the comprehensive scalable platform for every challenge in search & text mining, from management and exploitation of unstructured content to deriving deeper actionable insights that boost your business. 3RDi isn't merely a search solution. It is a comprehensive stack of solutions for text mining, enterprise search, content integration, governance, analytics and much more. -
21
Klevu
Klevu
Klevu is an intelligent site search solution designed to help e-commerce businesses increase onsite sales and improve the customer online shopping experience. Klevu powers the search and navigation experience of thousands of mid-level and enterprise online retailers by leveraging advanced semantic search, natural language processing, merchandising and multi-lingual capabilities, ensuring visitors to your site find exactly what they are looking for regardless of the device or query complexity. Klevu AI is the most human-centric based AI, designed specifically for ecommerce, and one of the most comprehensive, included in Gartner’s Market Guide 2021 for Digital commerce search. Deliver relevant search results to your customers with Klevu’s powerful and customizable search engine built exclusively for ecommerce.Starting Price: $449 per month -
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Inbenta Search
Inbenta
Deliver more accurate results through Inbenta Semantic Search Engine’s ability to understand the meaning of customer queries. While the search engine is the most widespread self-service tool on web pages with 85% of sites having one, the ability to serve up the most relevant information could be the difference between a good or poor onsite customer experience. Inbenta Search pulls data from across your customer relationship tools, such as Salesforce.com and Zendesk, as well as other designated websites. The Inbenta Symbolic AI and Natural Language Processing technology enable the semantic Inbenta Search to understand customers’ questions, quickly deliver the most relevant answers, and reduce on your support costs. Using Inbenta Symbolic AI technology also means that there is no need for lengthy data training, which allows you to quickly and easily deploy and benefit from the Inbenta Search engine tool. -
23
deepset
deepset
Build a natural language interface for your data. NLP is at the core of modern enterprise data processing. We provide developers with the right tools to build production-ready NLP systems quickly and efficiently. Our open-source framework for scalable, API-driven NLP application architectures. We believe in sharing. Our software is open source. We value our community, and we make modern NLP easily accessible, practical, and scalable. Natural language processing (NLP) is a branch of AI that enables machines to process and interpret human language. In general, by implementing NLP, companies can leverage human language to interact with computers and data. Areas of NLP include semantic search, question answering (QA), conversational AI (chatbots), semantic search, text summarization, question generation, text generation, machine translation, text mining, speech recognition, to name a few use cases. -
24
Dgraph
Hypermode
Dgraph is an open source, low-latency, high throughput, native and distributed graph database. Designed to easily scale to meet the needs of small startups as well as large companies with massive amounts of data, DGraph can handle terabytes of structured data running on commodity hardware with low latency for real time user queries. It addresses business needs and uses cases involving diverse social and knowledge graphs, real-time recommendation engines, semantic search, pattern matching and fraud detection, serving relationship data, and serving web apps. -
25
Microsoft Purview
Microsoft
Microsoft Purview is a unified data governance service that helps you manage and govern your on-premises, multicloud, and software-as-a-service (SaaS) data. Easily create a holistic, up-to-date map of your data landscape with automated data discovery, sensitive data classification, and end-to-end data lineage. Empower data consumers to find valuable, trustworthy data. Automated data discovery, lineage identification, and data classification across on-premises, multicloud, and SaaS sources. Unified map of your data assets and their relationships for more effective governance. Semantic search enables data discovery using business or technical terms. Insight into the location and movement of sensitive data across your hybrid data landscape. Establish the foundation for effective data usage and governance with Purview Data Map. Automate and manage metadata from hybrid sources. Classify data using built-in and custom classifiers and Microsoft Information Protection sensitivity labels.Starting Price: $0.342 -
26
Marqo
Marqo
Marqo is more than a vector database, it's an end-to-end vector search engine. Vector generation, storage, and retrieval are handled out of the box through a single API. No need to bring your own embeddings. Accelerate your development cycle with Marqo. Index documents and begin searching in just a few lines of code. Create multimodal indexes and search combinations of images and text with ease. Choose from a range of open source models or bring your own. Build interesting and complex queries with ease. With Marqo you can compose queries with multiple weighted components. With Marqo, input pre-processing, machine learning inference, and storage are all included out of the box. Run Marqo in a Docker image on your laptop or scale it up to dozens of GPU inference nodes in the cloud. Marqo can be scaled to provide low-latency searches against multi-terabyte indexes. Marqo helps you configure deep-learning models like CLIP to pull semantic meaning from images.Starting Price: $86.58 per month -
