Alternatives to Dosi
Compare Dosi alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Dosi in 2026. Compare features, ratings, user reviews, pricing, and more from Dosi competitors and alternatives in order to make an informed decision for your business.
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SCIKIQ
SCIKIQ
SCIKIQ is an AI-native Data & Intelligence Platform designed to help enterprises make their data trusted, governed, connected, and ready for AI in weeks rather than years. Recognized by Forrester, NASSCOM League of 10, YourStory Tech30, Inc42, and DataIQ, SCIKIQ supports enterprises across the USA, India, UK, and UAE. SCIKIQ brings together Data Integration, Data Quality, Data Governance, Metadata Management, Data Lineage, Semantic Intelligence, Knowledge Graphs, Conversational Analytics, Generative AI, Data Products, and AI Agents within one unified platform. Unlike traditional data platforms that often require extensive replatforming or migration, SCIKIQ works with an enterprise’s existing technology ecosystem. Organizations can connect SAP, Salesforce, Oracle, Snowflake, Databricks, AWS, Azure, GCP, data lakes, data warehouses, and enterprise applications through 200+ pre-built connectors, without rip-and-replace. Contextual Intelligence at the Core SCIKIQ goes beyond connecting data by helping AI understand the business context behind it. Its semantic intelligence layer brings together business terminology, KPI definitions, metadata, lineage, ownership, business rules, ontologies, and relationships to create a trusted context layer for enterprise analytics and AI. Business users can ask questions in natural language, investigate KPIs, identify root causes, and generate insights without writing SQL. Data teams gain enterprise-grade capabilities for data integration, quality, governance, lineage, metadata, and control. AI teams gain trusted, contextual enterprise data for building Generative AI applications, copilots, and intelligent AI agents. Why Enterprises Choose SCIKIQ AI-ready in 3–6 weeks | 200+ connectors | 99.9% availability | No-code | Multi-cloud | No vendor lock-in | No replatforming SCIKIQ has production deployments across industries including manufacturing, retail, aviation, logistics, BFSI, healthcare, and other data-intensive enterprises. -
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Denodo
Denodo Technologies
Denodo offers an AI Data Layer that helps organizations deliver live, unified, and governed data for trustworthy AI, analytics, and self-service initiatives. The platform uses logical data management to connect distributed data across hybrid, multi-cloud, on-premises, SaaS, and third-party environments without requiring data movement or duplication. Denodo helps businesses integrate data silos, enable self-service access, enforce governance, deliver real-time insights, and enrich data with business context. It is designed to support agentic AI by giving AI agents accurate, up-to-date, and governed enterprise data for better decisions and actions. The platform includes capabilities such as zero-copy data access, unified semantics, centralized compliance, natural language search, data marketplaces, and optimized query performance. -
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AnalyticsCreator
AnalyticsCreator
AnalyticsCreator is a metadata-driven design application for data warehouse automation and data product engineering across the Microsoft data stack. At its core is the AnalyticsCreator Governed Control Model, which keeps business meaning, data structures, transformation rules, dependencies and technical implementation connected in one controlled project model. Data teams design the required architecture in AnalyticsCreator, then generate native Microsoft assets from that design. Generated assets can include SQL Server objects, SSIS packages, Azure Data Factory pipelines, Microsoft Fabric components, deployment artefacts and Power BI semantic models. AnalyticsCreator supports dimensional, 3NF and hybrid modelling approaches together with ingestion, transformations, delta loading, historisation, Slowly Changing Dimensions, snapshots and repeatable data-processing patterns. Changes made in the model can be propagated across dependent project assets, while lineage, documentation and impact analysis remain connected to the underlying design. This helps teams reduce repetitive engineering work, standardise delivery and understand the effect of change before regenerating affected assets. AnalyticsCreator generates native Microsoft technology rather than requiring a proprietary runtime. Organisations retain ownership of the resulting implementation and can integrate generated assets into existing Git, Azure DevOps and CI/CD processes. Design Intelligence extends this governed project context into AI-assisted data engineering by giving authorised AI tools and agents structured access to metadata, lineage, dependencies and design rules. Typical use cases include enterprise data warehouse development, Microsoft Fabric adoption, SQL Server and SSIS modernisation, governed Power BI delivery, SAP-to-Microsoft analytics architectures and repeatable data product engineering. -
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dbt
dbt Labs
