Analyze · Causal & Impact
Stop reporting the number. Move it.
Most analytics tell you what happened. Celeredge tells you why, and what to change. Causal inference on your client's own data, grounded in the industry ontology.
Estimating causal effects across 38 tables, live.
From correlation to decision.
Three steps, one workflow.
1 · Discover drivers
Identify the variables that genuinely move a target KPI, drawn from the ontology graph, not guessed.
2 · Estimate effect
OLS estimation with confounders adjusted via the KPI graph, returning an effect size and confidence interval.
3 · Simulate impact
"Cut stockouts by 10%?" See the projected change in the outcome before you commit a recommendation.
Grounded, not guessed
Reasoning over real data.
The analysis connects to your client's warehouse and reasons over actual metrics like NPS, stockout rate, promo ROI and days of supply, not a generic template.
- Variable selection traverses the industry ontology
- Results cached per engagement, connection and KPI
- Streaming progress while the model runs, no black box
Bring a dataset. Leave with a decision.
We'll run a live causal simulation on a KPI that matters to you.