Alternatives to Graphwise
Compare Graphwise alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Graphwise in 2026. Compare features, ratings, user reviews, pricing, and more from Graphwise competitors and alternatives in order to make an informed decision for your business.
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Lettria
Lettria
Lettria offers a powerful AI platform known as GraphRAG, designed to enhance the accuracy and reliability of generative AI applications. By combining the strengths of knowledge graphs and vector-based AI models, Lettria ensures that businesses can extract verifiable answers from complex and unstructured data. The platform helps automate tasks like document parsing, data model enrichment, and text classification, making it ideal for industries such as healthcare, finance, and legal. Lettria’s AI solutions prevent hallucinations in AI outputs, ensuring transparency and trust in AI-generated results.Starting Price: €600 per month -
2
Timbr.ai
Timbr.ai
Timbr is the ontology-based semantic layer used by leading enterprises to make faster, better decisions with ontologies that transform structured data into AI-ready knowledge. By unifying enterprise data into a SQL-queryable knowledge graph, Timbr makes relationships, metrics, and context explicit, enabling both humans and AI to reason over data with accuracy and speed. Its open, modular architecture connects directly to existing data sources, virtualizing and governing them without replication. The result is a dynamic, easily accessible model that powers analytics, automation, and LLMs through SQL, APIs, SDKs, and natural language. Timbr lets organizations operationalize AI on their data - securely, transparently, and without dependence on proprietary stacks - maximizing data ROI and enabling teams to focus on solving problems instead of managing complexity.Starting Price: $599/month -
3
FalkorDB
FalkorDB
FalkorDB is an ultra-fast, multi-tenant graph database optimized for GraphRAG, delivering accurate, relevant AI/ML results with reduced hallucinations and enhanced performance. It leverages sparse matrix representations and linear algebra to efficiently handle complex, interconnected data in real-time, resulting in fewer hallucinations and more accurate responses from large language models. FalkorDB supports the OpenCypher query language with proprietary enhancements, enabling expressive and efficient querying of graph data. It offers built-in vector indexing and full-text search capabilities, allowing for complex searches and similarity matching within the same database environment. FalkorDB's architecture includes multi-graph support, enabling multiple isolated graphs within a single instance, ensuring security and performance across tenants. It also provides high availability with live replication, ensuring data is always accessible. -
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Stardog
Stardog Union
With ready access to the richest flexible semantic layer, explainable AI, and reusable data modeling, data engineers and scientists can be 95% more productive — create and expand semantic data models, understand any data interrelationship, and run federated queries to speed time to insight. Stardog offers the most advanced graph data virtualization and high-performance graph database — up to 57x better price/performance — to connect any data lakehouse, warehouse or enterprise data source without moving or copying data. Scale use cases and users at lower infrastructure cost. Stardog’s inference engine intelligently applies expert knowledge dynamically at query time to uncover hidden patterns or unexpected insights in relationships that enable better data-informed decisions and business outcomes.Starting Price: $0 -
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Memgraph
Memgraph
Memgraph is a high-performance, in-memory graph database that powers real-time AI context. It serves as the graph engine for GraphRAG pipelines, AI memory systems, and agentic workflows - delivering sub-millisecond multi-hop traversals with full provenance for any system that needs structured, connected context alongside semantic search. The same architecture that makes Memgraph the context layer for AI also drives real-time graph analytics across fraud detection, network analysis, infrastructure monitoring, and other operational use cases where speed and connectivity matter. -
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TopBraid
TopQuadrant
Graphs are the most flexible formal data structures (making it simple to map other data formats to graphs) that capture explicit relationships between items so that you can easily connect new data items as they are added and traverse the links to understand the connections. The semantics of data are explicit and include formalisms for supporting inferencing and data validation. As a self-descriptive data model, knowledge graphs enable data validation and can offer recommendations for how data may need to be adjusted to meet data model requirements. The meaning of the data is stored alongside the data in the graph, in the form of the ontologies or semantic models. This makes knowledge graphs self-descriptive. Knowledge graphs are able to accommodate diverse data and metadata that adjusts and grows over time, much like living things do. -
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Epsilla
Epsilla
Manages the entire lifecycle of LLM application development, testing, deployment, and operation without the need to piece together multiple systems. Achieving the lowest total cost of ownership (TCO). Featuring the vector database and search engine that outperforms all other leading vendors with 10X lower query latency, 5X higher query throughput, and 3X lower cost. An innovative data and knowledge foundation that efficiently manages large-scale, multi-modality unstructured and structured data. Never have to worry about outdated information. Plug and play with state-of-the-art advanced, modular, agentic RAG and GraphRAG techniques without writing plumbing code. With CI/CD-style evaluations, you can confidently make configuration changes to your AI applications without worrying about regressions. Accelerate your iterations and move to production in days, not months. Fine-grained, role-based, and privilege-based access control.Starting Price: $29 per month -
8
AllegroGraph
Franz Inc.
