Resources
Insights on building AI that runs real operations
White papers, field notes, and frameworks from the team building the governed layer for enterprise operations.
Featured white papers
Industry AnalysisJul 2026
The Model Is Not the Product: Why Reliable AI Runs on an Ontology
A short argument and a surprising result. The usual fix for unreliable AI agents is a bigger model. We think it is the layer around the model, and we ran the experiment to prove it. The full data and methodology are in the Technical Report.
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Illustration Industry AnalysisApr 2026
The Cost of Intelligence Has Collapsed. The Cost of Execution Is at an All-Time High.
Custom AI demos in 15 minutes. Models too capable to release. The gap between what's possible and what's safe to deploy has never been wider, and it's reshaping how enterprises should think about technology partnerships.
Read the paperIndustryMar 2026
The Executive Guide to Enterprise Agentic AI
Lessons from over 100 conversations with mid-market and enterprise stakeholders on what actually determines success with agentic AI, from pace of change to partner selection.
Read the paperEngineeringJan 2026
Why We're Building OrgBench™: You Don't Need AGI to Get AGI-Level ROI
High IQ doesn't predict success. Neither does raw model intelligence. The real bottleneck is orchestration, and that's why we're building OrgBench™.
Read the paperEngineeringDec 2025
Harness Engineering: How We Make AI Reliable for Supply Chain Operations
Why smarter AI models alone won't solve reliability problems, and how we turn probabilistic AI into deterministic performance.
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