Alternatives to Edison Analysis

Sapio Sciences delivers a cutting-edge AI-driven lab informatics platform that integrates Laboratory Information Management Systems (LIMS), Electronic Lab Notebooks (ELN), and a Scientific Data Cloud into one seamless ecosystem. It is tailored to advance scientific research, clinical diagnostics, drug discovery, and manufacturing through configurable, no-code solutions. The Sapio LIMS® automates complex workflows with full configurability, removing the need for programming. Sapio ELN® offers a flexible, adaptable electronic lab notebook that supports diverse experimental needs. The platform’s Scientific Data Cloud consolidates instrument and research data enterprise-wide, paving the way for AI-driven insights. By unifying these components, Sapio simplifies data management and boosts productivity across the lab lifecycle. The platform is accessible for a wide range of industries and research applications. It aims to reduce administrative burden and enhance collaboration within scientific teams.

Edison Scientific is an innovative AI platform that streamlines and expedites scientific research, allowing users to transition from developing hypotheses to obtaining validated results all within one cohesive environment. This platform seamlessly integrates workflows for literature synthesis, data analysis, and molecular design, enabling research teams to conduct comprehensive scientific investigations at a significantly faster pace. Central to its functionality is Kosmos, an autonomous research system capable of executing hundreds of research tasks simultaneously, which converts multimodal datasets into detailed reports featuring validated findings and figures ready for publication. Kosmos adeptly synthesizes information from scientific literature, public databases, and proprietary datasets, while also identifying new therapeutic targets, revealing biological mechanisms, and facilitating the iterative design and refinement of molecular candidates. Proven effective in real-world research contexts, Kosmos has showcased the capability to deliver results that would typically take months of human labor in just one day, revolutionizing the efficiency of scientific research and development. This remarkable speed not only enhances productivity but also empowers researchers to focus on more complex challenges in their fields.

The L7 Enterprise Science Platform (L7|ESP®) is a comprehensive platform designed to contextualize data and remove business silos through process orchestration. This all-in-one solution supports the digitalization of data and scientific processes within life sciences organizations. It includes native applications like L7 LIMS, L7 Notebooks, L7 MES, and L7 Scheduling. L7|ESP seamlessly integrates with third-party applications, lab instruments, and devices to consolidate all data into a unified model. Featuring a low-code/no-code workflow designer and numerous pre-built connectors, it ensures rapid implementation and full automation. Utilizing a single data model, L7|ESP enhances advanced bioinformatics, AI, and ML to provide new scientific and operational insights. L7|ESP addresses the data and lab management needs and challenges within the life sciences sector, specifically targeting: ● Research and Diagnostics ● Pharma and CDMO ● Clinical Sample Management Explore the L7 Resource Center for on-demand recordings, case studies, datasheets, and more: l7informatics dot com/resource-center

edison365 is a powerful cloud-based platform that unifies idea management, project delivery, and portfolio oversight in a single application. It enables businesses to customize workflows with configurable stage gates, approval flows, and governance models using intuitive drag-and-drop tools. The platform features personal dashboards for productivity, Gantt charts for visual project scheduling, and comprehensive reporting to support data-driven decision-making. Trusted by more than 100 global organizations, including those in engineering, construction, and healthcare sectors, edison365 helps teams discover and develop promising ideas with measurable ROI. It supports everything from innovation management to risk management and employee engagement, ensuring no project is too complex or too small. With award-winning tools and a user-friendly interface, edison365 transforms how businesses manage their work and deliver results. Its flexibility and scalability make it suitable for global teams and diverse industries. Overall, edison365 drives business transformation by connecting ideas to execution seamlessly.

Kosmos is introduced as an advanced "AI Scientist" designed to autonomously engage in discovery by analyzing extensive scientific writings and running code to arrive at innovative insights. By employing structured world models, it effectively integrates knowledge acquired from numerous agent trajectories while ensuring consistency across tens of millions of tokens, thus overcoming the limitations in context length that previous language model-based systems faced. In a typical operational cycle, Kosmos can review around 1,500 research papers and execute 42,000 lines of analytical code, achieving in a single day what beta testers believe would require a human researcher six months to accomplish. Furthermore, the outputs generated by Kosmos are entirely traceable; every conclusion drawn in its reports can be directly linked to the exact lines of code and relevant literature excerpts that contributed to it, facilitating comprehensive scrutiny of its reasoning process. This level of transparency not only enhances credibility but also allows for deeper insights into the research methodology employed by Kosmos.

