At HighRes®, we are committed to innovation as a core brand promise. This quarterly innovation update details the pace of our innovation as it relates to our digital portfolio.
This second edition covers Q2 2026 and spans a landmark partnership with NVIDIA, significant advances across Cellario OS™ V1.16 and V1.17, the continued development of our AI-powered beta products, and an expanding body of published use cases and integrations that demonstrate the breadth of what Cellario OS is enabling across life science organizations today.
Key Takeaways
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On June 23, 2026, HighRes announced the formal positioning of Cellario OS as the open execution layer for AI Scientists, beginning with an integration with NVIDIA BioNeMo Agent Toolkit at the BIO International Convention. Read the full announcement here.
Agentic life sciences workflows can generate and evaluate experiments at machine speed, but a protocol remains a hypothesis until something runs it correctly and returns trustworthy data. As AI Scientists accelerate hypothesis generation, the constraint shifts to execution. Cellario OS and Cellario Lab Assistant sit between the AI Scientist and the bench, translating scientific intent into physically executed experiments and returning structured, provenance-rich data the model can act on.
A central part of this is capability discovery: an AI Scientist can query the lab through Cellario Lab Assistant for the instruments, assays, methods, and constraints available on the floor. The lab returns a machine-readable capability model so experiments are designed against real-world conditions rather than assumptions. Generated protocols are simulated before any hardware moves, and Cellario OS then orchestrates execution deterministically with full traceability.
NVIDIA BioNeMo Agent Toolkit extends agent-callable AI skills into the physical lab. Cellario OS provides the execution layer that runs experiments and returns results the model can act on (Fig. 1).
We’ve shown already how Lab designer models can be passed through NVIDIA Omniverse to render lab layouts in a physically accurate, photorealistic environment, accessible to both human planners and AI planning tools. See the Lab Designer section for more.
NVIDIA Cosmos powers physical AI capabilities in Perception™, enabling real-time detection of instrument and workflow anomalies, and supporting autonomous recovery actions.
Figure 1. Cellario OS as the open execution layer, the relationship between the NVIDIA and Cellario Stacks for the lab.
A significant development for Cellario Lab Assistant this quarter is the introduction of the Skills architecture - a structured, extensible framework of discrete capabilities that Lab Assistant can deploy in response to natural language instructions. Skills are the building blocks that allow Lab Assistant to take meaningful, context-appropriate action on behalf of the scientist.
Skills are designed to be model-agnostic, meaning they are not tied to any single underlying AI model, and user-buildable. Teams with specific workflows can create and extend Skills to match their own laboratory environment and scientific processes. This is an important design principle: as the AI landscape evolves, Lab Assistant evolves with it, and organizations retain control over the capabilities deployed in their environments.
Error handling and troubleshooting is an example of a Skill in action, and it illustrates exactly why this model is powerful (Video 1). When an instrument encounters an issue mid-run, Lab Assistant deploys its error troubleshooting Skill: it interprets the error state, assesses the context of the running workflow, and guides the operator through recovery steps in plain language. Instructions are step-by-step, appropriate to the specific error type and instrument.
For any co-piloting tool to be genuinely useful in a complex laboratory environment, it must be able to handle the unexpected, not just the plan. The ability to diagnose and guide recovery in real time, without requiring operators to consult documentation or call a specialist, is a core value of the Skills approach. It reduces downtime, lowers the expertise required for independent operation, and builds confidence in the system.
Video 1. Cellario Lab Assistant deploying the error troubleshooting Skill, guiding an operator through instrument recovery using plain language instructions.
Beyond error recovery, Skills in early access include:
Watch Lab Assistant in action, building an orchestration workflow including agent-to-agent Opentrons method building, in our joint webinar here.
Cellario Lab Designer gives teams a 3D workspace to plan and validate laboratory layouts before a single piece of equipment is installed, connecting physical layout with operational logic so teams can identify conflicts, validate throughput, and align on design decisions months before deployment.
Figure 2. Cellario Lab Designer V0.5 showing improved visual quality and the expanded component library.
The Early Access Beta Program is now in active operation, with select partner organizations using Cellario Lab Assistant™, Cellario Lab Designer™, and Cellario Perception™ in real laboratory environments. Feedback from beta partners is directly shaping each product ahead of general availability.
Lab Assistant brings conversational AI to the Cellario platform - scientists interact with their lab in natural language, from workflow creation to real-time error recovery. Lab Designer accelerates lab planning and validation in a 3D environment, compressing months of pre-deployment work into days. Perception improves automation reliability through real-time machine vision, enabling systems to detect and respond to unexpected conditions autonomously.
