We are excited to announce the launch of our innovative custom lab integration solutions at Scispot, tailored specifically for the dynamic requirements of the biotech and pharma industries. This new offering features a flexible pay-as-you-go pricing model, a pivotal advancement ensuring affordability and adaptability for all lab sizes.
Empowering Labs with Flexible Pricing Models
Our newly unveiled solutions include not only a pay-as-you-go option but also an affordable monthly subscription model, making advanced lab integrations more accessible to a broader scientific community. These integrations seamlessly connect laboratory instruments with various data platforms, encompassing major Electronic Lab Notebooks (ELNs) like Scispot's Labspace, Benchling, and Dotmatics, as well as Laboratory Information Management Systems (LIMS) such as Scispot's Labsheets, LabWare, and Crelio Health. This connectivity extends to essential cloud storage services including AWS, Azure Blob, and Google Cloud Platform.
Streamlining Lab Operations with Scispot GLUE
At the heart of our integration solutions is Scispot GLUE, our custom data integration and transformation platform. It is equipped with built-in integrations for scientific apps and instruments, transformation scripts, and AI prompts, crucial for high-resolution instruments like mass spectrometers, flow cytometers, and microscopes. This ensures that data is precisely adjusted for significant analytical insights.
Scispot GLUE facilitates not only advanced analytics, machine learning, and AI implementations but also maintains rigorous compliance with regulatory standards. Comprehensive audit trails and detailed logs provide transparency in data handling from extraction to storage, ensuring accountability and reliability.
Simplified, Efficient & Affordable Lab Integration
Implementing our custom lab integration solutions is streamlined into three simple steps:
Data Source Selection: Users begin by choosing their data source from a variety of laboratory instruments or data systems.
Data Destination Choice: Next, they select where the data will be stored or analyzed, which can include options like Google BigQuery, AWS Redshift, or visualization tools such as Tableau and Microsoft Excel Power BI.
Customization of Data Processing: Finally, users set specific transformation rules that tailor data processing to meet unique research requirements.
These custom integrations have already enabled numerous labs to automate data flows, significantly enhancing data utility across analytics platforms, cloud storage, and databases.
Future of Labs: Interoperability
Our Co-Founder and CPO Satya Singh is confident that, as labs become more interoperable and connected, adopting a pay-as-you-go model is crucial to leveraging the full potential of the AI revolution. Our solutions are designed to make this future achievable today, emphasizing affordability, speed, and flexibility.
Stay tuned for more updates as we continue to innovate and expand our technology to meet the needs of the evolving biotech landscape.