FutureHouse is a nonprofit research organization dedicated to harnessing AI for the advancement of scientific discovery in biology and other intricate disciplines. This innovative lab boasts advanced AI agents that support researchers by speeding up various phases of the research process. Specifically, FutureHouse excels in extracting and summarizing data from scientific publications, demonstrating top-tier performance on assessments like the RAG-QA Arena's science benchmark. By utilizing an agentic methodology, it facilitates ongoing query refinement, re-ranking of language models, contextual summarization, and exploration of document citations to improve retrieval precision. In addition, FutureHouse provides a robust framework for training language agents on demanding scientific challenges, which empowers these agents to undertake tasks such as protein engineering, summarizing literature, and executing molecular cloning. To further validate its efficacy, the organization has developed the LAB-Bench benchmark, which measures language models against various biology research assignments, including information extraction and database retrieval, thus contributing to the broader scientific community. FutureHouse not only enhances research capabilities but also fosters collaboration among scientists and AI specialists to push the boundaries of knowledge.

OnMail has been designed to address the fundamental issues plaguing email services today. Many users have lost control over their inboxes, invasive ad targeting has become commonplace, and numerous email addresses that reflect our digital identities remain inaccessible, while simplicity has been sacrificed for convoluted processes. This innovative platform introduces a permission-based inbox, along with advanced features such as enhanced search capabilities using natural language processing and a distinctive system for importing existing email accounts into OnMail. Users can easily send large attachments and benefit from AI-driven suggestions that help with tasks like unsubscribing from unwanted emails, following up on messages, and automating inbox organization. Additionally, OnMail offers premium service plans that allow users to create a personalized email address by integrating their own custom domain. With all these features, OnMail not only simplifies email management but also empowers users to take back control of their digital communication. Moreover, the team behind OnMail, Edison, also conducts ecommerce research, providing valuable insights to businesses through Edison Trends.

Transform your tech enterprise without the need for a development team by effortlessly launching educational platforms, creating online courses, selling practice tests, managing live classes, and nurturing communities—all without any coding skills. Whether you're a veteran instructional designer or just starting out, EdisonOS stands out as the premier Learning Management System (LMS) for developing online courses. Boost the interactivity of your educational offerings with our advanced content authoring tools, which come equipped with over 50 native content types such as flashcards, quizzes, and matching activities. Conduct secure, live classes with experienced instructors, allowing for enhanced real-time interaction that enriches the learning environment. Design assessments and mock exams with ease, providing students with an authentic test-like experience through our user-friendly builder. Additionally, our comprehensive eCommerce solution enables you to establish, launch, and grow a lucrative knowledge-based business seamlessly. Personalize and oversee your online presence with a unique website that reflects your business's fundamental values, while effortlessly crafting engaging emails with EdisonOS to maintain your learners' interest and connection. With these tools, you can not only streamline your operations but also create a vibrant community around your educational offerings.

BenevolentAI is a pioneering platform that leverages artificial intelligence and scientific technology to enhance drug discovery processes, specifically targeting complex diseases by efficiently processing and interpreting extensive biomedical data to yield actionable insights more swiftly than conventional approaches. By utilizing its unique Benevolent Platform, the company seamlessly integrates both structured and unstructured biomedical information—spanning literature, genomics, clinical data, and multi-omics—into a detailed knowledge graph. This robust framework empowers researchers to analyze biological systems, formulate testable hypotheses, identify new drug targets, and create potential drug candidates with increased confidence and reduced failure rates, ultimately transforming the landscape of medicine development. With its innovative approach, BenevolentAI stands at the forefront of a new era in the pharmaceutical industry.

Manage, store, and collaborate on multi-omic datasets effectively. The Illumina Connected Analytics platform serves as a secure environment for genomic data, facilitating the operationalization of informatics and the extraction of scientific insights. Users can effortlessly import, construct, and modify workflows utilizing tools such as CWL and Nextflow. The platform also incorporates DRAGEN bioinformatics pipelines for enhanced data processing. Securely organize your data within a protected workspace, enabling global sharing that adheres to compliance standards. Retain your data within your own cloud infrastructure while leveraging our robust platform. Utilize a versatile analysis environment, featuring JupyterLab Notebooks, to visualize and interpret your data. Aggregate, query, and analyze both sample and population data through a scalable data warehouse, which can adapt to your growing needs. Enhance your analysis operations by constructing, validating, automating, and deploying informatics pipelines with ease. This efficiency can significantly decrease the time needed for genomic data analysis, which is vital when rapid results are essential. Furthermore, the platform supports comprehensive profiling to uncover novel drug targets and identify biomarkers for drug response. Lastly, seamlessly integrate data from Illumina sequencing systems for a streamlined workflow experience.