We are continuing to recruit new beta partners across all three products. If your organization is interested in early access and the opportunity to shape what these tools become ahead of general release, we welcome the conversation.
→ Express interest in the Early Access Beta Program
In our Q1 update we introduced Cellario Scheduler 4.5 as an upcoming capability. It is now fully released and we want to highlight it again because it represents a genuine inflection point for how laboratory protocols are designed and optimized.
The headline capability is a set of RESTful API endpoints that enable the programmatic creation, modification, and optimization of laboratory protocols through automated agents and intelligent systems (Fig. 3). These type-safe APIs support the full spectrum of protocol design, from creating complex multi-threaded workflows to dynamically adjusting parameters, resources, and timing constraints based on real-time experimental feedback.
Figure 3. Cellario Scheduler 4.5 screenshot of the new Simulation API endpoint to queue up a simulation.
This moves protocol development from static, manually designed workflows to dynamic, self-optimizing processes. Research teams can deploy agents that monitor experimental results, identify bottlenecks, and automatically generate protocol variants for testing, all while maintaining full audit trails. For laboratories running Design-Make-Test-Analyze (DMTA) cycles, this is the infrastructure that allows the loop to close programmatically rather than manually.
Looking ahead, Cellario Scheduler 4.5 will also unlock additional functionality within Cellario Lab Assistant in the coming weeks, specifically, simulation and protocol editing capabilities that allow scientists to model and refine scheduled protocols before committing them to execution. This is the next meaningful step in connecting the AI interface directly to the scheduling layer.
Download the full Cellario Scheduler 4.5 release notes here.
Two releases of Cellario OS have shipped since the Q1 update: V1.16 (April 16, 2026) and V1.17 (June 10, 2026), with a V1.17.1 patch following on July 12. Together they represent significant advances in workflow capability, developer tooling, and the breadth of connected extensions.
One of the largest areas of focus is broadening the capability set of an orchestration workflow. A workflow is a digitized representation of all of the steps required to complete an experiment. It comprises steps such as protocol – to call upon a scheduler run; guided tasks for operator interventions; direct device operations to directly control instruments; scripts and flow and logic control with decisions and loops. An example workflow can be seen in Figure 4.
Figure 4. An example DNA Assembly and quality assessment workflow, showing a complete orchestrated workflow.
Scheduling workflows to run at a future time has long been possible through Cellario Scheduler. V1.17 extends this capability across the full workflow experience in Cellario OS, with a block-calendar interface, conflict detection, reschedule support, and cancel-with-reason semantics (Fig. 5). Labs can now plan and commit workflows in advance, coordinate resources across teams, and manage capacity deliberately, without requiring all orders to be started in real time.
Figure 5. Workflow calendaring in Cellario OS V1.17 scheduling pending workflow orders across a calendar view with conflict detection.
Users can now author workflow scripts in Python, a significant expansion of the scripting environment that opens the platform to a much wider range of developers and technically capable users (Fig. 6). Scripts can be edited directly in-browser through a new web editor, or via a dedicated VSCode extension for teams who prefer a local development environment. Error messages from remote scripts are surfaced clearly in the OS UI, reducing debugging overhead substantially. Together, these changes make Cellario OS a meaningfully more open and developer-friendly platform.
Figure 6. Python workflow scripting in Cellario OS V1.17 in-browser editor showing a workflow script with real-time error feedback.
Workflow steps can now run in parallel branches within a single workflow. A new container experience, compiler validators, and runtime state management allow concurrent execution paths to be modelled and run through the orchestration layer, enabling genuinely parallel laboratory operations rather than forcing sequential execution where it is not required.
Cellario OS now supports recovering in-progress workflow runs after interruption. When a run is disrupted by a network event, device error, or system restart, the orchestration layer can resume from where it stopped rather than requiring a full manual restart. This meaningfully improves reliability for long-duration or complex workflows.
V1.16 established the Latest Workflows foundation: tighter integration between Cellario OS and Cellario Scheduler 4.5 through a cloud scheduler deployment model and scripting environment infrastructure. This is the technical foundation that the advanced V1.17 workflow capabilities are built on.
V1.16 and V1.17 have both advanced the depth of Cellario OS connector support. The following extensions have been updated or added in these releases, for a broader view of the platform's connector ecosystem, see the Growing Network of Connectors section below.
Full Limfinity biobanking LIMS integration is now delivered through the Cellario OS Extension Service, consolidating the integration into the standardized extension framework and simplifying deployment and maintenance for organizations using Limfinity as their sample management platform.
