Drag & drop pre-populated protocols or SOP templates and set automation rules to prepare your R&D projects with unrivaled speed.
Execute research experiments on your mobile device at the bench and automate inventory production and consumption as well as report creation.
Keeping everyone up to date on Scispot is a cinch. Collaborate with your customers or CROs on R&D and share the results in no time flat.
Our platform Scispot connects with hundreds of 3rd-party apps (Google Drive, OneDrive, Slack, Monday.com, etc.) and computational tools (Jupyter Notebook, R Studio, GPT-4, etc.)
"Scispot is very easy to integrate into our current system. It provided us with some ready-to-use workflows for automatically recording inventory, executing media recipes, and tracking a lot of the things that we do here. This raises our quality of work to a whole new level."
"I’ve started relying on Scispot for my daily research planning and execution. Using it to design my experiment templates and store all of my result data has been a game-changer."
"Scispot expands our digital footprint and helps us scale faster. It consolidates our company-wide operations and enhances the quality and efficiency of our science.”
"I highly recommend Scispot ELN to others, particularly to those in dry labs. Its API-first design enables seamless integration with productivity apps like Monday.com and analytics tools such as GraphPad Prism, enhancing our workflow and efficiency."
Q1. What does a contemporary ELN entail?
A1. A modern ELN is a digital lab notebook for wet and dry lab. Modern ELNs design specifically caters to data science use cases. For example, it should link unstructured data (like experiments and protocols) with structured metadata (like samples and inventory) easily. When the data is linked, Biotech AI companies can more easily use ELN data for their ML applications.
Q2. What is an ELN for Computational Biologists?
A2. An ELN for computational biologist is a digital management system designed to handle complex lab data. It's crucial for handling both organized and disorganized data, establishing it as a vital instrument in life science studies. Computational biologists often needs to share data with wet lab. If the ELN is designed for comp bio folks, it lets them share data using programming.
Q3. How does an API-First ELN Enhance Lab Management?
A3. An API-first ELN integrates seamlessly with various lab software and instruments. This integration helps in breaking down data silos, improving overall data management and information management in labs.
Q4. What are the advantages of ELNs with Generative AI in Data Science?
A4. ELNs with generative AI are crucial in data science. They utilize generative artificial intelligence (AI) to analyze large data sets, offering advanced AI models and natural language processing capabilities. For examples: Biotech AI companies use Scispot to summarise their experiments using LLM and foundation model without leaving the ELN interface.
Q5. Why are ELNs important for dry labs?
A5. ELNs for dry labs support environments that focus more on data analysis than physical experiments. These ELNs help in organizing lab data, thus playing a crucial role in lab management.
Q6. How Do ELNs Tackle Data Security?
A6. Data security is a priority for ELNs. They employ advanced security measures to protect sensitive lab data, reducing the risk of human errors and data breaches. A modern ELN satisfies all security controls related to SOC2, HIPAA, GDPR, and CFR-Part 11 compliance.
Q7. Are ELNs Suitable for Wet Labs As Well?
A7. Yes, ELNs are suitable for both wet labs and dry labs. They offer a versatile platform for managing all types of lab data, making them an integral part of any lab management system. Biotech labs use modern ELN to run as a digital biology company.
Q8. How Do ELNs Help in Managing Both Structured and Unstructured Data?
A8. ELNs, or electronic lab notebooks, are adept at handling both structured and unstructured data. This versatility makes them an excellent tool for comprehensive data management in various research fields. For example - Scispot Labsheets (structured data) and Labspaces (unstructured data) supports such seamless connection. As a result, Biotech AI companies can build their ontologies for AI.
Q9. What Makes ELNs Essential in Modern Research?
A9. ELNs are a software solution that revolutionizes traditional lab notebooks. They have generative AI and API-first functions, which are important for efficient data and information management in modern research. With LLM becoming more accessible, an ELN needs AI features like:
a. Summarising experiment reporting based on the structure of projects.
b. Summarising the inventory used across multiple experiments and protocols.
c. Using AI to create a record of your samples' history, connecting them to experiments and protocols for easy tracking.
Scispot empowers Biotech companies to be AI-first. It has helped me organize all of my ELN data with relevant metadata that I can now use for my downstream AI applications.
- Jason Wheeler, Head of Data, public Biotech company