AllegroGraph is a breakthrough solution that allows infinite data integration through a patented approach unifying all data and siloed knowledge into an Entity-Event Knowledge Graph solution that can support massive big data analytics. AllegroGraph utilizes unique federated sharding capabilities that drive 360-degree insights and enable complex reasoning across a distributed Knowledge Graph. AllegroGraph provides users with an integrated version of Gruff, a unique browser-based graph visualization software tool for exploring and discovering connections within enterprise Knowledge Graphs. Franz’s Knowledge Graph Solution includes both technology and services for building industrial strength Entity-Event Knowledge Graphs based on best-of-class tools, products, knowledge, skills and experience. -
9
Cube
Cube Dev
Cube is a platform that provides a universal semantic layer to simplify and unify enterprise data management and analytics. By transforming how data is managed, Cube eliminates the need for inconsistent models and metrics, delivering trusted data to users while making it AI-ready. This platform helps organizations scale their data infrastructure by integrating disparate data sources and creating consistent metrics that can be used across teams. Cube is designed for enterprises looking to enhance their analytics capabilities, make their data accessible, and power AI-driven insights with ease. -
10
GoodData
GoodData
Launch embeddable dashboards, charts, and graphs in unmatched time to market. With GoodData’s self-service analytics user interface, business users can build their own dashboards and visualizations to retrieve the insights they need. Don't pay per user when scaling your business. Plus, as your organization grows in data volume, so will your analytics — without impacting performance. GoodData lays the foundation for flexible data connection and transformation. Advanced data modeling and semantics ensure integrity and accuracy for every metric. Our platform is secure at every level, from multi-tenant architecture to regulatory compliance. Avoid common misconceptions about building a SaaS product with embedded analytics. Read about analytics integration into applications and the must-have features. -
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Actian Data Intelligence Platform is a cloud-native, AI-ready solution designed to transform how organizations discover, understand, govern, and trust their data across complex environments. It unifies capabilities such as data cataloging, metadata management, data governance, lineage, observability, and semantic context into a single platform, creating a central, trusted layer for enterprise data. Powered by a federated knowledge graph, it builds intelligent relationships between data assets, enabling the system to automatically understand context, deliver relevant search results, and provide recommendations for data use. This approach allows both technical and business users to easily find and work with trusted data, improving decision-making and operational efficiency. It continuously monitors data health, enforces governance policies, and generates automated trust signals, ensuring data remains accurate, compliant, and ready for analytics and AI applications.
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PoolParty
Semantic Web Company
Integrate an award-winning Semantic AI platform to build smart applications and systems. Use PoolParty to automate metadata creation and make information readily available to be used, shared and analyzed. PoolParty links unstructured and structured data, and connects data which is scattered across databases. Benefit from the next generation of graph-based data and content analytics with state-of-the-art machine learning techniques. Benefit from your data. PoolParty increases the quality of data, which leads to more precise results from AI applications and improved decision-making. Understand why the world’s biggest companies are using Knowledge Graphs, and why yours should be too. Engage with experts, partners, and customers’ presentations to unlock the full potential of semantic technologies and 360-degree views. We have helped over 180 enterprise-level customers master the challenges of information management. -
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Baidu Natural Language Processing, based on Baidu’s immense data accumulation, is devoted to developing cutting-edge natural language processing and knowledge graph technologies. Natural Language Processing has open several core abilities and solutions, including more than ten kinds of abilities such as sentiment analysis, address recognition, and customer comments analysis. Based on word segmentation, part-of-speech tagging, and named entity recognition technology, lexical analysis allows you to locate basic language elements, get rid of ambiguity, and support accurate understanding. Based on deep neural networks and massive high-quality data on the internet, semantic similarity is possible to calculate the similarity of two words through vectorization of words, meeting the business scenario requirements for high precision. Word vector representation can calculate texts through the vectorization of words and it can help you quickly complete semantic mining.