dbt helps data teams transform raw data into trusted, analysis-ready datasets faster. With dbt, data analysts and data engineers can collaborate on version-controlled SQL models, enforce testing and documentation standards, lean on detailed metadata to troubleshoot and optimize pipelines, and deploy transformations reliably at scale. Built on modern software engineering best practices, dbt brings transparency and governance to every step of the data transformation workflow. Thousands of companies, from startups to Fortune 500 enterprises, rely on dbt to improve data quality and trust as well as drive efficiencies and reduce costs as they deliver AI-ready data across their organization. Whether you’re scaling data operations or just getting started, dbt empowers your team to move from raw data to actionable analytics with confidence.Starting Price: $100 per user/ month -
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Cube
Cube Dev
Cube is an AI-powered business intelligence and semantic layer platform that helps organizations access, analyze, and govern business data across applications and AI agents. The software connects to data warehouses, databases, and other data sources to create a centralized semantic model containing standardized metrics, dimensions, relationships, and business definitions. Its AI-powered analytics capabilities allow users to ask questions in natural language, generate reports, build dashboards, and explore data without writing complex SQL queries. Cube provides Model Context Protocol (MCP) integrations that enable AI assistants such as ChatGPT, Claude, and Cursor to retrieve governed business information and perform analytical tasks. Its query acceleration engine uses caching and pre-aggregations to improve analytics performance while maintaining consistent data access controls. -
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Apache Ossie
Apache Software Foundation
Apache Ossie is an open specification and converter toolkit for exchanging semantic metadata across analytics, business intelligence, and AI systems. Its YAML-based format describes semantic models, datasets, fields, metrics, dimensions, relationships, and SQL expressions in a portable structure. Data and analytics engineers can use compatible implementations to author, translate, and reuse these definitions across connected platforms, supporting consistent business context for reporting and AI-assisted analysis. The project is an open-source community effort under the Apache License 2.0, with available conversions depending on each platform’s implementation. -
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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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Colrows
Colrows
Colrows is an autonomous semantic layer engineered to make enterprise AI reliable at production scale. Enterprise AI initiatives stall when models hallucinate and answers lack auditability. Colrows fixes the context, not the model. The platform continuously crawls databases, warehouses, catalogs, and documentation to build a dynamic business graph of entities, metrics, and logic. Sitting between enterprise data and AI surfaces, Colrows compiles natural language into governed, auditable SQL query plans. Every output traces directly to a verified single source of truth. Key capabilities include: AI Data Analyst: Conversational analytics with end-to-end SQL lineage. Semantic API: Standardized semantic infrastructure for internal copilots and agents. Auto-Crawl Engine: Continuous metadata synchronization without manual coding. Colrows delivers the mathematical accuracy and regulatory defensibility that probabilistic RAG cannot match. It is suited for regulated industries.Starting Price: $70/user/month -
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Verdonz
Verdonz
Verdonz is a business intelligence and AI analytics platform for teams investigating performance and business data. It connects to warehouses, databases, query engines, monitoring systems, and knowledge sources, organizing metrics, entities, relationships, and access rules in a shared semantic model. Users ask natural-language questions, inspect metric definitions and SQL behind answers, and explore dashboards, reports, and alerts based on governed metrics. Configurable AI agents investigate connected data and knowledge on demand, on a schedule, or after alerts; external assistants access approved context through the read-only Model Context Protocol (MCP) server or API. Embedded analytics can expose saved queries in other applications. Verdonz is available as hosted SaaS, in a dedicated instance or customer cloud, and as self-hosted software for organizations that need infrastructure control.Starting Price: $199/user/month -
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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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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. -
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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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Beye
Beye
Beye is an AI-native generative business intelligence platform that ingests and auto-cleans raw data from spreadsheets, ERPs, and cloud apps, into unified, AI-optimized dataverses in weeks rather than months. Its generative BI agent auto-builds your first data model and starter dashboards around your specific use case, applying metadata and semantic layers, measure creation, and data preparation without manual effort. Business users, managers, and executives can ask questions in plain English, no SQL or dashboard navigation required, to receive instant, high-fidelity analytics, contextualized insights, and root-cause explanations with traceable queries. It integrates seamlessly with SAP, Snowflake, Salesforce, NetSuite, and over 50 additional sources, supports collaborative channels and custom metrics, and validates answers through AI-driven workflows. -
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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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GoodData.AI