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GraphDB
Ontotext
*GraphDB allows you to link diverse data, index it for semantic search and enrich it via text analysis to build big knowledge graphs.* GraphDB is a highly efficient and robust graph database with RDF and SPARQL support. The GraphDB database supports a highly available replication cluster, which has been proven in a number of enterprise use cases that required resilience in data loading and query answering. If you need a quick overview of GraphDB or a download link to its latest releases, please visit the GraphDB product section. GraphDB uses RDF4J as a library, utilizing its APIs for storage and querying, as well as the support for a wide variety of query languages (e.g., SPARQL and SeRQL) and RDF syntaxes (e.g., RDF/XML, N3, Turtle). -
28
Site Search 360
Zoovu (Germany) (formerly SEMKNOX)
Site Search 360 is a smart, ad-free search bar for your website. With a simple drag-and-drop integration, get your search up and running in no time! Let your visitors find exactly what they are looking for, right away. Features of Site Search 360 include: - Quick and easy visual configuration - Autocomplete and search suggestions - Low-to-no-code Search Designer for a customized search UX/UI - Faceted search results (filters) - Semantic search: built-in dictionaries in 19 languages + the ability to add your custom synonyms - In-depth Analytics to help you get the most out of your search: what your visitors look for the most, what results they click on, what queries bring no results, etc. - Full control over search results: boost, reorder, redirect them in no time with our low-to-no-code Result Manager - Integration with Google Analytics and Google Tag Manager - Import of Google Custom Search promotions - Awesome support: via live chat, email, or phoneStarting Price: $9.00/month -
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Cloudflare Vectorize
Cloudflare
Begin building for free in minutes. Vectorize enables fast & cost-effective vector storage to power your search & AI Retrieval Augmented Generation (RAG) applications. Avoid tool sprawl & reduce total cost of ownership, Vectorize seamlessly integrates with Cloudflare’s AI developer platform and AI gateway for centralized development, monitoring & control of AI applications on a global scale. Vectorize is a globally distributed vector database that enables you to build full-stack, AI-powered applications with Cloudflare Workers AI. Vectorize makes querying embeddings, representations of values or objects like text, images, and audio that are designed to be consumed by machine learning models and semantic search algorithms, faster, easier, and more affordable. Search, similarity, recommendation, classification & anomaly detection based on your own data. Improved results & faster search. String, number & boolean types are supported. -
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Parallel
Parallel
The Parallel Search API is a web-search tool engineered specifically for AI agents, designed from the ground up to provide the most information-dense, token-efficient context for large-language models and automated workflows. Unlike traditional search engines optimized for human browsing, this API supports declarative semantic objectives, allowing agents to specify what they want rather than merely keywords. It returns ranked URLs and compressed excerpts tailored for model context windows, enabling higher accuracy, fewer search steps, and lower token cost per result. Its infrastructure includes a proprietary crawler, live-index updates, freshness policies, domain-filtering controls, and SOC 2 Type 2 security compliance. The API is built to fit seamlessly within agent workflows: developers can control parameters like maximum characters per result, select custom processors, adjust output size, and orchestrate retrieval directly into AI reasoning pipelines.Starting Price: $5 per 1,000 requests -
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Mixedbread
Mixedbread
Mixedbread is a fully-managed AI search engine that allows users to build production-ready AI search and Retrieval-Augmented Generation (RAG) applications. It offers a complete AI search stack, including vector stores, embedding and reranking models, and document parsing. Users can transform raw data into intelligent search experiences that power AI agents, chatbots, and knowledge systems without the complexity. It integrates with tools like Google Drive, SharePoint, Notion, and Slack. Its vector stores enable users to build production search engines in minutes, supporting over 100 languages. Mixedbread's embedding and reranking models have achieved over 50 million downloads and outperform OpenAI in semantic search and RAG tasks while remaining open-source and cost-effective. The document parser extracts text, tables, and layouts from PDFs, images, and complex documents, providing clean, AI-ready content without manual preprocessing. -
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Hulbee Enterprise Search
Hulbee
Security plays a very important role for us, that is why we make the most secure provision in the distribution of rights: Active Directory settings. This ensures 100% that the files are only displayed to the assigned person. Many companies want their own and innovative search for the website or intranet. Through the Hulbee Enterprise Search software, you get a semantic search of the information with a high-quality results relevance. You also have the option to customize your search using API and SDK. Many companies are technically very creative and want to adapt our Hulbee Enterprise Search to their own needs. We will be pleased to provide you this opportunity! Like a lego system, you can customize and extend our software to your IT needs. No matter whether Internet or Intranet, everything can be linked by API and expanded by SDK! You can also connect your own development environment to our search, so you remain independent from third parties. -
