A modern lab can run a sequencer in hours and then wait three days for someone to approve the reagent order that feeds it. As R&D scales across teams and sites, this pattern spreads.
The delays live between the steps: the requests, approvals, handoffs, and instrument access that still move through email and spreadsheets. Automating lab workflows is how labs cut that friction.
The catch is that “lab workflow automation” covers several different things, and buyers mix them up. Some tools automate the science, the experiments, and the data. Others automate the physical instruments through robotics. A third kind automates the operational work that keeps the lab running. A tool that is excellent at one is often absent from another.
This article sorts the category into the kinds of automation that actually exist, compares five tools that lead in each, and shows which lab each one fits. It is not the full workflow-management buyer’s guide, and it is not a Benchling-versus comparison. Each tool is here for what it automates.
The best lab workflow automation tools in 2026 depend on what you are automating.
- For operational workflows (requests, scheduling, maintenance): newLab®.
- For scientific and experiment workflows: Benchling.
- For configurable, no-code workflows across ELN and LIMS: Scispot.
- For physical instrument automation: Biosero Green Button Go.
- For general, lightweight coordination: Smartsheet.
What automating lab workflows actually means
“Lab workflow automation” sounds like one category. In practice, it is four, and knowing which one you need saves you from buying the wrong tool.
Scientific workflow automation handles the experiment itself:
- Capturing data,
- Tracking runs,
- Templating protocols, and
- Moving results between scientists.
This is the ELN and informatics layer, and it is where most life-sciences teams start.
Physical automation, often called lab automation, drives the hardware. Liquid handlers, robotic arms, and integrated workcells run and schedule themselves through orchestration software.
This matters most in high-throughput environments like genomics and drug discovery, and it is a different problem from the software workflows above.
Operational workflow automation handles the work around the science: service requests, equipment booking, maintenance, and the coordination between scientists, lab operations, and IT. This is the layer that most often still runs on email and shared calendars, even in labs with modern ELNs and robotics.
General work management covers none of these specifically. These tools let a team build custom workflows by hand, with no lab context built in.
Most labs need more than one. A team can run an ELN for experiments, a robotic platform for high-throughput assays, and still lose a day chasing a broken instrument because the service request sat in someone’s inbox. The tools below each lead in one of these layers.
How to choose a lab workflow automation tool
The category is broad, so the place to start is the layer you need to automate. These five checks narrow it down.
- Name the layer you are automating. Decide whether the bottleneck is the science, the physical instruments, the operational work around them, or general coordination. Buying a robotics orchestrator to fix a service-request backlog wastes money, and so does the reverse.
- Check how it connects to what you keep. Most labs already run an ELN, a LIMS, or instrument software, and they are not replacing all of it. Confirm the tool integrates with the systems you are keeping rather than adding another island.
- Look at configurability without code. Ask whether your team can build and change workflows themselves, or whether every change needs a developer or a vendor ticket. Labs that cannot adjust their own workflows tend to stop using the tool.
- Test it across sites and teams. A workflow that works for one lab often breaks when a second site, a shared instrument, or a cross-team handoff enters the picture. Run a real multi-site scenario before you commit.
- Count the admin load and the full cost. Add configuration, training, and the internal time to run the tool to the license fee. A tool that needs constant babysitting can cost more than a pricier one that runs quietly.
1. newLab®
newLab® automates the operational layer: the requests, scheduling, and maintenance work that surrounds the science. It runs natively on ServiceNow, which lets an organization extend the enterprise workflows it already uses into the lab instead of standing up another disconnected system.
The tools most labs buy first automate experiments or instruments. The operational work stays on email and spreadsheets, and that is usually where the time goes. newLab® moves that work into one system where a request has an owner, a booking respects a maintenance window, and lab, IT, and finance see the same equipment record.
- newLab® automates lab service requests, so a reagent order or a repair no longer sits unowned in an inbox and everyone can see its status.
- It automates equipment scheduling and booking against live equipment status, so a reservation does not land on an instrument that is down for maintenance.
- It ties those workflows to equipment and asset data, which keeps planning and coordination accurate across sites and teams.
- It structures the operational data these workflows produce for downstream use, the groundwork for AI-ready lab infrastructure, without capturing or storing scientific data.
newLab® does not drive instruments or robotics, and it does not replace an ELN or a LIMS. ELNs and LIMS automate experiments and scientific data. Robotic platforms automate physical instruments. newLab® automates the operational layer around both, and the three work together. It fits enterprise and multi-site R&D that has modernized the science but still runs operations by hand.
2. Benchling
Benchling automates scientific workflows. It captures experimental data, tracks runs, templates protocols, and keeps molecular biology and assay work organized, which is why research teams across life sciences adopt it.
Its automation is strong inside the scientific domain and thin outside it. Benchling coordinates the experiment; it does not manage the service requests, equipment scheduling, or cross-functional operations that sit around the experiment. Teams that need those usually run Benchling for the science and something else for the operations.