Nygen serves as a cloud-driven platform for the analysis and discovery of single-cell RNA sequencing (scRNA-seq) and multi-omics data, allowing researchers to seamlessly upload, explore, visualize, analyze, and interpret intricate cellular datasets through an easy-to-use, no-code interface that promotes drag-and-drop workflows and sophisticated scientific analysis without the need for programming knowledge. This platform merges Nygen Analytics for swift and reproducible exploration of scRNA-seq data with collaborative dashboards that produce publication-ready outputs, integrates Nygen Database for easy access to curated single-cell datasets to enhance research and comparative studies, and includes Nygen Insights, an AI-enhanced feature that offers precise cell annotations, thorough disease impact assessments, and customized biological insights. Furthermore, it accommodates a variety of data formats, integrates public datasets, fosters secure cloud collaboration, and offers functionalities such as literature-linked evidence and analyses focused on biomarkers, ultimately empowering researchers to derive meaningful conclusions from their data. By streamlining complex analytical processes, Nygen significantly enhances the efficiency of scientific research and discovery.

Scitara DLX™ provides a swift connectivity framework suitable for any instrument found within life science laboratories, all while operating on a cloud-based platform that is both compliant and auditable. As a versatile digital data infrastructure, Scitara DLX™ facilitates connections between various instruments, resources, applications, and software utilized in the lab. The comprehensive cloud system ensures that all data sources are interconnected, promoting seamless data movement across numerous endpoints. Consequently, researchers can concentrate on their scientific endeavors instead of being bogged down by data-related challenges. Moreover, DLX intelligently curates and corrects data as it is processed, fostering the creation of accurate and well-organized data models that are essential for enhancing AI and ML systems. This robust approach plays a vital role in advancing digital transformation strategies within the pharmaceutical and biopharmaceutical sectors. By unlocking valuable insights from scientific data, the platform accelerates decision-making processes in drug discovery and development, ultimately aiding in the expedited launch of new medications into the market. Additionally, the integration of such a sophisticated infrastructure not only streamlines workflows but also enhances collaboration among researchers, paving the way for innovative solutions in the life sciences field.

Precision, efficiency, and assurance. The integration of generative AI into the biopharmaceutical industry is here. This technology streamlines the arduous task of gathering, organizing, and analyzing extensive data sets. Achieve essential insights with complete assurance every single time. With our AI-driven platform for data handling and validation, you will keep your workflows organized effortlessly. Collect, process, and verify your data all from a single interface. Easily search through both public and private databases using key characteristics of drugs. Categorize drugs and clinical trials based on comprehensive patient demographics. Retrieve necessary data in straightforward language. Strengthen your conclusions by linking your findings to their original sources. Direct your focus towards creating valuable outputs from your data, bypassing the tedious manual sorting process. Our advanced language models empower researchers to conduct asset evaluations 4.8 times quicker than traditional methods. We provide access to an extensive index of over 38 million scientific articles, conference papers, and clinical trial data. With this system, you’ll have all the information you require at your fingertips, ensuring timely and informed decision-making. Additionally, our platform adapts to your unique needs, enhancing the research experience even further.

Microsoft Discovery is an advanced AI-powered platform designed to accelerate scientific discovery by enabling researchers to collaborate with a team of specialized AI agents. This platform leverages a graph-based knowledge engine that connects diverse scientific data, allowing for deep, contextual reasoning over complex and often contradictory theories. Researchers can customize AI agents to align with their specific domains and tasks, making it easier to manage and orchestrate research efforts. Built on Microsoft Azure, Discovery ensures a high level of trust, transparency, and compliance, offering an enterprise-ready solution. The platform has already been used to accelerate the development of a novel coolant for data centers, cutting the discovery time from months to just 200 hours. This demonstrates the transformative potential of AI in R&D, providing researchers with the tools to unlock new possibilities and innovations at scale.

Outdated research and development software significantly hinders scientific innovation, causing delays in progress, fragmenting data into isolated systems, and erasing valuable institutional knowledge. In contrast, Benchling stands out as the premier cloud solution for life sciences R&D, facilitating the acceleration, measurement, and forecasting of research activities from the initial discovery phase through bioprocessing, all within a single platform. This comprehensive suite comprises seven seamlessly integrated applications designed to enhance R&D efficiency across various levels. With a focus on codeless configuration, open integration, and customizable dashboards, Benchling meets the unique needs of its users. Furthermore, its profound expertise in life sciences R&D and consulting guarantees long-term success for teams. As a cohesive R&D platform, Benchling allows researchers to minimize time spent on data entry and retrieval, enabling them to collaborate more effectively and advance their studies. Scientists, project managers, and executives alike can improve R&D productivity through enhanced visibility into experimental contexts, overall program performance, and resource allocation. Ultimately, embracing a modern R&D platform like Benchling can transform the way teams approach scientific discovery and innovation.