GoodData.AI
GoodData.AI is an AI-ready analytics platform that helps organizations turn data into actionable insights through business intelligence, embedded analytics, and governed semantic modeling. It enables businesses to build dashboards, AI-powered applications, and intelligent workflows using a composable architecture designed for enterprise environments. The platform provides a centralized semantic layer that ensures consistent business logic across reports, analytics, AI agents, and embedded experiences. GoodData supports cloud and on-premises deployments while integrating with modern data ecosystems and enterprise applications. It also includes AI capabilities for conversational analytics, automation, decision support, and custom agent development. With enterprise-grade security, compliance certifications, and extensive developer tools, GoodData is designed to help organizations modernize their analytics infrastructure for the AI era. -
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Kyvos Semantic Layer
Kyvos Insights
Kyvos is a semantic layer for AI and BI. By standardizing how data is defined and understood, Kyvos gives organizations a single, consistent, business-friendly view of their entire data estate. The result: AI agents reason with governed context, BI tools report consistent metrics, and the business gets answers it can trust. Built for enterprise scale, Kyvos provides the speed, scale, and trust that production-grade AI and enterprise BI demand. It also maximizes analytics investments by reducing token consumption and cloud compute costs. -
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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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Brewit
Brewit
Make data-driven decisions 10x faster with self-service analytics. Integrate with your databases and data warehouses all-in-one place (Postgres, MySQL, Snowflake, BigQuery, and more). Brewit can write SQL queries and create recommended charts based on your data questions. It also helps you drill down on the analysis. Chat with your database, visualize insights, & perform analysis. Ensure answer accuracy and consistency with a built-in data catalog. An automated semantic layer that ensures Brewit answers with correct business logic. Easily manage your data catalog & data dictionary. Building a beautiful report is as easy as writing a doc. Data without a story is useless. Our Notion-style notebook editor allows you to create reports & dashboards easily, turning raw data into actionable insights. All organized data products are usable by anyone who has a data question, regardless of their technical skills. -
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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 -
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Datus
DatusAI
Datus is an AI-assisted data engineering and analytics platform that builds a shared business context layer over an organization’s existing data stack. Its Datus Agent can inspect warehouse schemas, SQL, ETL code, and business documents to draft semantic models and connect business concepts, metrics, and source data. Teams review definitions and generated SQL, then use DOSI to validate compatible models and compile queries into native SQL for supported data sources. Datus provides a browser-based Studio, a local command-line agent, and REST, Python SDK, and MCP interfaces for analytics teams, data engineers, and AI agents. Common workflows include data discovery, semantic modeling, governed text-to-SQL, metric queries, SQL development, and production data engineering. It is designed to work with existing warehouses and model providers rather than require a data migration.Starting Price: $0 -
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Graphwise
Graphwise
Graphwise is an AI platform that helps businesses automate knowledge and trust their AI by turning fragmented data into a trusted semantic backbone. The all-in-one suite makes generative AI reliable and scalable by transforming data into AI-ready, context-rich assets, deploying intelligent agent-based systems, and delivering powerful AI applications on an integrated platform. Graphwise moves beyond simple data chunks with Precise GraphRAG, using a governed knowledge graph to ground every response in verified facts, eliminate hallucinations, and provide accurate, actionable answers. It combines automated modeling, high-performance graph technology, semantic search, recommendation, taxonomy and ontology management, data automation, graph-based text mining, and enterprise-ready GraphRAG workflows. It supports use cases such as technical knowledge management, semantic digital twins, compliance intelligence, and scientific knowledge management. -
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AtScale
AtScale
AtScale helps accelerate and simplify business intelligence resulting in faster time-to-insight, better business decisions, and more ROI on your Cloud analytics investment. Eliminate repetitive data engineering tasks like curating, maintaining and delivering data for analysis. Define business definitions in one location to ensure consistent KPI reporting across BI tools. Accelerate time to insight from data while efficiently managing cloud compute costs. Leverage existing data security policies for data analytics no matter where data resides. AtScale’s Insights workbooks and models let you perform Cloud OLAP multidimensional analysis on data sets from multiple providers – with no data prep or data engineering required. We provide built-in easy to use dimensions and measures to help you quickly derive insights that you can use for business decisions. -
