kpis.do
Track Every Business Metric in Real-Time
Automated KPI tracking with AI-powered anomaly detection, root cause analysis, and natural language insights. Monitor revenue, growth, retention, and custom metrics—all updated in real-time with automatic alerts when metrics deviate from expected patterns.
import { KPIs } from 'kpis.do' // Track revenue with anomaly detectionKPIs.track.Revenue.every.hour($ => { const revenue = $.Database.query.sum('orders', 'amount', { status: 'completed' }) const analysis = $.AI.analyze.Metric({ metric: 'revenue', value: revenue }) if (analysis.anomaly && analysis.severity === 'high') { $.Slack.send.Alert({ text: `Revenue down ${analysis.change}%: ${analysis.reason}` }) }})
One of 48 primitives
kpis.do sits in Business: goals, plans and the work itself. Every .do shares one grammar, Business-as-Code, and one SDK.
Data
Records, vocabulary and search
Insight
Measure, test and trace
Frequently asked questions
Revenue metrics (MRR, ARR, churn rate), product metrics (DAU/MAU, feature adoption, session duration), growth metrics (conversion rates, CAC, LTV), operational metrics (API latency, error rates, uptime), and custom business metrics. Connect to any data source (databases, analytics tools, APIs) and define metrics using SQL, TypeScript, or natural language. Track 100+ pre-built KPIs or create unlimited custom metrics.
AI analyzes historical patterns and statistical models to establish baseline behavior for each metric. When values deviate significantly (configurable threshold, default 2-3 standard deviations), automatic alerts trigger with severity levels (low/medium/high/critical). Machine learning adapts to seasonality, growth trends, and business cycles. Reduce false positives by 90% compared to simple threshold alerts. Get root cause analysis explaining why metrics changed.
Yes. Build unlimited dashboards with drag-and-drop components (line charts, bar charts, tables, maps, custom visualizations). Define metrics using SQL queries or TypeScript transformations. Share with stakeholders via secure links, embed in internal tools, or schedule automated email reports (daily/weekly/monthly). Role-based access controls limit sensitive metrics. Export to PDF, CSV, or PNG for presentations.
AI agents continuously analyze KPI trends and generate natural language insights like "Conversion dropped 15% after homepage redesign" or "Revenue spike correlates with Black Friday campaign." Insights include root cause analysis (which segments were affected, correlation with other metrics), recommended actions, and confidence scores. Ask questions in natural language like "Why did churn increase last week?" and get instant answers with supporting data.
Yes. Native integrations with Tableau, Looker, Power BI, Metabase, Redash, and other BI platforms via JDBC/ODBC connections or REST APIs. Real-time data sync pushes KPI updates to external tools. Semantic models provide consistent metric definitions across all tools. Import data from Google Analytics, Mixpanel, Amplitude, Segment, or custom sources. Use .do as your single source of truth while keeping existing BI tools.