The Mosaic by Cenevo and Scigilian extensions have been updated across both releases, including a backport of the extensions core to Scigilian and dedicated development, QA, and demonstration environments for Mosaic. These updates build on the dose-response capabilities delivered in V1.15, deepening the integration with the scientific software tools used in drug discovery and sample management workflows.
Operators can now navigate guided tasks hands-free, with auto-scroll that follows workflow progress, improved barcode scanning, and focus-follows-progress behavior. Inventory position guidance has also been added, directing users to specific labware positions within the step-by-step flow. Both changes make Cellario OS more practical in environments where operators have their hands occupied with physical lab work.
With over 500 instrument and device drivers, one of the largest libraries of its kind in the industry, plus a growing set of deep software integrations, Cellario OS increasingly serves as the connective layer between the physical laboratory and the digital ecosystem around it. The integrations highlighted in the Cellario OS V1.16 and V1.17 section above are part of this broader network. For a deeper look at how Cellario OS functions as the integration layer that brings these connections together, see the Cellario OS as an Integration Layer section below.
The Benchling integration connects Cellario OS directly to Benchling's ELN. Scientists initiate runs from within Benchling, Cellario OS executes the workflow on the robotic system, and structured results flow back into the notebook automatically, eliminating manual data handling between bench and analysis. Watch the full demo and our recent webinar with the Benchling team.
HighRes and Opentrons demonstrated the industry's first agent-to-agent laboratory workflow. Cellario Lab Assistant communicating directly with the Opentrons AI via MCP server to generate protocols on behalf of another AI system. The demonstration covered a complete qPCR workflow from natural language intent to analyzed results. Watch the full demo in our recent webinar with the Opentrons team.
Mosaic by Cenevo is one of Cellario OS's most deeply integrated connector partners, with the integration enabling end-to-end dose-response and compound management workflows. As updated in V1.17, Mosaic now has dedicated development and QA environments within the OS extension framework, supporting more robust deployment and ongoing development of the integration. Watch the full demo in our recent webinar with the Cenevo team.
The Scigilian extension has been updated and brought into the standardized extension architecture, ensuring it benefits from the same reliability improvements and SDK tooling as other Cellario OS connectors.
Full Limfinity integration, delivered via the Cellario OS Extension Service in V1.17, gives organizations using Limfinity for biobanking and sample management a native, standardized path to connect their workflows to Cellario OS execution.
Figure 7. The Cellario OS connector ecosystem spanning ELNs, LIMS, sample management platforms, informatics tools, and AI Scientist platforms, underpinned by 500+ instrument drivers.
As the Cellario OS customer base grows and deployments deepen, a richer picture is emerging of the patterns in which the platform is being used. Three are now particularly well-documented.
The most established use case is Cellario OS as the orchestration layer for an integrated drug discovery automation facility, coordinating robotic systems, scheduling instruments, managing sample logistics, and returning operational data to the informatics infrastructure. Pfizer's High-Throughput Screening group shared their experience at SLAS2026, commissioning three Nucleus® automation systems within a newly renovated HTS lab and running cell-based, biochemical, and automated imaging workflows in parallel. Read the full story.
In many modern deployments, Cellario OS does not surface as the primary user interface at all. Instead, it runs as the invisible backbone - the driver layer that connects instruments, coordinates workflows, captures execution data, and exposes everything through a single unified API (Fig. 8). Digital applications, ELNs, and AI tools interact with the physical lab through that API without end users ever opening the Cellario interface.
This headless deployment model addresses a fundamental challenge: while the digital layer of the modern lab has become increasingly sophisticated, the physical lab remains fragmented. Instruments speak different languages, automation systems operate in silos, and translating digital intent into physical execution still requires complex, brittle integrations. Cellario OS resolves this by acting as the translation engine - a standardized execution layer that sits beneath whatever digital ecosystem an organization has already built.
The Cellario OS API is fully Swagger-documented, and the platform ships with SDK tooling that makes building on top of it accessible to development teams across the organization. Real-world integrations with Benchling, Genedata, Scigilian, Mosaic by Cenevo, and Limfinity, plus numerous custom-built internal systems, demonstrate the model in production. Read the full integration layer blog.
Figure 8. Cellario OS as the universal operating layer, bridging the physical laboratory and the digital ecosystem through a single API.
Sample logistics is a core application area for Cellario OS, particularly in drug discovery environments where dose-response experiments and compound management are foundational. Through the Mosaic by Cenevo integration, Cellario OS tracks sample location, consumption, and transformation in real time as samples move through automated and manual workflows - maintaining a live chain of custody without requiring separate integrations to each individual instrument or storage system.
Get in Touch
For a demonstration of any of the capabilities in this update, or to learn more about the Early Access Beta Program, please get in touch.
→ Express Interest in the Beta Program