Synthace is a biotechnology software company that helps research laboratories automate biological experiments using a platform that translates scientific ideas into executable workflows. In many life science organizations, experiments begin as written protocols that must be interpreted and manually executed across instruments, which can introduce variation and slow iteration. By shifting protocol design into software, Synthace allows researchers to define experiments visually, connect them to robotic systems and preserve a structured record of every step from planning through analysis.
This digital model reflects a broader trend in research infrastructure where software plays a larger role in coordinating laboratory activity. Instead of treating automation hardware as isolated equipment, the platform acts as an orchestration layer that connects instruments into a unified workflow environment. Scientists can design procedures once, store them centrally and deploy them across compatible systems without rewriting documentation for each run.
Workflow as Infrastructure
The Synthace platform is built around a workflow engine that enables researchers to construct experiments as structured digital processes. Each step in a protocol can be mapped within the interface, including reagent preparation, instrument interaction, incubation timing and data collection. Once defined, the workflow can be executed on laboratory hardware that is connected to the system, allowing software to translate experimental logic into machine instructions.
This architecture reduces reliance on manual transcription between planning and execution. When protocols exist only in text documents, laboratories may face inconsistencies in how different operators interpret instructions. Encoding experimental logic in software creates a standardized blueprint that can be reused, reviewed and adjusted with full version tracking. That capability supports reproducibility, which remains a persistent concern across biological research disciplines.
For laboratories that conduct iterative studies, digital workflows also support rapid modification. Scientists can update variables, adjust conditions and rerun experiments without rebuilding procedures from scratch. The ability to revise and redeploy protocols allows teams to explore broader parameter spaces while maintaining alignment across projects. In environments where speed and accuracy are both priorities, this structured flexibility becomes a strategic advantage.
Automation and Scale
High throughput experimentation has become a defining feature of modern drug discovery, genomics and synthetic biology. These fields require many parallel experiments to test combinations of concentrations, genetic constructs or environmental conditions. Manual execution of such studies can demand significant labor and increase the chance of inconsistencies.
Synthace’s software connects to laboratory automation systems so that workflows can run on robotic instruments in a coordinated manner. By integrating design and execution within one platform, researchers can schedule large batches of experiments, monitor progress and capture results in a unified system. The approach supports scale without requiring custom software development for each instrument.
From a business perspective, this model lowers barriers to automation adoption. Laboratories do not need to redesign infrastructure to implement digital workflows, and institutions with existing equipment can integrate compatible systems into the platform. This compatibility allows organizations to expand automation gradually rather than replacing hardware entirely, which can protect prior investments while increasing efficiency.
Reproducibility and Governance
Scientific credibility depends on reproducible methods and transparent documentation. When experiments are performed manually, details may reside in notebooks, spreadsheets or individual memory, which can complicate replication across sites. Synthace addresses this challenge by storing workflows digitally, linking each execution to its underlying protocol definition.
When data is generated, it is associated directly with the workflow that produced it. This linkage creates an auditable path from design through execution to analysis. Laboratories can review historical versions of protocols, compare results across iterations and verify how specific changes influenced outcomes. Such traceability supports internal governance standards and external reporting requirements.
The platform also supports collaboration across distributed research groups. Because workflows are stored centrally, scientists in different locations can execute identical experiments with consistent parameters. This shared structure is particularly relevant for organizations operating multiple laboratories or partnering across institutions, where alignment of methods can reduce duplication and accelerate joint projects.
Competitive Context in Laboratory Technology
The market for laboratory automation software includes instrument manufacturers, robotics providers and emerging digital platforms. Many vendors offer hardware specific control systems, but fewer provide cross platform workflow orchestration that operates independently of a single instrument brand. Synthace differentiates itself by focusing on experiment design as software infrastructure rather than tying workflows exclusively to proprietary devices.
As research institutions seek greater efficiency, integration between data systems and automation hardware has become a priority. Some competitors emphasize data analytics or sample tracking, while others focus on robotics control. Synthace’s strategy centers on the workflow layer that connects design, execution and documentation within one environment. This positioning places the company within the growing segment of laboratory digitalization tools that support programmable experimentation.
Investors and research leaders often evaluate automation solutions based on scalability, interoperability and reproducibility. Platforms that allow experiments to run across multiple instruments and facilities without rewriting protocols tend to align with long term infrastructure planning. By building a system that abstracts experimental logic from hardware details, Synthace addresses these criteria while supporting diverse research applications.
Business Strategy and Long-Term Value
From a strategic standpoint, laboratories adopting software defined workflows may gain operational predictability. When experiments are standardized digitally, resource planning becomes more accurate because teams can estimate instrument time, reagent usage and throughput based on documented workflows. This visibility supports budgeting and project management across research portfolios.
The platform’s cloud connectivity further extends accessibility. Researchers can design experiments remotely and coordinate execution with automated systems located within laboratory facilities. This capability supports collaboration between geographically separated teams and enables centralized oversight of distributed research programs.
As biological research continues to generate larger data sets and more intricate experimental designs, structured workflow management can reduce administrative overhead and free scientists to focus on hypothesis generation and analysis. Rather than spending time on manual protocol replication, researchers can concentrate on interpreting results and refining experimental direction.
Synthace operates within a broader shift toward programmable biology, where digital tools define how experiments are structured and executed. By embedding experimental logic in software and connecting it to laboratory hardware, the company contributes to a model in which research becomes more standardized, traceable and scalable. In a field where precision and reproducibility influence scientific and commercial outcomes, workflow-based automation offers laboratories a path toward greater consistency while maintaining flexibility for innovation.
Markus Gershater, Co-Founder & CEO, Synthace
