Scibot, also known as Scispot AI and AI Lab Assistant, integrates seamlessly with Scispot apps like alt-ELN, alt-LIMS, and alt-SDMS, as well as other ELN and LIMS systems. This integration centralizes data, making it accessible and interactive through Scibot's natural language processing capabilities. By connecting R&D, clinical, and production data, Scibot ensures you can extract insights and perform analyses as needed. This exemplifies the power of generative AI in biotech.
Scispot and its AI Lab Assistant Scibot integrate with Microsoft Power Platform, Power Apps, Azure, and MS365, centralizing all R&D, clinical, and product data. This integration allows users to “chat with their data” across different tools and formats. Historical lab data stored in Microsoft apps can be synced with Scispot’s Cloud for further analysis, visualization, and pattern recognition through Scibot, leveraging the benefits of AI in Biotech.
Yes, Scispot and its AI Lab Assistant, Scibot, integrate effectively with Microsoft Lists, facilitating lab operations and assay results management. This ensures smooth data flow, accurate tracking, storage, and easy access, enhancing lab workflow efficiency and accuracy. The integration highlights the efficiency of generative AI in biotech processes.
Yes, Scibot supports various scientific calculations and decision-making, including PI calculations, molecular weight determination, and sequence alignment calculations. These features are available if the relevant data is captured or synced with Scispot. For example, molecular weight can be determined by uploading chemical structure files like SMILES, MOL, or Inchi. This showcases the capabilities of AI in Biotech.
No additional hardware is needed to support Scispot and its AI Lab Assistant Scibot. They connect with lab instruments via Scispot Agent or Connector, enabling seamless data integration and interaction without extensive hardware investments. This ease of use is a significant advantage of generative AI in biotech applications.
Scispot is designed for easy integration without dedicated engineers or bespoke solutions. The platform offers out-of-the-box ELN and LIMS functionality, quickly configurable and personalized to meet specific lab requirements. Personalized AI training with your data ensures accurate and relevant recommendations from Scibot, facilitating a smooth integration process. This makes AI in Biotech accessible and efficient.
No, Scibot can access and integrate data from multiple instruments and apps within the lab. It creates a centralized data lake where data from different sources can be analyzed and interacted with, ensuring comprehensive coverage without the need for instrument-specific setups. This broad integration capability is a hallmark of generative AI in biotech.
Yes, Scispot supports comprehensive data associations across various research stages, including tracking and analyzing data from chemical inputs in drug formulation to in vivo endpoints in treated mice. This enables researchers to gain holistic insights and make informed decisions, demonstrating the power of AI in Biotech.
Scibot, AI Lab Assistant, is pre-trained with extensive public scientific data and proprietary biotech-specific ontologies, providing robust scientific context. Scispot can also train Scibot with your specific data, personalizing its capabilities to meet your lab’s unique needs. This customization is part of what makes generative AI in biotech so powerful.
Yes, Scibot, AI Lab Assistant, allows role-based access control, enabling selective connection for individual internal and external users to different R&D, clinical, and production data. This ensures external collaborators only access relevant information, maintaining data security and integrity. This feature underscores the secure application of AI in Biotech.
Scispot employs continuous prompt engineering and context-specific training to minimize inaccuracies or “hallucinations.” Rigorous validation processes and user feedback ensure the accuracy of Scibot’s insights. Scibot provides full transparency on the basis of its judgment while answering questions, ensuring trust in AI in Biotech applications.
Yes, Scispot includes a customizable dashboard feature for visualizing high-level information such as program progress and key metrics. With natural language processing, users can create personalized dashboards instantly without coding skills, providing real-time updates for better decision-making and efficient resource management. This feature enhances the usability of generative AI in biotech.
Storage and compute costs are included in Scispot’s licensing fee. Scispot pricing is based on the number of user seats and custom integrations, providing sufficient AI tokens for standard usage, ensuring no additional expenses for data storage or compute resources. This all-inclusive pricing model simplifies budgeting and financial planning for labs, making AI in Biotech more accessible.
Yes, Scibot, AI Lab Assistant, can clean, process, and enrich imported data in real-time, depending on the data type and workflow. This helps maintain data quality and integrity, ensuring accurate and reliable information for analysis. This real-time capability is a significant benefit of generative AI in biotech.