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Synaptica Graphite
Synaptica
Synaptica’s Graphite is a powerful tool for quickly designing, building, and managing Knowledge Organization Systems (KOS) using an intuitive graphical user interface. Graphite is based on Linked Data and Semantic Web standards and utilizes native RDF concept modeling. Powered by a graph database, Graphite offers speed and flexibility in the creation and management of various types of controlled vocabularies including taxonomies and ontologies. Quickly design, build, and manage enterprise Knowledge Organization Systems using an intuitive drag-and-drop graphical user interface and workflow. Centralize metadata KOS for rapid delivery to siloed information systems. Reuse schema templates to build standards-compliant KOS and EKGs in minutes. Reduce project costs and fast-track deliverables with libraries of public domain vocabularies. -
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RDFox
Oxford Semantic Technologies
The world's most performant knowledge graph and semantic reasoning engine. Founded by three professors at the University of Oxford, Oxford Semantic Technologies emerged as a result of extensive research into Knowledge Representation and Reasoning (KRR), out of which came the most powerful knowledge graph and semantic reasoning engine on the market today, RDFox. As an AI reasoning engine, RDFox mirrors human reasoning principles. With unrivaled reasoning capabilities, relying on accuracy, truth, and explainability, it empowers the next generation of AI applications. By inferring new knowledge exclusively from factual data, RDFox ensures results are firmly grounded in reality. RDFox’s incremental reasoning capabilities cause the consequences of the rules-based AI to be applied to the database in real-time as data is added, changed, or removed, all without needing a restart. Only the relevant information is updated without needing to reanalyze the entire data set.Starting Price: Free -
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eccenca Corporate Memory
eccenca
eccenca Corporate Memory provides a multi-disciplinary integrative platform for managing rules, constraints, capabilities, configurations, and data in a single application. Overcoming the limitations of traditional, application-centric (meta) data management models, its semantic knowledge graph is both highly extensible, integrative as well as interpretable both by machines and business users. The enterprise knowledge graph platform re-establishes global data transparency in enterprises as well as line-of-business ownership in a complex and dynamic data environment. It enables you to drive agility, autonomy, and automation without disrupting existing IT infrastructures. Corporate Memory integrates and links data from any source in a central knowledge graph. Use user-friendly SPARQL and JSON-LD frames to explore your global data landscape. The data management in the enterprise knowledge graph platform is implemented by HTTP identifiers and metadata. -
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Databao
JetBrains
Databao is an AI-powered agentic analytics platform designed to help organizations connect databases, BI tools, documents, and spreadsheets into a governed semantic layer that enables reliable natural language querying and analytics. The platform allows technical and business users to ask questions in plain language and receive accurate, reproducible answers without relying on manual dashboard creation, SQL writing, or ad-hoc analytics requests. Databao includes open-source tools such as Context Engine, Data Agent, and an Analytics CLI that work together to generate semantic context from enterprise data sources, automate SQL generation, query multiple datasets, clean and visualize data, and orchestrate conversational analytics workflows. The platform supports local deployment within an organization’s environment and integrates with large language models to reduce SQL hallucinations, improve query accuracy, and streamline data workflows.Starting Price: Free -
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GraphBase
FactNexus
GraphBase is a Graph Database Management System (Graph DBMS) engineered to simplify the creation and maintenance of complex data graphs. Complex and highly-connected structures are a challenge for the Relational Database Management System (RDBMS). A graph database provides much better modelling utility, performance and scalability. The current crop of graph database products - the triplestores and property graphs - have been around for nearly two decades. They're powerful tools, they have many uses, but they're still not suited to the management of complex data structures. With GraphBase, our goal was to simplify the management of complex data structures, so that your data could become something more. It could become Knowledge. We achieved this by redefining how graph data should be managed. In GraphBase, the graph is a first-class citizen. You get a graph equivalent of the "rows and tables" paradigm that makes a Relational Database so easy to use. -
