Articles
Supper and Amazon Redshift: AI Analytics for Business Teams
Learn how Supper works with Amazon Redshift to help business teams investigate warehouse data, combine SaaS sources, and reuse analytical workflows.
Supper and BigQuery: AI Analytics for Business Teams
Learn how Supper works with BigQuery to help business teams investigate warehouse data, combine SaaS sources, and reuse analytical workflows.
Supper and Databricks: AI Analytics for Business Teams
Learn how Supper connects to Databricks so business teams can analyze governed lakehouse and SaaS data using company definitions and reusable workflows.
Supper and Snowflake: AI Analytics for Business Teams
Learn how Supper connects to Snowflake so business teams can analyze governed warehouse and SaaS data using company definitions and reusable workflows.
How Supper Works with Amazon Redshift
Learn how Supper connects to Amazon Redshift, builds a business semantic model, supports cross-source analysis, and gives teams governed access to data.
How Supper Works with BigQuery
Learn how Supper connects to BigQuery, uses existing data context, supports cross-source analysis, and gives business teams governed access to data.
How Supper Works with Databricks
Learn how Supper connects to Databricks, uses Unity Catalog context, supports cross-source analysis, and gives business teams governed access to data.
How Supper Works with Snowflake
Learn how Supper connects to Snowflake, uses existing Semantic Views, supports cross-source analysis, and gives business teams governed access to data.
How to make AI use your company's own definitions
Supper Business Logic turns your company's terms, acronyms, rules, and definitions into instructions Supper applies to every question, so the same request returns the same answer.
How to make charts with natural language
Supper Charts turns data into visualizations from a plain-language request, then lets you refine the chart by conversation, with no chart-editor menus or settings to learn.
Supper MCP for LLMs
A semantic layer for trusted company data.
Reusable workflows for data analysis
Supper Skills turn recurring analysis like churn, health scoring, and pipeline risk into reusable workflows your AI agent runs the same way every time, using your team's own definitions.
AI Data Governance for Data Teams
Supper's Admin Control Center helps data teams govern AI data usage through shared definitions, visibility into activity, and access controls.
How Supper's Semantic Agent Keeps Business Context Current
Supper's Semantic Agent helps data teams find, investigate, and improve the business context that AI agents use to answer data questions.
Why AI Data Platforms Use Multiple AI Agents
AI data platforms use multiple agents because analysis, semantic modeling, and dashboard building need different tools and context. See how Supper's three agents split the work.
Skill Parser
Turn existing skill files into structured, reusable workflows Supper can understand.
The Supper SQL IDE Keeps SQL in the Analytics Workflow
Supper's SQL IDE gives technical users a professional SQL workspace connected directly to conversational and agentic data analysis.
User Entitlements for Agentic Analytics
Supper User Entitlements lets data teams control which schemas, tables, and columns each user can access through agentic analytics.
What makes an AI data agent trustworthy?
A practical look at the context, controls, and transparency reliable AI analysis requires.
What comes after the dashboard?
Why the next analytics interface will be conversational, contextual, and built around action.