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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. -
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Nowl
Gerling Solutions
Nowl is a semantic access layer that makes existing enterprise software and databases queryable for AI in business terms. Instead of giving an AI free SQL access, Nowl translates business questions into validated, read-only query plans and shows how every answer was derived, so results are traceable instead of a black box. A privacy layer filters data before anything is transmitted to a language model. Nowl is self-hosted (except the language model), EU data residency can be selected, and it changes nothing in the existing systems. It connects to assistants such as Claude via MCP. Typical uses: ad-hoc questions from sales, finance, service and management that standard reports do not cover. Built for mid-sized companies with grown software landscapes. Currently in a pilot program. -
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Actian AI Analyst
Actian
Actian AI Analyst is a context-aware conversational analytics platform designed to help organizations get trusted answers from their data using natural language. It enables business users to ask questions directly without writing SQL, transforming traditional dashboards into an interactive, ongoing conversation with data. It operates on a governed semantic layer that models business metrics, relationships, and definitions before analysis begins, ensuring that every query is grounded in how the organization actually works. This semantic layer is automatically generated and maintained by the Steward AI agent, which continuously monitors data definitions and connections, providing reviewable action plans to maintain accuracy over time. AI Analyst preserves conversational context across follow-up questions, allowing deeper exploration while keeping results consistent with defined business logic. -
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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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SAP Business Data Cloud is a fully managed SaaS solution that unifies and governs all SAP data while seamlessly connecting with third-party data, providing line-of-business leaders with the context needed to make impactful decisions. It offers mission-critical data products, granting access to SAP data across essential business processes in a deeply contextual and governed manner, thereby eliminating the high costs associated with data extraction and replication. As a leading data platform, it enables the connection of all SAP and third-party data through a fully managed SaaS solution in collaboration with Databricks. The platform delivers powerful insight applications, facilitating transformational insights for advanced analytics and planning across various lines of business. By harmonizing all mission-critical data within an open data ecosystem and leveraging a robust semantic layer, SAP Business Data Cloud provides unparalleled business understanding.
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SAP Datasphere
SAP
SAP Datasphere is a unified data experience platform within SAP Business Data Cloud, designed to provide seamless, scalable access to mission-critical business data. It integrates data from SAP and non-SAP systems, harmonizing diverse data landscapes and enabling faster, more accurate decision-making. With capabilities like data federation, cataloging, semantic modeling, and real-time data integration, SAP Datasphere ensures that businesses have consistent, contextualized data across hybrid and cloud environments. The platform simplifies data management by preserving business context and logic, providing a comprehensive view of data that drives innovation and enhances business processes. -
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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. -
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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 -
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Amazon Quick Suite
Amazon
Amazon QuickSuite is a unified generative-AI and analytics workspace designed to help business users, analysts, and domain experts turn data, workflows, and internal knowledge into actionable insights and automation. The platform brings together multiple capabilities; interactive dashboards and visualizations (leveraging the existing QuickSight service), natural-language Q&A and generative BI, workflow automation, deep data discovery and research agents, and connector support for enterprise systems and SaaS tools. From a data perspective, QuickSuite enables users to connect multiple data sources, spreadsheets, cloud warehouses, third-party apps, and on-premises systems, and ask questions in plain language, build dashboards, schedule reports, or trigger automations. From a workflow perspective, it allows non-technical roles to automate routine tasks, such as report generation, alerting, or data onboarding, through agent-powered flows. -
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BinarBase
BinarBase
Easily connect financial data, customer data and third-party apps to our unified platform. No complex setup required. Effortless tracking and analyzing all your business data, driving informed decision-making and growth. Our semantic layer infuses meaning into your data, making it readily understandable for business users. We provide you with a comprehensive view of your business performance, enabling you to see areas for improvement and optimize operations. Identify patterns in expenses, revenue streams and cash flow trends to gain a deeper understanding of your financial health. Understand customer behavior, including purchase patterns and payment cycles. Track key metrics to assess your startup's progress and make data-driven adjustments to your strategy. -
