Governed prediction models
Models with bias testing and records built in.
- 1Tests for unfair outcomes
- 2Documents data and purpose
- 3Monitors in production
Denver, CO · Data & AI Platforms
Data platforms and ML for Denver companies, with bias testing, documentation and monitoring that Colorado's AI and insurance rules call for.
Data & AI Platforms in Denver
Denver's economy spans aerospace and satellite firms, telecom and cable, energy, health systems and a growing software scene. Colorado was the first state to pass a broad AI law covering high-risk decisions, so AI that affects people needs careful design here.
Where it fits
Models with bias testing and records built in.
Link network quality to customer churn.
Built for Colorado rules
Duties to prevent algorithmic discrimination in consequential decisions.
Opt-outs from profiling and assessments for high-risk processing.
Testing to show models and external data do not discriminate unfairly.
Controlled unclassified information kept inside assessed environments, AI tools included.
Safeguards and a business associate agreement for anything touching patient data.
Working together · Mountain Time
Your morning is our evening, so we meet live at the start of your day and build while you sleep.
How we work
We map your data sources, flows, owners and quality issues.
We design a platform that fits your cloud, scale and budget.
We deliver pipelines, models and dashboards in working increments.
We set up monitoring, alerts and governance your team can run.
Yes. Bias tests, data documentation and monitoring results are recorded for each model, which supports the impact assessments and records the law expects.
MLOps is the set of practices and tools for deploying, monitoring and updating machine learning models reliably, much as DevOps does for software. It keeps models accurate as data changes.
We work with the major cloud providers and with on-premise environments, and design the platform around the tools and contracts you already have.
Not always. We often build the data foundations a specific AI use case needs first, then extend the platform as more use cases follow.
Let's talk
We help you navigate Enterprise AI, from first use case to production.
Let's connect