decisions at scale
to improve profits
Businesses are automating more decisions at scale.
transaction risk assessment
matching & dispatch
Unfortunately, these systems are fragile and opaque—a high-stakes liability.
As systems decay,
errors compound silently,
swapped data sources
These systems comprise a complex ensemble of models, heuristics, algorithms, and data sources developed and managed by disparate teams of various disciplines.
Worse, nobody feels accountable.
We lack the global visibility needed to prioritize issues for business impact.
AI that observes your automated decisions in production and alerts precisely where you’re leaving value on the table.
after a lightweight agent is installed atop your production decision systems, dcyd learns the dependency graph of data (sources, models, and transformations) supporting those decisions.
when combined with the decisions’ outcomes, an intelligent analysis alerts how much value can be recovered by fixing the components having the worst impact on your objectives.
Existing solutions aren't solutions
looking in the wrong haystack.
The reams of data in your datastores a mere shadows of the vital decisions your automated systems have made. hoping to find actionable insights simply by slogging through a morass of logs is hopeless.
You need to observe the decisions themselves and see their impact on your bottom line.
missing the big picture.
Your business decisions don’t run on isolated models. They run on chains of models, sprinkled with heuristics, complicated by feedback loops. Model monitoring doesn’t give you what you need because it lacks visibility across systems and doesn’t know your business objectives.
You need a solution that provides cross-system visibility and understands your business objectives.
too noisy and too needy.
Anomaly detection routines detect what’s different, not what’s bad. steady underperformance goes unnoticed, while alerts are riddled with noisy distractions. your teams waste their time responding to false positives and adjusting alert thresholds manually.
You need a solution that bothers you when—and only when—decisions are harming your business.
if you care about profits, revenue, and growth.
observes automated decisions in production
learns behaviors and data dependencies
analyzes the impact of each component on business objectives
alerts only business-critical issues, because it understands what's important