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Arize Phoenix
Arize AI
Phoenix is an open-source observability library designed for experimentation, evaluation, and troubleshooting. It allows AI engineers and data scientists to quickly visualize their data, evaluate performance, track down issues, and export data to improve. Phoenix is built by Arize AI, the company behind the industry-leading AI observability platform, and a set of core contributors. Phoenix works with OpenTelemetry and OpenInference instrumentation. The main Phoenix package is arize-phoenix. We offer several helper packages for specific use cases. Our semantic layer is to add LLM telemetry to OpenTelemetry. Automatically instrumenting popular packages. Phoenix's open-source library supports tracing for AI applications, via manual instrumentation or through integrations with LlamaIndex, Langchain, OpenAI, and others. LLM tracing records the paths taken by requests as they propagate through multiple steps or components of an LLM application.Starting Price: Free -
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Textkernel Source & Match
Textkernel
Source & Match automatically matches the best candidates and jobs across internal and external databases. Through our semantic layer and sophisticated data enrichment everyone becomes an expert sourcing specialist. We find what you mean, not just what you type, making it easy to discover the best talent or jobs. Plus, our powerful matching engine, integrated into your ATS, CRM, Internal Mobility or Talent Management platform, automatically transforms a job posting or candidate into a comprehensive search query providing results with a shortlist of promising candidates or jobs. Our matching accuracy is the game-changer as it provides results you can rely on! - Unlock the full value of your talent and jobs database - Automate with confidence - Eliminate bias Source & Match products redefine the hiring process by enhancing efficiency, elevating the candidate experience, and empowering organizations to turn their talent data into a valuable asset. -
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Solid
Solid
Solid is an AI-powered data intelligence platform designed to make enterprise data reliable and ready for use across AI, analytics, and “chat with your data” experiences. It automatically discovers, documents, and builds business-aware semantic models from a company’s existing data, queries, and tools, creating a consistent foundation that AI systems can trust. It analyzes how data is actually used within the organization and generates validated tables, metrics, relationships, and SQL logic aligned with real business definitions. Through products such as Solid Build and Solid Analyze, teams can automate semantic modeling, translate natural-language questions into production-ready SQL, and keep models continuously updated as data changes. It emphasizes transparency and human oversight, allowing data teams to review, edit, and validate AI-generated models rather than relying on opaque automation. -
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SSAS
Microsoft
Installed as an on-premises server instance, SQL Server Analysis Services supports tabular models at all compatibility levels (depending on version), multidimensional models, data mining, and Power Pivot for SharePoint. A typical implementation workflow includes installing a SQL Server Analysis Services instance, creating a tabular or multidimensional data model, deploying the model as a database to a server instance, processing the database to load it with data, and then assigning permissions to allow data access. When ready to go, the data model can be accessed by any client application supporting Analysis Services as a data source. Models are populated with data from external data systems, usually data warehouses hosted on a SQL Server or Oracle relational database engine (Tabular models support additional data source types). -
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BeagleGPT
BeagleGPT
Proactive data and insights nudges for each user according to their usage pattern, automated heuristic rules, data updates, and user-cohort learnings. The semantic layer is finetuned for organizations with their nomenclatures and terminologies. User roles and preferences are considered while building responses for them. Advanced modules to answer how, why and so what scenarios. A single subscription covers the entire organization, truly propelling data democratization. Beagle is built to nudge you and your team toward data-driven decision-making. It is your personal data assistant that delivers all data-related updates and alerts in your message box. With in-built self-service functionalities, Beagle reduces the total cost of ownership by huge margins. Beagle connects with other dashboards to enhance their power and increase their reach in the organization. -
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Flitch
Flitch
