Just Ask.No SQL Required.
Natural language analytics for business users. Ask questions in plain English, get instant insights. Self-service data exploration without coding or waiting on data teams.
Examples
See It in Action
Real questions. Real answers. Instant insights.
What was our revenue last quarter compared to the same period last year?
Q3 2024 revenue was $4.2M, up 23% from Q3 2023 ($3.4M). Growth driven primarily by enterprise segment (+45%).
Which customers are at risk of churning in the next 30 days?
12 accounts flagged high-risk: Acme Corp (87% risk), TechStart Inc (82% risk), GlobalCo (79% risk)... [View full list]
Show me sales pipeline by stage and expected close date
[Generates pipeline visualization] Total pipeline: $8.7M across 47 deals. $2.1M expected to close this month.
What's driving the increase in support tickets this week?
Support tickets up 34% WoW. Top drivers: billing questions (42%), feature requests (28%), bug reports (18%).
Capabilities
Analytics for Everyone
Self-service analytics that actually works. No training required.
Ask in Plain English
No SQL, no formulas, no special syntax. Ask questions like you would ask a colleague.
Instant Answers
Get responses in seconds, not hours. No waiting for the data team to build a report.
Smart Visualizations
AI automatically chooses the best chart type. Bar, line, pie—whatever tells the story best.
Follow-Up Questions
Drill down naturally. "Show me by region" or "What about last year?" just work.
Save & Share
Turn any query into a dashboard widget or scheduled report. Share with your team.
Learn Your Business
AI understands your terminology. "Big deals" means >$100K if that's what you've defined.
Use Cases
Questions Every Role Can Ask
From CFO to marketing intern—everyone gets instant access to data.
"What's our cash runway at current burn rate?"
→ Instant treasury visibility without building spreadsheets
"Which deals are most likely to close this quarter?"
→ AI-ranked pipeline without manual forecasting
"What's our CAC by channel for the last 6 months?"
→ Channel ROI without waiting on analytics team
"How are we tracking against our board metrics?"
→ Real-time board readiness without prep work
Comparison
SQL vs. Natural Language
Same question. Very different experience.
Traditional SQL
SELECT
DATE_TRUNC('month', created_at),
SUM(amount) as revenue
FROM orders
WHERE created_at >=
DATE_TRUNC('quarter',
CURRENT_DATE - INTERVAL '3 months')
GROUP BY 1
ORDER BY 1;Requires SQL knowledge + schema familiarity
Neuronify
"Show me monthly revenue for last quarter"
Anyone can ask. Instant answer.