Analytics AI apps

AI-native business intelligence and data visualization platform.

Golden Analytics is a web-based business intelligence platform that combines data connection, discovery, preparation, analysis, and dashboarding in one tool. It profiles datasets automatically, surfaces patterns, and a 'Slider of Autonomy' lets users dial how much the AI does versus how much they drive themselves — taking a raw dataset to a shared dashboard in as little as two clicks. It offers a free tier, with Team and Enterprise plans that include all features without token metering.

Agentic AI data platform for research and analytics.

Zerve is a data platform that brings AI agents, notebooks, automatic data discovery, conversational reports, and deployment into a single canvas for data scientists and analysts. Agentic notebooks assist with exploration and analysis, the platform maps schemas and surfaces patterns from connected data, and finished work can ship directly as an API, app, or dashboard. It offers a free tier, with self-hosted and air-gapped deployments for enterprise.

AI agents for finance teams — chat with your data, automate reporting.

Finance automation platform whose AI agents let teams query financial systems in natural language — no SQL required — and automate reporting workflows like flux analysis, AR aging, and revenue forecasting. It connects to ERPs (NetSuite, QuickBooks), data warehouses (Snowflake), and billing systems, and exports analysis in multiple formats.

Natural-language data analyst that turns questions into SQL.

Defog is an AI data analyst that converts natural-language questions into SQL across databases, warehouses, and CSVs, returning answers without writing queries. It is built on SQLCoder, the company's own open-source text-to-SQL model, and emphasizes privacy—your data is never sent to or used to train the model. Defog Agents extend it to multi-step SQL, Python, and R workflows.

Explore, structure, and analyze millions of unstructured records as interactive embedding maps.

Nomic Atlas is a data-intelligence platform that embeds large collections of text, image, and audio data and renders them as interactive 2-D maps you can browse, search, cluster, and label in the browser. Powered by Nomic's own embedding and topic-modeling models, it scales from hundreds to tens of millions of points and exposes the same pipeline through a developer API for embeddings and retrieval.

Agentic notebooks that let any team explore data in natural language with inspectable SQL.

Querio is a data platform built around agentic notebooks: teams and customers ask questions in natural language and Querio's agents generate the SQL and Python to answer them, with every query visible and editable. It connects to multiple data sources, integrates with Slack, and can embed analytics into customer-facing applications for users of any technical level.

AI-assisted self-service BI built on a programmable, governed semantic layer.

Holistics is a business intelligence platform that lets data teams define centralized metrics and modeling logic in a programmable semantic layer, then lets business users explore the data through AI queries or point-and-click without writing SQL. Its AI reasons over the governed semantic layer — generating AQL (Analytics Query Language) rather than raw text-to-SQL — so answers stay grounded in defined metrics, with lineage, multi-turn context, and Git-based version control for analytics-as-code.

Agentic analytics that investigates why your metrics moved and delivers the answer.

Tellius is an AI-native analytics platform that lets teams ask questions of enterprise data in natural language and get finished insights back, not raw dashboards. Its Kaiya assistant handles conversational analytics, automated anomaly detection, and autonomous root-cause investigation, chaining detection, explanation, and delivery into agentic 'missions'. Outputs include board-ready presentations and executive memos.

Agentic spreadsheet where every cell runs its own AI agent to research and fill data.

A web-based spreadsheet reimagined as a living workspace powered by swarms of AI agents. Each cell can run its own agent that finds, verifies, and fills in data, so the sheet actively researches, analyzes, and produces deliverables in real time. It's aimed at bulk data gathering and enrichment across consulting, finance, sales, and operations workflows.

AI agent for spreadsheets that builds and edits financial models in Excel and Sheets.

An AI agent purpose-built for spreadsheet work, from cleaning data and writing formulas to building full financial models — DCFs, LBOs, and three-statement models — from a natural-language prompt. It runs as a web app and as native add-ins for Excel and Google Sheets, with a Windows CLI for power users. Built for analysts who live in spreadsheets rather than as a generic chatbot bolted onto a grid.

AI-native data platform: warehouse, ETL, BI, and agents in one.

Definite is a data-platform-as-a-service that bundles a managed warehouse, ETL pipelines, modeling, and BI into one AI-native product. Its assistant, Fi, turns natural-language questions into SQL and builds full data apps — filters, KPIs, and tables — not just charts. It ships 500+ connectors and exposes data to external agents like Claude and Cursor over MCP.

AI data-analysis notebooks that turn questions into dashboards.

Fabi.ai is an AI-native analytics platform built around Smartbooks — reactive notebooks that blend SQL, Python, and natural-language querying. Analysts ask a question and Fabi generates the query, chart, or workflow, then turns the result into a shareable dashboard or scheduled report. It connects to warehouses like Snowflake, BigQuery, and Redshift.

AI data analyst that answers business questions in plain language.

Zenlytic is a self-serve business intelligence platform whose AI analyst, Zoë, answers natural-language questions by reasoning over a governed semantic layer rather than raw tables, so results map to agreed business definitions. It connects to warehouses like Snowflake, BigQuery, Redshift, and Databricks plus dbt and Looker semantic models, and returns inspectable analyses, visualizations, and reports inside the app or via Slack and Teams. The emphasis is on auditable, defensible answers for non-technical users.