Flitch is a cloud business intelligence and application-building platform for teams that want to analyze operational data and create tools around it. Users define data sources, metrics, relationships, permissions and business context, then use those shared definitions to build dashboards, internal apps, written reports, scheduled workflows and an AI chat assistant. The platform connects databases, data warehouses, SaaS services, files and APIs; database and warehouse queries can run in place, while connected SaaS data is refreshed on a schedule. Users can add input tables for business data entry and publish dashboards or apps to a custom domain, embed them, or share them with access controls such as email, passwords and row-level rules. Flitch is intended for organizations seeking self-service analytics and governed data tools, including teams with or without dedicated analysts.Starting Price: $20/user/month -
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DataGalaxy
DataGalaxy
DataGalaxy is a next-generation data governance and intelligence platform designed to help organizations manage, understand, and maximize the value of their data. Built around a unified interface, it empowers everyone—from executives to data consumers—to collaborate seamlessly across data assets, strategies, and analytics. The platform’s automated data catalog, governance hub, and AI co-pilot reduce manual work while ensuring compliance and data quality across systems. With over 70+ integrations, including Snowflake, Databricks, Power BI, and AWS, DataGalaxy connects your data ecosystem into a single source of truth. Its value tracking center and strategy cockpit align data initiatives with business goals, driving measurable outcomes and enterprise-wide visibility. Loved by users, DataGalaxy turns governance into a strategic advantage for the modern enterprise. -
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Microsoft Fabric
Microsoft
Reshape how everyone accesses, manages, and acts on data and insights by connecting every data source and analytics service together—on a single, AI-powered platform. All your data. All your teams. All in one place. Establish an open and lake-centric hub that helps data engineers connect and curate data from different sources—eliminating sprawl and creating custom views for everyone. Accelerate analysis by developing AI models on a single foundation without data movement—reducing the time data scientists need to deliver value. Innovate faster by helping every person in your organization act on insights from within Microsoft 365 apps, such as Microsoft Excel and Microsoft Teams. Responsibly connect people and data using an open and scalable solution that gives data stewards additional control with built-in security, governance, and compliance.Starting Price: $156.334/month/2CU -
41
Compass
Dagster Labs
Compass is an AI-powered, Slack-native data assistant that turns plain English questions into instant answers, summaries, charts, and insights powered by your actual warehouse data, so teams can make data-driven decisions without waiting on BI backlogs or building dashboards first. It connects directly to major data warehouses (Snowflake, BigQuery, Redshift, Postgres, AWS Athena, Databricks, and more), learns your schema and context, and generates governed, SQL-backed responses and visualizations in the tools your team already uses, all while keeping your data where it lives and under your control. Compass builds organizational context over time so answers become more accurate and relevant, supports collaboration through Slack threads, can schedule recurring analysis, and provides a shared repository of definitions and insights that help reduce analytical silos and reliance on specialized SQL users.Starting Price: $49 per month -
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DataAgents
DataAgents
DataAgents is an AI-native business data platform combining data integration, transformation, analytics and autonomous AI agents. The platform ingests data from CRM, ERP, accounting, marketing, e-commerce and analytics systems and transforms it into standardized business models. AI agents operate over this business context to answer natural-language questions, monitor KPIs, detect anomalies, perform automated investigations and generate recommendations. DataAgents can be deployed as SaaS, private cloud/VPC or on-premise depending on customer infrastructure and data-sovereignty requirements. -
43
GoalfyData
GoalfyData
GoalfyData is an AI data platform that helps teams turn business data and agent-generated results into reusable, governed datasets and data applications. It provides AI agents with persistent business context, including field definitions, table relationships, metric logic, processing rules, permissions, and usage guidance. Instead of repeatedly uploading the same files or explaining business definitions in every AI conversation, teams can maintain a shared source of truth that different agents and collaborators can reuse. GoalfyData supports structured dataset management, AI-powered data analysis, data governance, automated reporting, business intelligence, dashboard creation, and recurring data workflows. AI agents can query maintained datasets, generate reports, and build focused data apps while preserving the underlying schema, relationships, calculation rules, and access controls. Managed Refresh can rerun configured update workflows on a schedule, helping datasets, reports.Starting Price: $12/month -
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Athenic AI
Athenic AI
Discover the nuance behind the trends by following a guided journey of data analytics questions to understand what’s truly going on. Empower your stakeholders with self-service data analytics. Give them the ability to access and analyze the data they need, when they need it. Increase efficiency, reduce dependency on IT, and make data-driven decisions faster with a self-service analytics solution. Athenic AI connects to your data stored in a database, data warehouse or an application like a CRM or ERP platform to answer your questions without SQL knowledge or a business analyst. We have built Athenic to be able to interpret natural language and translate into SQL queries. We have even added the option to give the AI additional context in natural language. -
