The roadmap advances the Clinisys Connected Laboratory Intelligence value chain through a compounding maturity progression that shifts the laboratory from a static System of Record focused on descriptive insight, to a System of Workflow standardizing task execution, to a System of Intelligence optimizing operations via prediction and anomaly detection, and ultimately to an agentic System of Orchestration that executes workflows under human approval. CTO Shay Hassidim noted that this framework ensures every laboratory decision—from sequencing specimens to advancing therapeutic discovery—is informed by governed, generative AI grounded in trusted laboratory context while maintaining clinicians in full control.
Rather than locking healthcare organizations into a single proprietary ecosystem, Clinisys established two open foundation paths running on the Clinisys Laboratory Solution Extended API and shared platform services. The CLS Model Context Protocol foundation adopts the emerging MCP standard to allow advanced IT teams to safely connect approved enterprise AI assistants to governed laboratory information with strict organizational permissions, guardrails, and auditability. In parallel, the CLS NoCode AI foundation leverages pre-built components to let frontline lab teams configure automated, governed workflows—such as reflex testing, result verification, and corrective actions—without writing software code. These capabilities are intended to scale across a planned Clinisys AI Marketplace that will distribute certified agents, skills, and third-party extensions.
The broader strategy organizes shared AI capabilities into five targeted outcome domains, spanning embedded Workflow Copilots, conversational and predictive Advanced Analytics, automated specimen and turnaround-time Orchestration, the AI Marketplace, and an Intelligent Lab Command Center designed to unify instrument telemetry and agent oversight.
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