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VectorDB
VectorDB
VectorDB is a lightweight Python package for storing and retrieving text using chunking, embedding, and vector search techniques. It provides an easy-to-use interface for saving, searching, and managing textual data with associated metadata and is designed for use cases where low latency is essential. Vector search and embeddings are essential when working with large language models because they enable efficient and accurate retrieval of relevant information from massive datasets. By converting text into high-dimensional vectors, these techniques allow for quick comparisons and searches, even when dealing with millions of documents. This makes it possible to find the most relevant results in a fraction of the time it would take using traditional text-based search methods. Additionally, embeddings capture the semantic meaning of the text, which helps improve the quality of the search results and enables more advanced natural language processing tasks.Starting Price: Free -
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Amazon S3 Vectors
Amazon
Amazon S3 Vectors is the first cloud object store with native support for storing and querying vector embeddings at scale, delivering purpose-built, cost-optimized vector storage for semantic search, AI agents, retrieval-augmented generation, and similarity-search applications. It introduces a new “vector bucket” type in S3, where users can organize vectors into “vector indexes,” store high-dimensional embeddings (representing text, images, audio, or other unstructured data), and run similarity queries via dedicated APIs, all without provisioning infrastructure. Each vector may carry metadata (e.g., tags, timestamps, categories), enabling filtered queries by attributes. S3 Vectors offers massive scale; now generally available, it supports up to 2 billion vectors per index and up to 10,000 vector indexes per bucket, with elastic, durable storage and server-side encryption (SSE-S3 or optionally KMS). -
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NeuraVid
NeuraVid
NeuraVid is an AI-powered video analysis platform designed to transform video content into actionable insights. It offers advanced transcription services with industry-leading accuracy, converting speech to text while identifying multiple speakers and providing word-level timestamps. It supports over 40 languages, ensuring accessibility for a global audience. NeuraVid's AI-powered semantic search enables users to find specific moments within videos instantly, looking beyond exact matches to locate contextually relevant content. Additionally, it automatically generates smart chapters and concise summaries, facilitating effortless navigation through lengthy videos. NeuraVid also features an AI video assistant that allows users to interact with their videos, obtaining insights, summaries, and answers to questions about the content in real time.Starting Price: $19 per month -
36
Databricks
Databricks
The Databricks Data Intelligence Platform allows your entire organization to use data and AI. It’s built on a lakehouse to provide an open, unified foundation for all data and governance, and is powered by a Data Intelligence Engine that understands the uniqueness of your data. The winners in every industry will be data and AI companies. From ETL to data warehousing to generative AI, Databricks helps you simplify and accelerate your data and AI goals. Databricks combines generative AI with the unification benefits of a lakehouse to power a Data Intelligence Engine that understands the unique semantics of your data. This allows the Databricks Platform to automatically optimize performance and manage infrastructure in ways unique to your business. The Data Intelligence Engine understands your organization’s language, so search and discovery of new data is as easy as asking a question like you would to a coworker. -
37
Embeddinghub
Featureform
Operationalize your embeddings with one simple tool. Experience a comprehensive database designed to provide embedding functionality that, until now, required multiple platforms. Elevate your machine learning quickly and painlessly through Embeddinghub. Embeddings are dense, numerical representations of real-world objects and relationships, expressed as vectors. They are often created by first defining a supervised machine learning problem, known as a "surrogate problem." Embeddings intend to capture the semantics of the inputs they were derived from, subsequently getting shared and reused for improved learning across machine learning models. Embeddinghub lets you achieve this in a streamlined, intuitive way.Starting Price: Free -
38
Infinia ML
Infinia ML
Document processing is complicated, but it doesn’t have to be. Introducing an intelligent document processing platform that understands what you’re trying to find, extract, categorize, and format. Infinia ML uses machine learning to quickly grasp content in context, understanding not just words and charts, but the relationships between them. Whether your goal is process automation, predictive insights, relationship understanding, or a semantic search engine, we can build it with our end-to-end machine learning capabilities. Use machine learning to make better business decisions. We customize your code to address your specific business challenge, surfacing untapped opportunities, revealing hidden insights, and generating accurate predictions to help you zero in on success. Our intelligent document processing solutions aren’t magic. They’re based on advanced technology and decades of applied experience. -
