Clinisys, a global provider of laboratory informatics solutions, has unveiled its AI Innovation Roadmap: an open, governed platform strategy that connects laboratory data, analytics, AI agents and workflow automation.
Facing workforce, financial, technology, cyber and data-governance pressures, laboratories need more than isolated AI features.
Clinisys aims to provide a connected intelligence layer that supports action while keeping people in control.
The roadmap advances laboratories from systems of record to workflow and intelligence, then to orchestration.
Each stage builds on trusted data, moving from descriptive insight to prediction, anomaly detection and agentic workflows with human approval.
“Every laboratory decision, from the next sample to run to the next therapy to develop, should be informed by governed AI built on trusted laboratory data,” said Shay Hassidim, Chief Technology Officer, Clinisys.
Open by design
Two complementary foundations are planned. CLS MCP is being designed to connect approved AI assistants to governed laboratory context through CLS APIs, with permissions, guardrails, audit and observability.
CLS NoCode AI, built around Decisions, is intended to help operational teams configure workflows using reusable templates and connectors for processes such as reflex testing, result review and corrective action.
Both paths are designed to build on the CLS Extended API and shared services for data, analytics, governance, integration and workflow execution, supporting reuse across CLS and selected Clinisys core products.
Five customer-value initiatives
The roadmap spans Workflow Copilots, Advanced Analytics, Automation and Orchestration, a planned AI Marketplace for certified agents and templates, and a future Intelligent Lab Command Center combining alerts, instrument monitoring, agent supervision and decision support.
Agents in action
The Analytics Agent is designed to guide authorised users through Ask, Visualise, Analyse, Export and Schedule, enabling exploration of governed CLS data and recurring information delivery aligned to roles and permissions.
Equipment Care applies instrument activity, quality-control data, service history, maintenance requirements and workload to equipment-readiness workflows.
Intended outcomes include earlier issue detection, fewer avoidable reruns and more time for laboratory professionals.
“The advantage is not a single agent,” added Prashant Prabudh, Director, AI Analytics and Agentic Platforms, Clinisys.
Release-specific availability will be communicated following readiness and approval reviews. Quantified outcomes and standards claims will be added once validated.
