
Built for testing laboratories, QBench is a cloud LIMS that brings samples, workflows, lab data, inventory, reporting, quality processes, and client interactions into a single system.
From order placement through sample processing, results, and automated reporting, QBench supports every stage of lab operations. Lab teams configure their own workflows, data fields, and automation rules, so the software fits existing processes instead of forcing new ones. When requirements shift, labs can adjust fields, processes, and automations without depending heavily on custom code.
Instruments, software, and outside systems connect to QBench through file parsers and a robust API, which moves data automatically and limits repetitive entry and transcription mistakes. For reporting beyond the LIMS, labs can connect QBench to Tableau, Power BI, Domo, or Looker via REST API.
What labs get with QBench:
Sample and workflow management
Configurable workflows and custom data fields
Workflow automation
Instrument and system integrations
File parsing and API connectivity
Inventory management
A client portal
Automated reporting
Analytics and operational insights
Connections to Tableau, Power BI, Domo, and Looker
A built-in Quality Management System (QMS)
Because it runs in the cloud, lab teams get secure access to their data, workflows, quality management, and reporting in one centralized platform. Implementation and ongoing guidance come from a team that includes former bench scientists who understand laboratory workflows.
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SciSure is a Scientific Management Platform built to support the full range of laboratory operations for scientific organizations. It combines ELN, LIMS, and Health & Safety functionality, giving teams a single system to document experiments, track sample lineage, manage chemical inventory, and run structured, audit-ready compliance processes.
Instead of relying on disconnected systems, organizations get one governed platform that improves reproducibility, increases visibility into lab operations, and reduces risk as they scale.
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Nextflow
Data-driven computational pipelines. Nextflow allows for reproducible and scalable scientific workflows by using software containers. It allows adaptation of scripts written in most common scripting languages. Fluent DSL makes it easy to implement and deploy complex reactive and parallel workflows on clusters and clouds. Nextflow was built on the belief that Linux is the lingua Franca of data science. Nextflow makes it easier to create a computational pipeline that can be used to combine many tasks. You can reuse existing scripts and tools. Additionally, you don't have to learn a new language to use Nextflow. Nextflow supports Docker, Singularity and other containers technology. This, together with integration of the GitHub Code-sharing Platform, allows you write self-contained pipes, manage versions, reproduce any configuration quickly, and allow you to integrate the GitHub code-sharing portal. Nextflow acts as an abstraction layer between the logic of your pipeline and its execution layer.
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Seqera
Seqera is an innovative bioinformatics platform crafted by the team behind Nextflow, aimed at optimizing and improving the oversight of scientific data analysis workflows. It provides a robust array of tools, such as the Seqera Platform for managing scalable data pipelines, Seqera Pipelines that grant access to a handpicked selection of open-source workflows, Seqera Containers to facilitate container management, and Seqera Studios that create interactive environments for data analysis. The platform is designed to integrate smoothly with a variety of cloud and on-premises systems, promoting reproducibility and compliance within scientific research. Users can incorporate Seqera into their existing infrastructures, including major cloud services like AWS, GCP, and Azure, all without the need for mandatory migrations. This flexibility allows for total control over data residency while enabling global scalability, ensuring that security and performance are never compromised. Furthermore, Seqera empowers researchers to enhance their analytical capabilities while maintaining a seamless operational flow within their established systems.
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