39
Repustate
Repustate
Repustate provides world-class AI-powered semantic search, sentiment analysis and text analytics for organizations globally. It gives businesses the capability to decode terabytes of information and discover valuable, actionable, business insights more astutely than ever. From our esteemed clients in the Healthcare industry, to recognised leaders in Education, Banking or Governance, Repustate provides continuous deep dives into complex integrated data across industries. Our solution drives sentiment analysis and text analytics for social media listening, Voice of Customer (VOC), and video content analysis (VCA) across platforms. It encompasses the plethora of slangs, emojis and acronyms superseding the rules of formal language in social media. Whether it’s data from Youtube, IGTV, Facebook, Twitter or TikTok, or your own customer review forums, employee surveys, or EHRs, you can identify the critical aspects of your business precisely.Starting Price: $299 per month -
40
Milvus
Zilliz
Vector database built for scalable similarity search. Open-source, highly scalable, and blazing fast. Store, index, and manage massive embedding vectors generated by deep neural networks and other machine learning (ML) models. With Milvus vector database, you can create a large-scale similarity search service in less than a minute. Simple and intuitive SDKs are also available for a variety of different languages. Milvus is hardware efficient and provides advanced indexing algorithms, achieving a 10x performance boost in retrieval speed. Milvus vector database has been battle-tested by over a thousand enterprise users in a variety of use cases. With extensive isolation of individual system components, Milvus is highly resilient and reliable. The distributed and high-throughput nature of Milvus makes it a natural fit for serving large-scale vector data. Milvus vector database adopts a systemic approach to cloud-nativity, separating compute from storage.Starting Price: Free -
41
JAQI
Metal Networks.AI
Copy and paste queries or type right into our search box and our AI technology takes care of the rest. Increases efficiency by 50-80% with accurate search results. JAQI® makes life easier by translating the way a buyer describes products into searchable terms. Your ecommerce customers or sales reps no longer need to do the "matching" to your catalog. Our search technology supports industrial materials with flexible customization options. Say goodbye to searching one line item at a time using inefficient drop-down menus or filters. Search 10, 20, or even 100+ line items simultaneously and add to your quote in seconds. JAQI API plug-in easily integrates into ecommerce applications such as websites & ERP systems to power fast and accurate search results for your customers. Our technology makes it faster & easier than ever before to find any product in any catalog in any format. JAQI powers your ecommerce website or ERP with AI search technology. -
42
LanceDB
LanceDB
LanceDB is a developer-friendly, open source database for AI. From hyperscalable vector search and advanced retrieval for RAG to streaming training data and interactive exploration of large-scale AI datasets, LanceDB is the best foundation for your AI application. Installs in seconds and fits seamlessly into your existing data and AI toolchain. An embedded database (think SQLite or DuckDB) with native object storage integration, LanceDB can be deployed anywhere and easily scales to zero when not in use. From rapid prototyping to hyper-scale production, LanceDB delivers blazing-fast performance for search, analytics, and training for multimodal AI data. Leading AI companies have indexed billions of vectors and petabytes of text, images, and videos, at a fraction of the cost of other vector databases. More than just embedding. Filter, select, and stream training data directly from object storage to keep GPU utilization high.Starting Price: $16.03 per month -
43
Vectorize
Vectorize
Vectorize is a platform designed to transform unstructured data into optimized vector search indexes, facilitating retrieval-augmented generation pipelines. It enables users to import documents or connect to external knowledge management systems, allowing Vectorize to extract natural language suitable for LLMs. The platform evaluates multiple chunking and embedding strategies in parallel, providing recommendations or allowing users to choose their preferred methods. Once a vector configuration is selected, Vectorize deploys it into a real-time vector pipeline that automatically updates with any data changes, ensuring accurate search results. The platform offers connectors to various knowledge repositories, collaboration platforms, and CRMs, enabling seamless integration of data into generative AI applications. Additionally, Vectorize supports the creation and updating of vector indexes in preferred vector databases.Starting Price: $0.57 per hour -
44
Oracle Autonomous Database
Oracle
Oracle Autonomous Database is a fully automated cloud database that uses machine learning to automate database tuning, security, backups, updates, and other routine management tasks traditionally performed by DBAs. It supports a wide range of data types and models, including SQL, JSON documents, graph, geospatial, text, and vectors, enabling developers to build applications for any workload without integrating multiple specialty databases. Built-in AI and machine learning capabilities allow for natural language queries, automated data insights, and the development of AI-powered applications. It offers self-service tools for data loading, transformation, analysis, and governance, reducing the need for IT intervention. It provides flexible deployment options, including serverless and dedicated infrastructure on Oracle Cloud Infrastructure (OCI), as well as on-premises with Exadata Cloud@Customer.Starting Price: $123.86 per month -