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Microsoft Discovery
Microsoft
Microsoft Discovery is a new agentic platform designed to revolutionize research and development (R&D) by empowering scientists and engineers with AI-driven collaboration and high-performance computing (HPC). Built on Azure, this platform enables researchers to work alongside specialized AI agents that help accelerate the discovery process through advanced knowledge reasoning, hypothesis formulation, and experimental simulations. The platform's graph-based knowledge engine facilitates complex, contextual reasoning over vast amounts of scientific data, promoting transparency and accountability while speeding up the discovery cycle. By automating and enhancing research tasks, Microsoft Discovery offers an extensible, enterprise-ready solution that integrates seamlessly with existing tools and datasets. -
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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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Codd AI
Codd AI
Codd AI solves one of the biggest problems in analytics: making data truly business-ready. Instead of teams spending weeks manually mapping schemas, building models, and defining metrics, Codd uses generative AI to automatically create a context-aware semantic layer that aligns technical data with your business language. That means business users can ask questions in plain English and get accurate, governed answers instantly—through BI tools, conversational AI, or any endpoint. With governance and auditability built in, Codd makes analytics faster, clearer, and more trustworthy. Codd AI ingests both technical metadata from your database, as well as business rules and logic to use AI to auto-generate the most comprehensive semantic layer. This semantic layer is embedded in an intelligent query agent to power natural language (NLP) conversational analytics or power traditional BI toolsStarting Price: $25k per year -
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TextQL
TextQL
The platform indexes BI tools and semantic layers, documents data in dbt, and uses OpenAI and language models to provide self-serve power analytics. With TextQL, non-technical users can easily and quickly work with data by asking questions in their work context (Slack/Teams/email) and getting automated answers quickly and safely. The platform also leverages NLP and semantic layers, including the dbt Labs semantic layer, to ensure reasonable solutions. TextQL's elegant handoffs to human analysts, when required, dramatically simplify the whole question-to-answer process with AI. At TextQL, our mission is to empower business teams to access the data that they're looking for in less than a minute. To accomplish this, we help data teams surface and create documentation for their data so that business teams can trust that their reports are up to date. -
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←INTELLI•GRAPHS→
←INTELLI•GRAPHS→
←INTELLI•GRAPHS→ is a semantic wiki designed to unify disparate data into interconnected knowledge graphs that humans, AI assistants, and autonomous agents can co-edit and act upon in real time; it functions as a personal information manager, family tree/genealogy system, project management hub, digital publishing platform, CRM, document management system, GIS, biomedical/research database, electronic health record layer, digital twin engine, and e-governance tracker, all built on a next-gen progressive web app that is offline-first, peer-to-peer, and zero-knowledge end-to-end encrypted with locally generated keys. Users get live, conflict-free collaboration, schema library with validation, full import/export of encrypted graph files (including attachments), and AI/agent readiness via APIs and tooling like IntelliAgents, which provide identity, task orchestration, workflow planning with human-in-the-loop breakpoints, adaptive inference meshes, and continuous memory enhancement.Starting Price: Free -
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Cohere
Cohere
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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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). -
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Knowledge Catalog is an AI-powered data catalog from Google Cloud that helps organizations manage and understand their entire data ecosystem. It automatically extracts semantics from both structured and unstructured data to build a dynamic context graph. This enables better data discovery, governance, and context-aware insights across the enterprise. The platform helps reduce AI hallucinations by grounding models in accurate, enterprise-specific data. It provides tools for tracking data lineage, profiling data, and measuring data quality. Users can also create business glossaries and enrich metadata to improve data usability. Knowledge Catalog integrates with various Google Cloud services and supports both analytics and AI-driven workflows. Overall, it enhances data visibility, governance, and trust across organizations.Starting Price: $0.060 per hour
