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Intelligence for the regulated world

Research, guides, and perspectives on AI in healthcare, finance, and science.

Healthcare AIFeatured

Why Explainable AI is No Longer Optional in Healthcare

As CMS and FDA tighten their guidance on clinical decision support tools, healthcare teams face a new mandate: if your AI makes a recommendation, you must be able to explain it. Here's what that means in practice.

8 min readApril 28, 2026
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Query Intelligence

Natural Language to SQL in Regulated Environments: A Safety-First Approach

Giving non-technical users the ability to query production databases sounds dangerous. It doesn't have to be. We break down the guardrails that make NL-to-SQL safe for healthcare and financial data.

6 min readApril 14, 2026
Finance AI

The Hidden Cost of Bad Data in Financial Services

A single corrupted field in a risk model can cascade into millions in mis-priced exposure. We analyzed 50 production data incidents to understand where financial data quality breaks down — and how to catch it earlier.

10 min readComing soon
Machine Learning

Beyond SHAP: A Practical Guide to Root Cause Analysis for ML Models

SHAP values tell you which features mattered. But they don't tell you why a specific prediction was wrong, or how to fix it. This guide covers the techniques we use in Decision Intelligence to go deeper.

12 min readComing soon
Healthcare AI

Building HIPAA-Compliant AI Infrastructure: What We Learned

After two years of deploying AI in hospital systems, we've accumulated a playbook for infrastructure that actually passes audit. This is the guide we wish we'd had on day one.

9 min readComing soon
AI Infrastructure

AI Observability: What It Actually Means for Production Systems

Observability for software means logs, metrics, and traces. For AI systems, it's more complex. We define what meaningful AI observability looks like when models are making consequential decisions.

7 min readComing soon

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Intelligence for the regulated world

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