optimizing pricing, lending, risk, and promos. transparently.

decisions as a service

automate intelligent
decisions in a dash.

the flow

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the video (1).png


  • decimates time to scaling good decisions

  • saves you the cost of a Data Science team

  • eliminates hidden DevOps maintenance costs

  • lets you inspect the full rationale for each decision

  • easy to call or integrate with existing codebase

  • continuously optimizes for your biz objectives

  • promotes clarity of business objectives


  • handles all business objectives

  • handles all common decision "levers"

  • continually self-optimizes

  • full analysis and reporting

  • batch mode

  • recalls full historical context

  • download data organized for analysis

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decision diagnostics

AI that learns the context behind your automated decisions, and alerts what to fix to recover the most value.

the flow

spot complex graph

the video


  • decimates time to discover and fix valuable issues

  • guards against decay due to

    • evolving markets​

    • fragile pipelines

    • imprecise definitions

    • swapped data sources

    • unstable logging

  • lets you deploy models and algos with confidence

  • frees several Eng/DS to invent, not reinvent

  • increases trust in your Data Org

  • fills Eng/Data/Prod accountability gap

  • last line of defense, watching the watchmen


  • alerts as data issues are discovered

  • estimates of business value of each issue

  • graphical view of global production data

  • spans batch/async pipelines, too

  • installs simply

  • recalls full historical data context

  • data organized ideally for analysis

  • interact through UI, API, and CLI

existing solutions aren't solutions.

data quality monitoring:

searches the wrong haystack.

Data quality monitors look for changes in stored data, mostly unrelated to strategic, automated decisions.

dcyd hones in on data relevant to decisions that move the business.

model monitoring:

misses the big picture.

Model monitoring sees isolated pieces of the puzzle, and can't connect local performance to business objectives.


dcyd connects data all the way from sources to decisions.

anomaly detection:

too noisy, too needy.

Anomaly detection has no sense of priority and wakes you up for nothing.

dcyd alerts only when anomalies are impacting your business objectives.

is the future of business decision-making @scale.
  • observes data flowing in production.

  • learns behaviors and data dependencies.

  • analyzes the impact on business objectives.

  • alerts only business-critical issues.

better decisions at scale

let's get started

good dcysion!