Blog
From chaos to science
At Tessel, we build neural developer tools that transform experimental chaos into systematic insight for AI developers, while enabling healthcare institutions to rigorously evaluate AI before procurement.
August 23, 2025
The Trust Gap: How Hospitals Can Safely Adopt Pathology AI
Pathology AI achieves human-level accuracy yet clinical adoption stalls. Hospitals lack frameworks to assess real-world performance beyond vendor benchmarks. Misaligned stakeholders—admins wanting ROI, pathologists fearing displacement, IT assessing infrastructure—can't build trust without evidence. Our tools expose AI's blind spots before deployment and predict real-world performance in your specific environment. Stop guessing where AI works or fails in your hospital—know exactly.
Read MoreAugust 21, 2025
Case Study: Automatic Label Error Detection with Tessel SDK
Label errors are a common yet overlooked source of brittleness in medical imaging and pathology. Systematic mislabels push models toward spurious patterns, hurting generalization and causing failures in production. Our SDK automatically spots these issues with representation analysis during training, flagging suspicious samples in the background with no extra work—saving expensive debugging cycles and valuable pathologist time.
Read MoreAugust 12, 2025
Beyond Benchmarks – A New Paradigm for Building Trustworthy Pathology AI
In digital pathology, benchmarks rarely demonstrate how models behave in various hospital settings. We need to develop a working theory of how models behave—how they react to different data sources, artifacts, and conditions. A hypothesis-driven process that combines systematic stress testing with neural representation analysis can map these behaviors, explain their causes, and guide targeted improvements.
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