Conversational analytics products built on top of raw text-to-SQL invite two problems at once: your data leaves your boundary, and the model can invent plausible-looking answers. DataGenie is designed from the ground up to avoid both.Documentation Index
Fetch the complete documentation index at: https://docs.datagenie.ai/llms.txt
Use this file to discover all available pages before exploring further.
Three guarantees
Zero raw data to LLMs
Language models only see aggregated KPIs and dimension values — never row-level data. Your raw records stay in your environment.
Deterministic algorithms
Anomaly detection, root-cause attribution, forecasting, and scenario planning run on proven statistical and ML algorithms — not generative models.
Human-in-loop by design
Wisdom plans an execution path, runs it through deterministic services, and presents the result for you to review. You validate; DataGenie doesn’t guess.
How Wisdom stays safe
is an agentic system that understands business questions and orchestrates deterministic services to answer them. It is not text-to-SQL. It does not invent numbers.Question interpretation
Wisdom parses your question using an LLM — but with only metadata (KPI names, dimension names, domain knowledge) in scope. No raw data.
Execution plan
A master coordinator agent selects which deterministic services to call — Metric, Insights, Contribution Analysis, Forecasting, or Scenario Planning — and in what order. The plan branches based on intermediate results.
Deterministic computation
Every number comes from a deterministic service running on your data. The LLM sees aggregated outputs, never rows.
The guardrails you configure
Every Wisdom-enabled dataset has three configuration surfaces that act as safety gates. None are optional for enterprise deployments.Domain Knowledge
Natural-language rules that encode your business logic. Wisdom answers within these rules — it doesn’t invent them.
Wisdom Skills
Packaged, reusable analytical pipelines defined in plain language. Each Skill runs as a deterministic pipeline.
Business Events
A documented timeline of real-world context. Wisdom connects observed patterns to recorded causes — not invented correlations.
Why this matters
For enterprise buyers, this is the difference between experimenting with AI analytics and deploying it to production. Teams at regulated, data-sensitive companies have run DataGenie in production because the safety properties are structural — not a policy document.What’s next
Security & Trust
SSO, RBAC, audit, and our Trust Center.
Wisdom overview
See the agentic analytics assistant in action.