LLMs made old languages newly useful: COBOL for mainframes, Fortran for scientific code, and Rust, SQL, and Prolog as strict substrates for agentic systems. Healthcare has its own old language hiding in plain sight: X12. Before LLMs, X12 was mostly treated as ugly plumbing: loops, delimiters, companion guides, clearinghouse edits, payer-specific quirks, rejections, and acknowledgments. In an agentic workflow, those constraints become the feature. They give stochastic agents a deterministic target. This talk shows how healthcare agents can compile messy operational evidence into X12-shaped workflows: chairside audio into 837D claim narratives, imaging systems into 275/PWK attachment flows, payer portals and phone calls into 270/271 eligibility and 276/277 claim status, preauth evidence into 278 workflows, and EOBs, scanned mail, and bank data into 835/820 payment reconciliation. The core pattern is simple: LLMs reason over ambiguity; X12 provides the syntactic and semantic harness for validation, auditability, acknowledgments, rejections, human review, and high-volume automation. This is not an EDI nostalgia talk. It is a production architecture talk about building reliable agents in one of the messiest enterprise domains.
AI in Healthcare sessions at AI Engineer World's Fair 2026 in San Francisco.
Thursday, July 2, 2026
1:55 PM - 2:15 PM·20m
Track 7 · Room 2024
Capacity: 250 attendees
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Vasant Kearney
CEO
Onlay AI
@vasantkearney
Vasant Kearney is CEO of Onlay AI, where he builds agentic healthcare revenue-cycle infrastructure across claims, eligibility, attachments, payer follow-up, payment posting, and bank reconciliation. He previously co-founded and served as CTO of Retrace, an AI company in healthcare automation. Before startups, Vasant was an Assistant Professor in Radiation Oncology at UCSF, completed a UCSF medical physics residency, and earned a PhD in Biomedical Engineering. He mentored radiation oncology residents at UCSF and machine learning students at USF. His scientific work spans a broad range of topics, including generative MRI-to-CT translation, tumor localization, anatomy segmentation, treatment-planning optimization, Nvidia CUDA programming, and dental disease classification. Vasant has published numerous peer-reviewed healthcare AI papers and served as a reviewer and associate editor for high-impact journals. His work sits at the intersection of healthcare operations, regulated workflows, multimodal AI, and production agent systems.