Open-source product analytics with LLM observability built in.

A product analytics platform that folds session replay, feature flags, experiments, and a data warehouse into one stack. Its LLM analytics suite tracks traces, token costs, latency, and model errors for AI products, with automatic clustering that groups traces by behavior. Usage-based pricing with a generous free tier on every product.

AI financial analyst agent built natively into Excel.

Endex embeds an AI agent natively into Microsoft Excel for institutional finance teams. It runs long multi-step tasks — building three-statement models, DCFs, and presentation decks — grounded in a firm's internal data, public disclosures, and trusted financial sources, with custom LLMs tuned for financial documents. It is deployed at investment banks, private-equity firms, and hedge funds, with SOC 2 and ISO 27001 compliance and zero-data-retention agreements with model providers.

AI-native collaborative notebook for data teams.

Collaborative data notebook positioned as a drop-in Jupyter replacement: real-time multiplayer editing, SQL + Python + R blocks, warehouse integrations (Snowflake, BigQuery, Redshift), and notebooks that deploy as data apps and dashboards. Deepnote AI generates, fixes, and explains code, and an agent can run analyses autonomously.

Open-source GenBI agent: ask in plain language, get governed SQL, charts, and dashboards.

An agentic GenBI platform from Canner that turns natural-language questions into governed SQL, charts, and live dashboards over 20+ databases and warehouses, from BigQuery and Snowflake to PostgreSQL and DuckDB. Its open-source core is a semantic 'context layer' (MDL) that grounds LLM-generated queries in business definitions instead of raw schemas. Runs self-hosted via Docker or as a managed cloud with RBAC and row/column-level security.

An AI spreadsheet where cells run real code against live data connections.

Quadratic is a from-scratch spreadsheet built on Rust, WASM, and WebGL that pairs AI analysis with real code: cells can execute Python, SQL, and JavaScript, and connect to 25+ sources like Postgres, Snowflake, BigQuery, and QuickBooks. Ask questions in natural language and get working formulas, code, and charts back in the grid.

Open-source SQL agent — ask questions in plain English, get accurate SQL on your warehouse.

A Python framework for text-to-SQL: you train a RAG layer on your schema, past queries and documentation, and Vanna generates SQL that actually fits your warehouse, returning results as DataFrames or Plotly charts. Connects to Postgres, MySQL, Snowflake, BigQuery, SQLite and more. Vanna 2.0 adds agent features — lifecycle hooks, middlewares, conversation storage and observability — with an optional hosted cloud for access control and audit logs.

Agentic analytics notebook for SQL, Python, and R data teams.

A collaborative data workspace combining SQL, Python, and R notebooks with shareable data apps. Its Notebook Agent and Magic AI generate queries, debug code, run exploratory analysis, and build visualizations as editable notebook cells. Built for data teams that need reproducible, governed analysis rather than one-off chat answers.

Conversational AI data analysis for files, databases, and the web.

A no-code data analysis tool that turns natural-language questions into instant insights, charts, and presentations. Users upload Excel, CSV, TSV, and SQL files or paste URLs, and the AI handles cleaning, statistical analysis, and visualization with suggested follow-up questions. Supports multi-modal inputs including images and audio.

Agentic analytics platform with the Spotter natural-language agent.

An enterprise analytics platform built around search and AI. Its Spotter agent lets users ask questions in natural language and get governed answers on live data, reasoning through each step and checking its own work via a semantic layer. Also ships specialized agents for modeling, visualization, and code, with embeddable governed analytics.

AI-native BI that builds dashboards from plain-English questions.

An AI-native business intelligence platform that connects directly to SQL databases and warehouses. Describe what you want in natural language and it generates the query, picks a chart type, and saves the result to a dashboard. Supports Postgres, MySQL, BigQuery, Snowflake, and 750+ data sources via built-in connectors.

No-code predictive analytics and forecasting for media and agency teams.

A no-code AI platform for building predictive models, forecasts, and audience segments from business data. Users connect a CSV or live source like Salesforce, HubSpot, or Snowflake and build models through chat and drag-and-drop, then generate client-ready reports. Now focused on media agencies and marketing analytics use cases.

Conversational analytics over your Databricks lakehouse data.

A no-code conversational analytics interface within the Databricks platform. Business users ask plain-English questions about lakehouse data and Genie returns SQL, charts, and natural-language explanations. It adapts to your business concepts and enforces Unity Catalog governance, so answers stay secure and auditable. Billed through Databricks compute rather than a separate license.

Chat with your data — an AI data analyst for CSVs, sheets, and DBs.

An AI data analyst that lets you upload CSVs, Excel, and Google Sheets, then ask questions in plain language to clean, analyze, visualize, and model your data. It writes and runs Python behind the scenes and can generate charts, slides, and reports from the results. Pro plans add direct connectors to live databases like Snowflake, BigQuery, and Postgres.