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Kyvos Semantic Layer
Kyvos Insights
Kyvos is a semantic layer for AI and BI. It gives organizations a single, consistent, business-friendly view of their entire data estate. By standardizing how data is defined and understood, Kyvos eliminates metric drift across BI tools and ensures that LLMs and AI agents work with governed business semantics rather than raw tables. Kyvos also delivers lightning-fast analytics at massive scale and high concurrency — including granular multidimensional analysis on the cloud — without the sluggish query times and escalating cloud costs that typically come with it. Kyvos semantic layer provides a unified semantic foundation for AI and BI, standardizing metrics, KPIs, and business logic across tools. It grounds AI in governed business context, eliminates metric drift, and delivers sub-second analytics at scale with high concurrency. It also enables deep multidimensional analysis and reduces cloud costs by serving analytics through its semantic layer. -
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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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RAAPID
RAAPID INC
Over 15+ years, we have been the pioneers in building successful clinical NLP platforms & their applications that delivers high accuracy and precision rates. Our core capability is to interpret unstructured notes, accurately and at scale. Tried & tested on billions of diverse and real clinical notes & documents. Explainable AI with reasoning, context & evidence for output. Medical knowledge infused NLP with 4M+ entities & 50M+ relationships. Built using innovative Machine Learning (ML) & Deep Learning (DL) models. Leverage a foundation of rich ontologies & clinician-specific terminologies. We have the ability to understand, interpret and extract context & meaning from the messy, inconsistent, non-standardized data within medical documents. Our Clinical domain experts continuously infuse knowledge graphs into our NLP by mapping all the clinical entities and the relationship between them. So far, we have more than 4 million entities and 50 million relationships. -
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Dremio
Dremio
Dremio delivers lightning-fast queries and a self-service semantic layer directly on your data lake storage. No moving data to proprietary data warehouses, no cubes, no aggregation tables or extracts. Just flexibility and control for data architects, and self-service for data consumers. Dremio technologies like Data Reflections, Columnar Cloud Cache (C3) and Predictive Pipelining work alongside Apache Arrow to make queries on your data lake storage very, very fast. An abstraction layer enables IT to apply security and business meaning, while enabling analysts and data scientists to explore data and derive new virtual datasets. Dremio’s semantic layer is an integrated, searchable catalog that indexes all of your metadata, so business users can easily make sense of your data. Virtual datasets and spaces make up the semantic layer, and are all indexed and searchable. -
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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. -
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HyperGraphDB
Kobrix Software
HyperGraphDB is a general purpose, open-source data storage mechanism based on a powerful knowledge management formalism known as directed hypergraphs. While a persistent memory model designed mostly for knowledge management, AI and semantic web projects, it can also be used as an embedded object-oriented database for Java projects of all sizes. Or a graph database, or a (non-SQL) relational database. HyperGraphDB is a storage framework based on generalized hypergraphs as its underlying data model. The unit of storage is a tuple made up of 0 or more other tuples. Each such tuple is called an atom. One could think of the data model as relational where higher-order, n-ary relationships are allowed or as graph-oriented where edges can point to an arbitrary set of nodes and other edges. Each atom has an arbitrary, strongly-typed value associated with it. The type system managing those values is embedded as a hypergraph and customizable from the ground up. -
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DenserAI
DenserAI
DenserAI is an innovative platform that transforms enterprise content into interactive knowledge ecosystems through advanced Retrieval-Augmented Generation (RAG) solutions. Its flagship products, DenserChat and DenserRetriever, enable seamless, context-aware conversations and efficient information retrieval, respectively. DenserChat enhances customer support, data analysis, and problem-solving by maintaining conversational context and providing real-time, intelligent responses. DenserRetriever offers intelligent data indexing and semantic search capabilities, ensuring quick and accurate access to information across extensive knowledge bases. By integrating these tools, DenserAI empowers businesses to boost customer satisfaction, reduce operational costs, and drive lead generation, all through user-friendly AI-powered solutions. -