45
Claude Dashboards
Anthropic
Claude Dashboards is a beta feature in Anthropic's Claude web application for creating dashboards from company data using natural-language requests. Users connect a supported data warehouse or another app connected to Claude, ask a question, and Claude writes SQL queries and builds charts in an artifact. Each chart exposes its query and data-refresh time. Users can refine dashboards through chat, adjust views or filters, inspect query logic, save dashboards in the Artifacts tab, and share them. The feature is intended for quick, exploratory analysis, such as comparing signups or revenue across periods, rather than replacing deeper analysis in dedicated tools. It is available on Claude Pro, Max, Team, and Enterprise plans, where its use counts toward plan limits; Enterprise owners must enable it. Individual Claude users and teams analyzing connected business data are its primary audience.Starting Price: $20/month -
46
GetDot.ai
Snowboard Software GmbH
Dot (getdot.ai) is an AI data analyst. People ask in plain English in Slack, Microsoft Teams, the web app, or from AI agents through its MCP server and CLI. Dot finds the right tables, writes and runs SQL on the company's own warehouse, and answers with charts, data and the SQL it ran. Data teams train it with notes, dbt and semantic-layer context and evaluations, and a Context Agent keeps that knowledge current. It also builds data apps and scheduled reports. SOC 2 Type II and GDPR compliant.Starting Price: Free -
47
Spreadsite
Spreadsite
Spreadsite uses Al to transform your data into beautiful, interactive web dashboards, with no coding required. Transform your spreadsheets into custom agent-powered websites with our intuitive workflow. Discover how our agent-powered website generator can transform your spreadsheet data into stunning, interactive web applications at scale. Spreadsite performs optimally with clean, well-structured data. Qualitative data with short entries tends to work particularly well. However, we're continually improving our system to handle various data types. Spreadsite stands out by offering 100% AI-generated, custom-built interfaces for your data. Our tool is designed to create unique visualizations tailored specifically to your dataset, providing an unparalleled level of customization and insight. Transform your spreadsheets into interactive custom websites, built from scratch just for you.Starting Price: $10 per month -
48
ClarityQ
ClarityQ Inc
ClarityQ is an AI data analytics platform for data, product, and business teams. It connects to warehouses such as Snowflake, BigQuery, Redshift, Databricks, PostgreSQL, Athena, and Azure Synapse, where users ask questions in natural language and receive analysis, visualizations, insights, and action plans without remodeling data. Its automatically maintained Context Layer organizes business logic, metric definitions, and table relationships, with changes tracked for review. Answers can show reasoning, generated SQL, and data sources; validation checks results, and follow-up questions clarify ambiguity. Teams create dashboards from prompts, schedule reports to Slack or email, and share results with role-aware access controls. The platform is read-only by default and offers an open API, SOC 2 Type II and GDPR compliance, Private Link, and single-tenant options. Use cases include product, growth, and business analysis for gaming, SaaS, e-commerce, and consumer app companies.Starting Price: $499/month -
49
Mint
DZG Studio LLC
Mint is a macOS storage cleanup and file-organization app for developers, independent professionals and studios working on individual Macs. It maps disk use and presents caches, build output, app leftovers and supported AI-coding workspace data for review before cleanup. Users can preview folder-organization plans, apply selected moves, and run enabled Auto Care routines while Mint is running. For eligible duplicate or supported files, Optimize can reduce storage use while keeping files in place. Mint Direct also provides a command-line interface and Model Context Protocol server for storage queries and supported cleanup from scan plans; these agent tools do not expose every in-app operation. File analysis and organization run locally on the Mac. Available actions, free allowances, recovery and licensing vary by edition and operation. Requires macOS 14 or later.Starting Price: $9.95/month -
50
Span-01
Respan
Span-01 is a hyper-parallel reasoning classifier built to detect complex behaviors across long production traces in a single forward pass. Rather than generating tokens sequentially, it reasons over natural-language behavior definitions and returns direct probabilities for present, absent, and not_observable. The model is trained for general classification reasoning with RLAIF before being specialized for behavior detection, allowing it to apply previously unseen definitions to new behaviors and domains instead of relying on a fixed taxonomy. At inference time, hyper-parallel definition branches evaluate multiple behaviors against the same trace context simultaneously, while hybrid attention helps preserve reasoning over long, complex inputs. Span-01 is designed for production monitoring across safety, reliability, grounding, agent behavior, and response quality, including jailbreak and prompt injection detection, privacy, and secrets.Starting Price: $199 per month
