Apply approved customer scores
Connect
SPIRITT
FaradayPut predictions into operation
Connect models to customer work
Operate Faraday datasets, cohorts, outcomes and delivery targets using your account’s customer data and model evidence. Carry approved source data through cohorts, outcomes and output scopes with visible dependencies.
What you can do with Faraday.
A connected prediction pipeline
Carry approved source data through cohorts, outcomes and output scopes with visible dependencies.
Delivery that can be checked
Preview destination payloads and inspect target state before treating a prediction feed as ready.
Models with operating evidence
Track ingress, membership and efficacy to spot stale inputs or changing audience behavior.
Works with your other apps.
Get started in three steps.
01
Open your workspace
Start a SPIRITT workspace for a connected prediction pipeline and give it your operating priorities.
02
Connect Faraday
Connect your Faraday account and choose the records and actions this workspace may use. Use existing authorized datasets and specify permitted model and delivery changes.
03
Delegate an outcome
Ask SPIRITT to build a prediction operations desk. It carries the work through and checks the result.
Hand over a mission.
Choose a mission. Make it yours.
Put Faraday to work.
Connect models to customer work
Questions
Faraday, with SPIRITT.
01Can it create predictive workflows?+
Yes. Faraday datasets, cohorts, outcomes, persona sets, scopes and targets can be created or maintained within the account’s available resources.
02Does a model guarantee more revenue?+
No. SPIRITT uses the observed outcome and scope-efficacy metrics to evaluate operation, not invented uplift or guaranteed business results.
03Can it deliver scores to other systems?+
Targets configure prediction and cohort delivery to existing authorized destinations. SPIRITT can preview a target and inspect its configuration and status.
04Does it need new consumer data purchases?+
These missions can use your existing customer datasets and account resources. Adding paid data or expanding subscriptions is a separate authorization.
05Can it diagnose stale predictions?+
The dependency graph, dataset ingress metrics and resource states help trace stale outputs to their upstream cause.
06What is the difference between archive and delete?+
Archiving stops resource updates while retaining visibility. Deletion permanently removes the resource and requires a separate retention decision.