Impact Engine — Orchestrator

Fan-out/fan-in pipeline runner for scaling pilot experiments to full deployment

Running a single causal study is hard enough. Running a portfolio of pilots — measuring effects, scoring confidence, selecting winners, and validating at scale — means stitching together independent analysis steps, synchronizing results, and managing a fan-out/fan-in execution pattern. Most teams build this glue code from scratch for every engagement.

Impact Engine — Orchestrator wires the full MEASURE → EVALUATE → ALLOCATE → SCALE pipeline into one config-driven run. A YAML file defines your initiatives, budget, and component settings. The orchestrator fans out pilot measurements in parallel, collects confidence-scored results, runs portfolio selection, then scales the winners — producing an outcome report that compares predicted vs actual impact. Swap any pipeline component by changing one line in the config.

Visit our documentation for details.