Products
Outcome Measure
Establish what happened. Connect to data, ingest evidence, produce the factual record.
The evidence and calculation layer
Before anyone can argue about whether an outcome counts, someone has to establish what actually happened. That is Outcome Measure's job. It connects to the agreed source systems and produces the measured outcome record: a structured, timestamped, evidence-backed factual account of every event that might constitute an outcome.
Outcome Measure does not decide whether an event counts commercially. That is Outcome Verify's job. Outcome Measure answers a narrower, more fundamental question: what happened? It collects the evidence, normalizes it, calculates the raw metrics, flags anomalies, and produces the factual record that the rest of the platform relies on.
This separation matters. When measurement and commercial judgment are combined in one system, disputes become intractable. By isolating the factual layer, Outcome Measure gives both parties a shared evidentiary foundation. If the numbers are wrong, fix the data. If the classification is wrong, take it up with Outcome Verify.
Outcome Measure is configured by the deal specification you create in Deal Designer. Define what to measure there, and Outcome Measure knows exactly what to look for.
Evidence infrastructure, not just a connector
Data connectors & evidence ingestion
Pre-built connectors for Zendesk, Salesforce, ServiceNow, AWS Cost Explorer, NetSuite, Jira, and HubSpot. Support for API-based, event-stream, file-upload, and manual evidence submission. Read-only access to source systems—Acretix never writes to production environments.
Evidence normalization
Normalize incoming data across different sources, schemas, and formats into a consistent evidence model. Handle field mapping, type coercion, deduplication, timezone reconciliation, and data quality validation. Pipeline configuration is versioned and auditable.
Baseline comparison
Compare incoming events against the independently established baseline defined in Deal Designer. Track cumulative progress relative to the agreed starting point. Detect baseline drift and flag when underlying conditions have changed materially. Baselines are independently measured—not vendor-reported figures.
Raw metric calculation
Calculate the raw outcome metrics—event counts, aggregate values, rates, durations, and derived calculations—before any commercial rules are applied. These are the numbers before Outcome Verify applies count/no-count logic. The calculation methodology is defined in Deal Designer and applied automatically.
Anomaly detection & confidence scoring
Flag unexpected shifts in event volume, timing patterns, or data characteristics. Score the confidence level of each measured outcome based on data completeness, source reliability, and consistency with historical patterns. Surface potential data quality issues before they become commercial disputes.
Measured outcome records
Produce a structured evidence packet for each measured event: the source data, the transformation applied, the raw metric calculated, the confidence score, and all supporting citations. This is the factual input that Outcome Verify uses to make the commercial determination. Each record is immutable once produced.
How Outcome Measure connects to everything else
Outcome Measure sits between Deal Designer and Outcome Verify. It receives the outcome definitions and measurement methodology from Deal Designer—what to look for and how to calculate it. It produces the measured outcome records that Outcome Verify uses to make count/no-count decisions. When Outcome Verify flags a data discrepancy during adjudication, it routes back to Outcome Measure for re-measurement or additional evidence. The evidence model is shared across the entire platform—Outcome Settle references the same underlying data when generating settlement statements.
From data connection to factual record
Connect
Deal Designer publishes the deal specification. Outcome Measure uses it to know what to look for. The data connection is established — CSV or live API to the agreed source system.
Ingest and normalize
Events arrive from the agreed source system. Outcome Measure normalizes them, checks for anomalies, handles duplicates and missing data, and produces clean evidence records.
Calculate and score
Raw metrics are calculated against the deal specification. Confidence scores are assigned. Low-confidence records are flagged. The measured outcome records are ready for Outcome Verify.
Produce the factual record
Outcome Measure produces the measured outcome record with a complete evidence packet for each event. This is the factual foundation that Outcome Verify uses to make the commercial determination.
Every measurement starts with a deal spec
Talk to our team about your measurement setup.