Query every connected data source in plain English. Every answer runs through your governed semantic layer, so you're never one definition conflict away from the wrong number.
Every enterprise has deployed an AI assistant. And every enterprise is discovering the same problem: the AI gives different answers to the same question, depending on which system it queried and how it interpreted the data it found.
LazyFox's Natural Language Analytics sits on top of your governed semantic layer. Before any query reaches your data, the meaning has already been resolved, which revenue number, which customer definition, which time window. The answer you get is the right one, not the most probable one.
Six capabilities that turn natural language queries into governed, auditable, cross-system intelligence.
Ask any business question in plain English. No SQL, no dashboard configuration, no data team involvement. The interface translates intent into governed queries, resolving your organization's specific metric definitions automatically before touching any data source.
Plain English · Zero SQLAsk a question that spans Salesforce, SAP, Databricks, and MongoDB in a single prompt. LazyFox reconciles the meaning across all of them at runtime, so "what is our Q3 churn?" returns one governed answer, not three different numbers from three different systems.
Multi-source · ReconciledA controller asking about revenue and a sales director asking about revenue need different answers, both correct. LazyFox's contextual layer applies role-based definitions automatically, so every user gets the view that's governed for their function. Without asking twice.
Context-driven · AutomaticNo raw data is ever sent to a language model. LazyFox operates on your schema and governed semantic definitions, the actual data your query retrieves comes directly from your source systems, not through any model. Enterprise-grade data privacy without enterprise-grade complexity.
Zero data exposure · On-prem readyLanguage model tokens are consumed once, at setup, when LazyFox builds your governed query templates from your semantic definitions. At query time, execution is fully deterministic: 100% from actual data, no per-query model calls, no hallucinations. Consistent answers, predictable cost.
Deterministic · Cost-controlledEvery query, every answer, every data source referenced, logged. Who asked, when, against which version of the semantic definition, and which systems were queried. Governance for enterprise AI that goes beyond model compliance into the meaning of every answer returned.
Full lineage · AuditableWhen an executive asks "what is our NRR?", the answer they need requires data from your CRM, your data warehouse, and possibly your ERP. Today, that answer is assembled by a human intermediary who manually pulls, reconciles, and formats it.
LazyFox eliminates that intermediary, not by letting an AI interpret the data, but by governing the meaning before the query runs. Every cross-system answer is resolved against your approved semantic definitions, so it's the same answer your finance team would give. Automatically.
Most natural language data tools send your question to a language model and hope the interpretation matches your intentions. LazyFox works differently, meaning is resolved before the model is ever involved.
The answers are deterministically correct, not probabilistically likely. Your CFO doesn't need "probably right." They need right.
LazyFox identifies the business concepts in your question (KPIs, time windows, dimensions, filters) using your organization's own vocabulary.
Each concept is matched to your governed semantic layer, the definitions your team has approved, with role-based context applied for the querying user.
Deterministic queries run against the relevant source systems (Salesforce, SAP, Databricks, MongoDB) in parallel. No raw data touches an LLM.
Results are combined and surfaced with full attribution, which definition version was used, which systems were queried, when the data was last refreshed.
Every query and response is recorded for audit, compliance, and drift detection. If users consistently push back on an answer, LazyFox surfaces that as a drift signal to the semantic manager.
Natural Language Analytics is designed for business users, not data teams. Everyone gets answers. The data team gets fewer interruptions.
Natural Language Analytics connects to your existing systems read-only. No ETL, no migration. Add a new data source and it's immediately queryable, governed by the same semantic layer.
See all integrations →We'll connect LazyFox to one of your data sources and let you ask real questions, live, in the demo. Bring the question your team argues about most.