Workstream Intelligence

Problem:
We can't catch avoidable mistakes early
in a data science project's maturity.

If this sounds familiar, you're not alone.

Many teams detect problems with their datasets, policies, and models once it's too late.

Workstream Intelligence automates the detection of potentially problematic data science scenarios and empowers you to take back control.

Automatically detect high-risk data science situations like fairness and explainability violations before they become problematic.

Workstream Intelligence monitors and automatically flags potential issues. Catch mistakes earlier in a project’s lifecycle and improve your ROI and deployment velocity.

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See the invisible.

If you don't know how things connect, you can't predict how they interact.

Our proprietary inference engine detects problematic relationships:
between your datasets, models, workflows, people, and processes.

Catch problems before they happen.

Efficacy

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Execute Data science workflows effectively. Recall fewer systems from prod. Deal with less unacceptable and unexpected behavior.

Velocity

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Projects move quickly from concept to production with clear expectations and requirements, coordination, and high visibility.

Consistency

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Follow predictable standards and best-practices that everyone agrees on.

Continuity

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Known data failure modes are analyzed and small steps are constantly taken to prevent them.

Knowability

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An automated papertrail of how your people, processes, and tools worked together.

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Mission Control

An initiative of AIRL:

The Artificial Intelligence Responsibility Laboratory,
Public Benefit Corporation.

(c) 2022.

Made with love in Los Angeles, San Diego, and Abuja.