The best fit is a research team whose day runs on experiments, not operations.
3. Scispot
Scispot automates lab workflows through a configurable, API-first platform that combines ELN and LIMS functions. Its draw is configurability: teams model their own workflows and connect the pieces through the API, often without writing code, which suits labs that cannot commit a developer to every change.
The flexibility has a cost. Configuration takes real effort up front, and as a newer vendor, Scispot has a smaller install base than the incumbents. Labs that want a system they shape themselves get a lot here; labs that want something rigid and proven may look elsewhere.
4. Biosero Green Button Go
Biosero Green Button Go automates physical instruments. It orchestrates liquid handlers, robotic arms, and integrated workcells, scheduling and running them together as coordinated pipelines. In high-throughput genomics, proteomics, and drug discovery, this is what “automation” usually means.
This is a different category from the software-workflow tools above, and it is worth naming clearly. If your bottleneck is physical throughput, a robotics orchestrator like Green Button Go solves it. If your bottleneck is coordination and operations, it does not, and pairing it with an operational layer is common.
It belongs in high-throughput labs where the work is physical instrument automation.
5. Smartsheet
Smartsheet is a general work-management platform that some labs adapt for workflow automation. Its flexibility lets a team build custom trackers and simple automations without specialized lab software, which appeals to groups that want something lightweight and familiar.
The limit is lab context. Smartsheet does not know what an instrument, a calibration record, or a service request is, so a team has to build and maintain all of that by hand, and it gives no visibility into lab resources on its own. It works for teams that want lightweight, custom coordination, not a lab-specific system.
Lab workflow automation tools compared
What each tool automates, the lab it fits, and where its automation stops.
| Tool | Type of automation | What it automates | Best-fit lab | Where its automation stops |
|---|---|---|---|---|
| newLab® | Operational | Service requests, scheduling, maintenance, coordination | Enterprise multi-site R&D | Does not run instruments or capture scientific data |
| Benchling | Scientific | Experiments, data capture, protocols | Experiment-driven research teams | Operational and cross-functional workflows |
| Scispot | Configurable ELN/LIMS | Custom, no-code lab workflows | Teams that self-configure workflows | Setup effort; smaller install base |
| Biosero Green Button Go | Physical / robotic | Liquid handlers, robotic arms, workcells | High-throughput automation labs | Operational and software workflows |
| Smartsheet | General work management | Custom trackers, simple automations | Lightweight coordination | No lab context; manual setup |
Which tool fits your lab
Automating lab workflows starts with naming the layer, because no single tool owns all of them. Match the tool to the bottleneck. If the science is slow, look at Benchling or a configurable platform like Scispot. Physical throughput points to a robotics orchestrator like Biosero Green Button Go.
A team that just wants to build its own trackers can use Smartsheet. And if the bottleneck is the operational work, the requests, the bookings, and the maintenance that still run on email, that is the layer newLab® automates.
Most enterprise labs have already modernized the science and the instruments. The operational layer is the one still waiting. If that sounds like your lab, book a demo, and we will show you how newLab® automates it on ServiceNow, alongside the tools you already run.
FAQs
What is lab workflow automation software?
Lab workflow automation software replaces manual, email-and-spreadsheet processes with structured digital workflows teams can track and scale. The term covers several layers: automating experiments, automating physical instruments, and automating the operational work around them. Which one you need depends on where your lab loses the most time.
What is the difference between lab workflow automation and lab automation?
People often confuse the two. Lab automation usually means physical automation: robots, liquid handlers, and instruments that run themselves. Lab workflow automation is broader and includes the software and operational workflows, the requests, approvals, scheduling, and handoffs, that coordinate the people and the work.
Can you automate lab workflows without coding?
Yes, with configurable or no-code tools. Platforms like Scispot let teams build and change workflows themselves, and operational platforms like newLab® configure requests and scheduling without development. The trade-off is that more flexibility usually means more upfront setup time.
What is the best lab workflow software?
There is no single best tool, because they automate different layers. For experiments, Benchling leads; for configurable ELN and LIMS workflows, Scispot; for physical automation, Biosero Green Button Go; for operational workflows, newLab®; and for lightweight coordination, Smartsheet. Start by naming the layer you need to automate.
Is newLab® a lab workflow automation tool?
Yes, for operational workflows. newLab® automates service requests, equipment scheduling, and maintenance coordination across sites, built natively on ServiceNow. It does not drive instruments or capture scientific data, so it works alongside your ELN, LIMS, and any robotics.
How is newLab® different from a LIMS or an ELN?
An ELN or a LIMS automates the science: experiments, samples, and scientific data. newLab® automates the operational layer around the science: the requests, bookings, and maintenance that keep the lab running. The two solve different problems and are commonly used together.
Does lab workflow automation replace my LIMS or ELN?
No. Most workflow automation, including newLab®, covers a different layer from your ELN or LIMS and connects to it rather than replacing it. The goal is to remove coordination friction, not to rip out the systems that already work.