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Kavida.ai
Kavida.ai
Kavida.ai is an intelligent knowledge-management and workspace platform that uses artificial intelligence to help individuals and teams capture, connect, and contextualize information automatically within a unified notebook interface, eliminating manual tagging, folders, and fragmented documents. It ingests notes, research, documents, links, and conversations, then uses semantic AI to create an interconnected knowledge graph that surfaces related concepts, auto-generates summaries, and suggests relevant insights as users work, reducing cognitive load and making information easier to find and reuse. It supports natural language querying so users can ask questions about their knowledge base and receive concise, AI-generated answers with links back to source context, and it offers tools for outlining, brainstorming, planning, and project tracking that adapt to individual workflows. -
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Iris.ai
Iris.ai
Iris.ai is a world-leading and award-winning AI engine for scientific text understanding. It is a comprehensive platform for all research-related knowledge processing needs. Our Researcher Workspace solution provides smart search and a wide range of smart filters, reading list analysis, auto-generated summaries, autonomous extraction, and systematising of data. Iris.ai allows humans to focus on value creation by saving 75% of a researcher’s time, doing specialised, interdisciplinary field analysis to an above human level of accuracy. Its algorithms for text similarity, tabular data extraction, domain-specific entity representation learning, and entity disambiguation and linking measure up to the best in the world. Its machine builds a comprehensive knowledge graph containing all entities and their linkages to allow humans to learn from it, use it, and give feedback to the system. Applying these features to scientific and technical text is a complicated challenge few others can achieve. -
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Constellation
ShiftinBits Inc
Graph-backed code intelligence for your AI assistant. Constellation turns your codebase into a queryable knowledge graph, giving AI assistants the structural understanding they need to reason about real software — not just the plain text. Why Constellation? Text search tells you where a string appears, *everywhere* that string appears. Constellation tells you the exact location of the symbol in question, what it means, what calls it, and what breaks if you change it. Before your assistant edits a function, it can ask: - Where is this defined, and where is it used across the codebase? - What's the blast radius of this change? - Which modules have circular dependencies or dead code? - How does data flow through the call graph? Answers come from a semantic graph, not a grep loop. One Tool, Countless Capabilities A single `code_intel` tool exposes a rich JavaScript API as a "Code Mode" tool, allowing AI agents to craft complex composite queries.Starting Price: $29.99/month -
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Strategy Mosaic
Strategy Software
Strategy Mosaic is an AI-powered universal semantic data layer and analytics foundation that sits on top of an organization’s existing data systems to unify, govern, and accelerate access to business data for analytics, AI, and reporting without costly restructuring. It creates a single source of truth with consistent business definitions, metrics, and security policies across tools and sources, harmonizing data from hundreds of systems so insights are reliable and comparable everywhere. Built with AI-assisted data modeling (Mosaic Studio), Mosaic automates data preparation, cleansing, enrichment, and modeling, reducing the time and effort needed to build robust data products and semantic models. Its universal connectors let users access governed data via SQL, REST, Python, or through popular BI and productivity tools like Power BI, Tableau, Excel, and Google Sheets, while an in-memory acceleration engine delivers fast query performance across diverse sources. -
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Anzo
Cambridge Semantics
Anzo is a modern data discovery and integration platform that lets anyone find, connect and blend any enterprise data into analytics-ready datasets. Anzo’s unique use of semantics and graph data models makes it practical for the first time for virtually anyone in your organization – from skilled data scientists to novice business users – to drive the data discovery and integration process and build their own analytics-ready datasets. Anzo’s graph data models provide business users with a visual map of enterprise data that is easy to understand and navigate, even when your data is vast, siloed and complex. Semantics add business content to data, allowing users to harmonize data based on shared definitions and build blended, business-ready data on demand. -
