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Inside χ-Bench’s healthcare workflows
A benchmark for complete healthcare workflows across providers and health plans.
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Research, engineering, and ideas from Actava.ai.
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How Cura 1T learns through evaluation
How evaluation failures guide training data for a healthcare foundation model.
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Training specialized models with Model Factory
How verified workflow experience supports training and checkpoint selection.
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19 articles
CompanyIn the news
Claude, GPT, and Gemini Fail 72% of the Time in Medical Settings! The Brutal Truth Exposed by CHI-Bench: Can AI Agents Can't Be Used in Hospitals?
A benchmark released yesterday (May 20, 2026) sent shockwaves through the AI industry. Thirty AI agents — including the latest Claude, GPT-5.5, and Gemini — failed 72% of the time on U.S. medical workflows.
Company6 min read
Actava.ai publishes CHI-Bench
The research release introduces an interactive benchmark for long-horizon healthcare workflows and reports limitations under its evaluation protocol.
CompanyIn the news
Claude, GPT, Gemini Agents Fail 72% of U.S. Healthcare Workflows, New Benchmark Finds
AI labs position agents as ready for long workflows, but until now no public benchmark validated that claim in healthcare, where one missed policy check can mean a denied authorization, delayed treatment, or audit finding. Each trial in CHI-Bench runs an agent for 60-80 steps across four to six clinical stages, exposing 21 healthcare apps through 200+ MCP tools and a 1,279-document operations handbook. It evaluates the trajectory, every artifact, and world state using deterministic unit tests and LLM judge for evidence grounding, consent, and cross-stage consistency.
CompanyIn the news
Claude, GPT, Gemini Agents Fail 72% of U.S. Healthcare Workflows, New Benchmark Finds
Across the 30 frontier agents tested, Anthropic's Claude Code with Opus 4.6 achieved the best overall performance at 28% pass@1, followed by OpenAI's Codex with GPT-5.5 at 21%. By domain, utilization review reached 41%, care management 32%, and prior-authorization paperwork 29%. Reliability remained a major issue, with no agent clearing 20% when the same case was run three times. Under endurance testing, where agents were asked to handle 25 cases in one session, the best system completed under 4%. In a fully end-to-end setting, where one AI submitted a prior-auth request and a second acted as the UM reviewer, no task passed successfully.
Company3 min read
Introducing Actava.ai’s AI governance tools
The launch announcement outlines framework assessments, policy management, and evidence collection around agent operations.
CompanyIn the news
ACTAVA.ai Launches CHRYSO AI Compliance Solution
ACTAVA now offers a purpose-built solution to test and monitor AI agents against real, accepted standards. CHRYSO offers radically simplified AI policy management, team training, and agent testing. An enterprise-level suite integrates policy management, virtual training, and a specialized Agent Registry helps organizations mitigate legal and ethical risks. By providing real-time monitoring and automated control evidence, CHRYSO ensures AI agents remain compliant with critical standards, including NIST AI RMF, HIPAA, CMS HEI, and ONC HT1.
Company2 min read
Actava.ai at the Suncoast Gateway Conference
An April 2026 company announcement covering participation in the conference’s healthcare AI discussion.
Company1 min read
Haolin Chen on environments for agent evaluation
Why realistic tools, intermediate decisions, and outcome criteria matter when evaluating enterprise agents.
Company1 min read
Tao Xia on infrastructure for reliable agents
Observability, failure isolation, and traceable boundaries around probabilistic models.
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