Supper is an AI‑native data platform that connects to SaaS tools and databases in minutes, allowing users to ask natural‑language questions and receive instant, audit‑tracked insights. It automates data integration, applies built‑in business logic and security controls—including SOC 2 compliance and PII/PHI segregation—to generate accurate SQL queries and visualizations without custom ETL code. The service is designed for high‑growth enterprises seeking rapid, self‑serve analytics with minimal engineering effort.
Funding
Funding not disclosed
Founders
Product
Problem
Companies with fast‑growing businesses often rely on traditional BI stacks that require weeks of integration, dedicated engineering effort, and complex licensing, making it difficult to obtain timely answers from their data.
Solution
Supper provides an AI‑native data platform that connects to SaaS tools and databases in minutes and lets users ask natural‑language questions to receive instant, audit‑tracked insights. The system classifies data sensitivity, enforces SOC 2‑compliant security, and applies built‑in business logic to generate accurate SQL queries without exposing raw LLM data. Answers are delivered in seconds with optional charting, and a conversational flow enables follow‑up queries similar to interacting with a data analyst. Supper also offers a unified data stack—including layers for intelligence, business logic, data cleansing, semantic modeling, and aggregation—so organizations can replace or augment existing pipelines without custom ETL code. Dedicated support and on‑demand analyst assistance accelerate onboarding and ensure the platform reflects each company’s vocabulary and reporting needs.
Target Audience
Primary customers are high‑growth enterprises and their data‑focused teams—product, finance, and operations analysts—who need rapid, self‑serve insights without extensive engineering overhead.
Features
- Pre‑built connectors for SaaS applications and data warehouses with automated schema discovery, enabling data source integration in minutes
- Natural‑language to SQL engine that incorporates contextual business rules, permissioning, and audit‑trail logging for each query
- Real‑time and cached data access across unified aggregation layer, eliminating the need for custom ETL pipelines
- Built‑in data cleansing and semantic structuring that standardizes fields, flags inconsistencies, and maintains source data integrity
- Interactive charting and visualization options that generate board‑ready graphics directly from query results
- Enterprise‑grade security including SOC 2 Type I/II compliance, PII/PHI segregation, and robust entitlement management
- Ongoing AI‑driven learning of company‑specific terminology and business logic to improve answer accuracy over time