39
Boost.space
Boost.space
Boost.space is a no-code agentic database designed to give AI agents and automations the structured business context they need to operate effectively. It centralizes scattered data from CRM, ecommerce, billing, and support systems into a unified Single Source of Truth. The platform enables continuous two-way synchronization across tools, ensuring that information remains accurate and up to date. With built-in AI enrichment, users can classify records, normalize attributes, and generate structured metadata at scale. Boost.space also supports workflow automation through integrations with platforms like Make, Zapier, and n8n. Through its Model Context Protocol (MCP), AI agents can query live data and execute actions across connected systems without relying on static exports. Trusted by thousands of teams globally, Boost.space transforms fragmented datasets into actionable AI-ready infrastructure.Starting Price: $15/month -
40
Graphlit
Graphlit
Whether you're building an AI copilot, or chatbot, or enhancing your existing application with LLMs, Graphlit makes it simple. Built on a serverless, cloud-native platform, Graphlit automates complex data workflows, including data ingestion, knowledge extraction, LLM conversations, semantic search, alerting, and webhook integrations. Using Graphlit's workflow-as-code approach, you can programmatically define each step in the content workflow. From data ingestion through metadata indexing and data preparation; from data sanitization through entity extraction and data enrichment. And finally through integration with your applications with event-based webhooks and API integrations.Starting Price: $49 per month -
41
NudgeBee
NudgeBee
NudgeBee is an AI Agents and Agentic Workflow platform built for SRE, CloudOps, and DevOps teams. It combines pre-built AI Assistants for incident troubleshooting, cloud cost optimization, and Kubernetes operations with a visual no-code Workflow Builder for custom automation. NudgeBee's AI engine auto-investigates alerts using a live semantic Knowledge Graph, grounded in your actual infrastructure topology. It queries data in place from existing tools (Prometheus, Datadog, Grafana, Loki) with zero data ingestion. The Workflow Builder supports 20+ action categories, native AWS/Azure/GCP CLI nodes, A2A and MCP protocol support, and human-in-the-loop approval gates. 49+ integrations. Enterprise-ready with RBAC, audit trails, BYOM (Bring Your Own Model), and self-hosted deployment. SOC-2 Type II and ISO 27001 compliant.Starting Price: $150 per month -
42
Mastech InfoTrellis
Mastech Infotrellis
Mastech InfoTrellis is a specialist in Digital Transformation solutions and enables enterprises to discover business-relevant insights through Enterprise Knowledge Graphs. With tools and techniques like Ontologies, Machine Intelligence, we help enterprises bring data to life and absorb intricate business objects in an easily comprehensible arrangement. -
43
Cognee
Cognee
Cognee is an open source AI memory engine that transforms raw data into structured knowledge graphs, enhancing the accuracy and contextual understanding of AI agents. It supports various data types, including unstructured text, media files, PDFs, and tables, and integrates seamlessly with several data sources. Cognee employs modular ECL pipelines to process and organize data, enabling AI agents to retrieve relevant information efficiently. It is compatible with vector and graph databases and supports LLM frameworks like OpenAI, LlamaIndex, and LangChain. Key features include customizable storage options, RDF-based ontologies for smart data structuring, and the ability to run on-premises, ensuring data privacy and compliance. Cognee's distributed system is scalable, capable of handling large volumes of data, and is designed to reduce AI hallucinations by providing AI agents with a coherent and interconnected data landscape.Starting Price: $25 per month -
44
CData Connect AI
CData
CData’s AI offering is centered on Connect AI and associated AI-driven connectivity capabilities, which provide live, governed access to enterprise data without moving it off source systems. Connect AI is built as a managed Model Context Protocol (MCP) platform that lets AI assistants, agents, copilots, and embedded AI applications directly query over 300 data sources, such as CRM, ERP, databases, APIs, with a full understanding of data semantics and relationships. It enforces source system authentication, respects existing role-based permissions, and ensures that AI actions (reads and writes) follow governance and audit rules. The system supports query pushdown, parallel paging, bulk read/write operations, streaming mode for large datasets, and cross-source reasoning via a unified semantic layer. In addition, CData’s “Talk to your Data” engine integrates with its Virtuality product to allow conversational access to BI insights and reports. -
45
Klee
Klee
