Data freedom & integration in laboratory automation

Data ownership determines who controls access, format, and future usability of your experimental and process data.

In automated labs, this becomes critical because:

• Data is generated continuously across instruments, robotics, and software systems
• Long-term projects rely on historical data remaining accessible and usable
• IT and digital teams need flexibility to integrate, analyse, and scale systems over time

If data is locked into vendor-specific software or formats, it can limit your ability to migrate systems, adopt new tools, or meet evolving compliance requirements.

Open integration refers to the ability of automation systems to connect easily with your existing and future software stack without requiring proprietary restrictions.

In practical terms, this includes:

• Standardised interfaces such as REST APIs
• Compatibility with common platforms like LIMS, ELNs, MES, and ERP systems
• The ability to exchange data in widely recognised, non-proprietary formats
• Flexibility to integrate third-party instruments, labware, and software

An open integration approach allows automation systems to fit into your digital ecosystem, rather than forcing your ecosystem to adapt around them.

Labman systems are designed as open, configurable platforms rather than closed ecosystems.

Key characteristics include:

• BaseApp software architecture that supports custom workflows and external system connectivity
• API-first approach, enabling integration with LIMS, ELNs, MES, and ERP platforms
• Use of non-proprietary labware and hardware interfaces wherever possible
• Modular system design that allows changes and extensions over time

This approach ensures that data can move freely between systems and remain accessible beyond the lifespan of any single platform.

Some automation solutions are designed around tightly controlled ecosystems, where:

• Software, hardware, and consumables are interdependent
• Integration with external systems may be limited or require additional licensing
• Data access may depend on vendor-controlled tools or formats

In contrast, an open approach:

• Avoids dependency on a single vendor for upgrades or expansions
• Supports integration with existing and future tools
• Reduces the risk of needing to replace entire systems when requirements change

Vendor lock-in can introduce both operational and financial risks over time:

• Limited flexibility to adopt new technologies or workflows
• Higher long-term costs (OPEX) due to licensing, upgrades, or proprietary consumables
• Complex migrations if you need to move away from the system
• Data accessibility challenges, particularly for long-term projects or audits

These risks are often not apparent at the point of purchase but become significant as systems scale.

Open systems reduce total cost of ownership by:

• Eliminating reliance on proprietary consumables or software add-ons
• Allowing incremental upgrades instead of full system replacements
• Enabling competitive sourcing of components and integrations
• Reducing the cost and complexity of future system changes

For many organisations, this flexibility becomes more valuable than upfront cost differences.

Yes. Labman systems are designed to integrate with existing digital infrastructure.

Typical integrations include:

• Bi-directional data exchange with LIMS and ELNs
• Workflow orchestration with MES platforms
• Data reporting into ERP systems
• Custom integrations for internal databases or analytics platforms

Because integrations are handled via standard interfaces, systems can be adapted to your specific architecture.

For IT and digital stakeholders, open automation systems offer:

• Greater control over data structures and access
• Easier alignment with internal data governance policies
• Reduced dependency on vendor-specific tooling
• More straightforward integration with enterprise systems

This often enables faster deployment of digital initiatives and reduces long-term technical debt.

Open systems support compliance by ensuring that:

• Data remains accessible and traceable across systems
• Audit trails can be integrated into broader data environments
• Reporting can be standardised across multiple platforms

Because data is not confined to a single proprietary environment, it is easier to align with regulatory and quality frameworks.

As laboratories become more digitally connected, priorities are shifting towards:

• Interoperability across systems and sites
• Long-term data usability for AI, modelling, and analytics
• Avoiding technical and financial lock-in
• Aligning automation with wider digital transformation strategies

An open approach to automation supports these priorities by enabling flexibility from the outset.

When assessing vendors, useful questions include:

• Can data be accessed without proprietary software?
• Are APIs available and documented?
• Can the system integrate with our existing LIMS/ELN/MES?
• Are consumables or components restricted to a single supplier?
• What happens if we need to upgrade or migrate in the future?

Clear, transparent answers to these questions are a strong indicator of openness.

An open approach to laboratory automation gives you:

• Control over your data
• Freedom to evolve your systems
• Reduced long-term risk and cost
• Alignment with digital and IT strategies

Rather than locking you into a fixed ecosystem, it allows your automation infrastructure to grow with your organisation.