Regard vs OpsLevel
Side-by-side comparison of AI visibility scores, market position, and capabilities
NYC healthcare AI clinical insights at $350M valuation Jul 2024 with 3M+ diagnoses surfaced and $50M+ incremental revenue for partners; $81.3M total ($61M Oak HC/FT Series B) serving Banner Health and Sentara competing with Nuance CDI.
About
Regard is a New York-based healthcare AI company — backed with $81.3 million in total funding including a $61 million Series B in July 2024 led by Oak HC/FT with Cedars-Sinai Health Ventures at a $350 million valuation, following a $15.3 million Series A in 2022 and $5 million seed in 2021 — providing health systems with an AI clinical insights platform that analyzes 100% of hospitalized patient medical record data to surface missed diagnoses to care teams, acting as an AI co-pilot for physicians that has surfaced 3 million+ diagnoses and generated $50+ million in incremental revenue for health system partners through improved documentation accuracy. Founded in 2019 by Eli Ben-Joseph, Nate Wilson, and Thomas Moulia (Stanford graduate students) and launched in 2021, Regard serves major health systems including Banner Health (33 acute care hospitals) and Sentara Health (12 hospitals).
OpsLevel is a developer portal and service catalog for tracking service ownership, maturity scorecards, and production readiness across microservices.
About
OpsLevel is a developer portal platform that gives engineering organizations visibility into the services they operate, who owns them, and how mature they are relative to internal engineering standards. At its core, OpsLevel maintains a service catalog that maps every microservice, repository, and infrastructure component to a team owner, populating metadata automatically from integrations with GitHub, GitLab, PagerDuty, Datadog, and cloud providers. This catalog becomes the authoritative source of truth for answering questions like who to contact about a service, what tier of reliability it requires, and what dependencies it has — questions that are often unanswerable at engineering organizations that have grown past the point where everyone knows everything.
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