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Predict.ai
Analytics & insights

Understand your data before you predict it.

Predict.ai turns connected time-series data and events into an explorable workspace, then continuously surfaces the changes and relationships worth investigating.

Hundreds of signals in one view — grouped, searchable, zoomable, and aligned with event streams.

Explore

See the whole workspace without flattening it into a spreadsheet.

Compare signals across different units and magnitudes, drill into groups, pin important series, and move from a multi-year overview to a precise time window.
  • Group envelopes keep large signal collections readable
  • Overlay continuous signals with scored event streams
  • Zoom, pan, filter, pin, and compare shapes or raw values
Start broad, drill into a group, then pin the exact signals you want to compare.

Automatic insights

Get a statistically grounded brief of what changed.

The workspace intelligence brief ranks important findings from computed evidence. The narrative explains the result; the underlying metrics, periods, and signal history remain available for review.
  • Executive summary and ranked headlines
  • Recent movers and volatility changes
  • Leading indicators, weekly rhythms, and anomaly periods
  • A watchlist of signals that deserve attention next
The language is generated; the numbers and rankings come from deterministic analysis.

Relationships

Find what moves together—and what tends to move first.

Inspect correlation, direction, lag, and predictive evidence across signals. Use those relationships to investigate business behavior or identify candidate inputs for a forecast.
  • Lead-lag analysis identifies earlier-moving signals
  • Relationship strength stays tied to the evaluated window
  • Visual graphs help teams move from a finding to its evidence
Relationships are evidence to investigate—not automatic claims of causation.

Trends and shifts

Compare recent behavior with a longer baseline and see which signals moved most.

Recurring rhythms

Surface daily, weekly, and longer seasonal patterns in time-series behavior.

Anomaly periods

Locate unusual windows across many signals without inspecting every chart manually.

Leading indicators

See which signals tend to change before another signal moves.

Freshness and coverage

Inspect records, time span, latest values, cadence, and ingestion health.

Evidence in context

Keep the chart, evaluated period, and supporting signals beside every finding.

Put your data to work.

Connect your own data or start with a sample. Explore automatic insights, ask questions, engineer features, and build a forecast in the same workspace.

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