Enterprise AI, from strategy to production
Minneapolis, MN · Data & AI Platforms
Data platforms and ML for Twin Cities companies, from store demand and supply chains to claims and device quality data, with explainability built in.
Data & AI Platforms in Minneapolis
The Twin Cities host an unusual number of national headquarters: big-box retailers, one of the largest health insurers, medical device makers, food and agribusiness giants and regional banks. Minnesota's privacy law also gives people the right to question decisions made by profiling.
Where it fits
Better forecasts for every store and item.
Crop, commodity and production data in one view.
Built for Minnesota rules
A right to question profiling decisions and see the data behind them.
Safeguards and a business associate agreement for anything touching patient data.
Software that informs diagnosis or treatment may itself be a regulated device.
A written security program covering every system that handles customer financial data.
Working together · Central 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. We record the key factors behind each prediction, so your team can explain a decision and correct the data if a customer asks.
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