DataReady: Gemini-First BI Truth Audit

Every major BI platform in 2026 ships natural language querying - Power BI Copilot, Looker with Gemini, ThoughtSpot Sage, Tableau Einstein. They all assume the underlying data is clean, labeled, and semantically coherent. It usually is not. Real enterprise data environments contain columns named `val1`, status values like `1`, `active`, `NULL`, and `yes` in the same field, date columns stored as text strings, and data dictionaries that describe a grain the warehouse table no longer uses. BI copilots built on these layers don't fail gracefully, they confidently serve wrong answers to executives. What DataReady Does DataReady is a Gemini-first audit system for semantic-layer readiness. Upload a CSV (or schema extract), an optional dashboard PDF or screenshot, and an optional data dictionary PDF. DataReady runs 4 specialized Gemini agents: 1. Profiler: column-level analysis + multimodal cross-checking across all inputs 2. Business Logic Validator: checks whether the data makes business sense, not just whether it parses 3. Remediation Planner: generates SQL, Python, and plain-English fixes for every issue 4. Readiness Scorer: synthesizes findings into a score (0–100), grade, and executive verdict DataReady discriminates: messy data gets an F with detailed remediation; clean data gets a B with minimal flags.