Local and secure AI on your desktop, ensuring comprehensive insights with complete data security and privacy. Experience unparalleled efficiency, privacy, and intelligence with our cutting-edge macOS-native app and advanced AI features. RAG can utilize data from a local knowledge base to supplement the large language model (LLM). This means you can keep sensitive data on-premises while leveraging it to enhance the model‘s response capabilities. To implement RAG locally, you first need to segment documents into smaller chunks and then encode these chunks into vectors, storing them in a vector database. These vectorized data will be used for subsequent retrieval processes. When a user query is received, the system retrieves the most relevant chunks from the local knowledge base and inputs these chunks along with the original query into the LLM to generate the final response. We promise lifetime free access for individual users. -
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Aiimi
Aiimi
Aiimi’s Workplace AI platform is an enterprise-scale AI and data management solution that connects all structured and unstructured data across an organization through a single Virtual Data Layer, enabling secure, scalable AI-powered search, analysis, automation, and actionable insights. It uses AI, machine learning, and Retrieval Augmented Generation (RAG) to discover, classify, enrich, and govern data at scale, turning fragmented information into trusted, “AI-ready” datasets that support natural language search, contextual chat and assistant features, advanced Q&A, and visualizations like knowledge graphs and timelines. It automates complex processes such as data governance, compliance monitoring, data quality improvement, DSAR/disclosure handling, and cloud/legacy system migration, while preserving access controls, permissions, and audit trails. -
47
Kater.ai
Kater.ai
Kater is built for data professionals and data inquisitors. All organized data products are immediately usable by anyone who has a data question, without knowing a lick of SQL. Kater aims to bridge the ownership of data across all business domains in your company. Butler securely connects to your data warehouse's metadata and objects to help you code, discover data, and so much more. Optimize your data for AI with automatic intelligent labeling, categorization, and data curation. We help you define your semantic layer, metric layer, and general documentation. Validated answers are stored in the query bank for smarter, more accurate responses. -
48
AnzoGraph DB
Cambridge Semantics
With a huge collection of analytical features, AnzoGraph DB can enhance your analytical framework. Watch this video to learn how AnzoGraph DB is a Massively Parallel Processing (MPP) native graph database that is built for data harmonization and analytics. Horizontally scalable graph database built for online analytics and data harmonization. Take on data harmonization and linked data challenges with AnzoGraph DB, a market-leading analytical graph database. AnzoGraph DB provides industrialized online performance for enterprise-scale graph applications. AnzoGraph DB uses familiar SPARQL*/OWL for semantic graphs but also supports Labeled Property Graphs (LPGs). Access to many analytical, machine learning and data science capabilities help you achieve new insights, delivered at unparalleled speed and scale. Use context and relationships between data as first-class citizens in your analysis. Ultra-fast data loading and analytical queries. -
49
Vertesia
Vertesia
Vertesia is a unified, low-code generative AI platform that enables enterprise teams to rapidly build, deploy, and operate GenAI applications and agents at scale. Designed for both business professionals and IT specialists, Vertesia offers a frictionless development experience, allowing users to go from prototype to production without extensive timelines or heavy infrastructure. It supports multiple generative AI models from leading inference providers, providing flexibility and preventing vendor lock-in. Vertesia's agentic retrieval-augmented generation (RAG) pipeline enhances generative AI accuracy and performance by automating and accelerating content preparation, including intelligent document processing and semantic chunking. With enterprise-grade security, SOC2 compliance, and support for leading cloud infrastructures like AWS, GCP, and Azure, Vertesia ensures secure and scalable deployments. -
50
MetaCenter
Data Advantage Group
MetaCenter enables business and technology teams to catalog and classify an organization's information assets. Users can self-service questions about their data assets and how data flows through the business and classify how it should be used. This enables organizations to lower costs while improving agility and reducing operational risks. Search-based semantic layer automates cross-referencing models. Faceted Views of specific data assets can be published to individual roles. Lower cost of ownership and higher levels of automation deliver superior ROI compared to competing solutions. Simple GUI driven customization enables rapid application customization. No programming or professional services are required.