45
Weaviate
Weaviate
Weaviate is an open-source vector database. It allows you to store data objects and vector embeddings from your favorite ML-models, and scale seamlessly into billions of data objects. Whether you bring your own vectors or use one of the vectorization modules, you can index billions of data objects to search through. Combine multiple search techniques, such as keyword-based and vector search, to provide state-of-the-art search experiences. Improve your search results by piping them through LLM models like GPT-3 to create next-gen search experiences. Beyond search, Weaviate's next-gen vector database can power a wide range of innovative apps. Perform lightning-fast pure vector similarity search over raw vectors or data objects, even with filters. Combine keyword-based search with vector search techniques for state-of-the-art results. Use any generative model in combination with your data, for example to do Q&A over your dataset.Starting Price: Free -
46
Voyage AI
MongoDB
Voyage AI provides best-in-class embedding models and rerankers designed to supercharge search and retrieval for unstructured data. Its technology powers high-quality Retrieval-Augmented Generation (RAG) by improving how relevant context is retrieved before responses are generated. Voyage AI offers general-purpose, domain-specific, and company-specific models to support a wide range of use cases. The models are optimized for accuracy, low latency, and reduced costs through shorter vector dimensions. With long-context support of up to 32K tokens, Voyage AI enables deeper understanding of complex documents. The platform is modular and integrates easily with any vector database or large language model. Voyage AI is trusted by industry leaders to deliver reliable, factual AI outputs at scale. -
47
Vespa
Vespa.ai
Vespa is forBig Data + AI, online. At any scale, with unbeatable performance. To build production-worthy online applications that combine data and AI, you need more than point solutions: You need a platform that integrates data and compute to achieve true scalability and availability - and which does this without limiting your freedom to innovate. Only Vespa does this. Vespa is a fully featured search engine and vector database. It supports vector search (ANN), lexical search, and search in structured data, all in the same query. Users can easily build recommendation applications on Vespa. Integrated machine-learned model inference allows you to apply AI to make sense of your data in real-time. Together with Vespa's proven scaling and high availability, this empowers you to create production-ready search applications at any scale and with any combination of features.Starting Price: Free -
48
SuperDuperDB
SuperDuperDB
Build and manage AI applications easily without needing to move your data to complex pipelines and specialized vector databases. Integrate AI and vector search directly with your database including real-time inference and model training. A single scalable deployment of all your AI models and APIs which is automatically kept up-to-date as new data is processed immediately. No need to introduce an additional database and duplicate your data to use vector search and build on top of it. SuperDuperDB enables vector search in your existing database. Integrate and combine models from Sklearn, PyTorch, and HuggingFace with AI APIs such as OpenAI to build even the most complex AI applications and workflows. Deploy all your AI models to automatically compute outputs (inference) in your datastore in a single environment with simple Python commands. -
49
Objective
Objective
Objective is a multimodal search API that works for you, not the other way around. Objective understands your data & your users, enabling natural and relevant results. Even when your data is inconsistent or incomplete. Objective understands human language, and ‘sees’ inside images. Your web & mobile app search can understand what users mean, and even relate that to the meaning it sees in images. Objective understands the relationships between huge text articles and the parts of content in each, letting you build context-rich text search experiences. Best-in-class search comes from layering all the best search techniques. It’s not about any single approach. It’s about a curated, tight top-to-bottom integration of all the best search & retrieval techniques in the world. Evaluate search results at scale. Anton is your evaluation copilot that can judge search results with near‑human precision, available in an on‑demand API. -
50
Sophi
Sophi
Sophi is an end-to-end agentic commerce platform that guides users from discovery to purchase through real-time, conversational experiences. It replaces keyword-based search with intent-driven dialogue across web and app environments, understanding what customers mean, not just what they type. Instead of making search feel like a task, Sophi helps it feel like a conversation, pinpointing shopper needs in real time like a top salesperson. It reads shopper context and product details to surface relevant options, dynamically reorder results, explain choices, and recommend products across brand-owned websites and mobile apps. Its semantic understanding helps product listing pages become interactive sales conversations, especially for fashion, beauty, home, and large-scale ecommerce catalogs, where choice overload can hurt conversion. Sophi integrates user memory mapping with semantic product understanding to capture intent, behavior, and context.