Sapio Sciences focuses on making life in the lab easier and more productive for scientists and the teams that support them. Founded with deep roots in machine learning and AI, the company invested early in a modern lab platform, data architecture and user experience that could support real experimental work at scale. Today, Sapio delivers the Sapio Platform, an agentic AI lab informatics platform that is unified, configurable, low code and scalable. It brings together Sapio LIMS, the market’s most advanced and flexible LIMS for automating research, diagnostics and manufacturing, Sapio ELaiN, the third generation AI lab notebook that acts as an AI co-scientist, and Sapio Scientific Data Cloud, the scientific data unification solution with built-in data organization, search, charting and tools. Scientists and lab teams can easily configure workflows, data structures and role based screens without writing code, while agentic AI helps develop procedures, automate steps and connect and analyse results. Sapio works with leading and emerging biopharma R&D, biotech, CRO and clinical diagnostics organizations worldwide.

Google Colab is a complimentary, cloud-based Jupyter Notebook platform that facilitates environments for machine learning, data analysis, and educational initiatives. It provides users with immediate access to powerful computational resources, including GPUs and TPUs, without the need for complex setup, making it particularly suitable for those engaged in data-heavy projects. Users can execute Python code in an interactive notebook format, collaborate seamlessly on various projects, and utilize a wide range of pre-built tools to enhance their experimentation and learning experience. Additionally, Colab has introduced a Data Science Agent that streamlines the analytical process by automating tasks from data comprehension to providing insights within a functional Colab notebook, although it is important to note that the agent may produce errors. This innovative feature further supports users in efficiently navigating the complexities of data science workflows.

Leverage artificial intelligence to condense scientific papers into concise summaries. By simply sending an email with the text, a URL, or attaching a PDF, you can receive a brief overview in your inbox within minutes, making it an ideal resource for researchers, students, and science enthusiasts pressed for time who struggle to navigate lengthy and complex articles. This innovative tool enhances productivity by saving valuable time for those engaged in scientific pursuits.

Locating, reading, and evaluating every pertinent scientific research paper can quickly become an exhausting and lengthy endeavor. Our AI-powered research assistant, crafted by academics for academics, allows you to dedicate more time to what you truly enjoy: engaging in research. Keep yourself updated with a snapshot of ongoing projects in your field, learn about the contributions of particular researchers, and explore potential opportunities for collaboration. Instead of spending an entire month on literature review, you can complete it in mere minutes. Effortlessly search through millions of publications across various academic disciplines to pinpoint essential information with just one click. Gain a quick understanding of scientific articles through concise summaries that highlight key concepts and findings in moments. Plus, utilize our specialized AI reviewer to receive immediate feedback on your manuscript before you submit it to conferences or journals, ensuring your work is of the highest quality. This innovative tool not only saves you time but also enhances the overall quality of your research output.

SciSpace BioMed serves as an innovative AI-powered "co-scientist" tailored for the field of biomedical research, integrating an extensive literature repository with over 150 bio-tools and more than 100 academic databases and software applications to enhance intricate research processes, which encompass areas such as genomics, single-cell analysis, drug discovery, and clinical genomics. This platform empowers researchers to pose questions in natural language, manage datasets, analyze variants or multi-omics results, plan experimental workflows, reason about clinical biology and diseases, and produce publication-ready materials, including figures, tables, and presentations, all while ensuring transparency and proper citations. Furthermore, users have the capability to engage with scientific articles through a “chat with PDF” feature that allows them to highlight and seek clarification on challenging text, mathematical content, or tables, making it an excellent tool for grasping complex methods or concepts. For the purposes of literature review or preliminary research, its AI-enhanced semantic search can sift through millions of academic papers, providing citation-supported summaries that facilitate deeper understanding and exploration of the relevant literature. This functionality significantly accelerates the research process, allowing scientists to focus more on their discoveries rather than administrative tasks.

JupyterHub allows users to establish a multi-user environment that can spawn, manage, and proxy several instances of the individual Jupyter notebook server. Developed by Project Jupyter, JupyterHub is designed to cater to numerous users simultaneously. This platform can provide notebook servers for a variety of purposes, including educational environments for students, corporate data science teams, collaborative scientific research, or groups utilizing high-performance computing resources. It is important to note that JupyterHub does not officially support Windows operating systems. While it might be possible to run JupyterHub on Windows by utilizing compatible Spawners and Authenticators, the default configurations are not designed for this platform. Furthermore, any bugs reported on Windows will not be addressed, and the testing framework does not operate on Windows systems. Although minor patches to resolve basic Windows compatibility issues may be considered, they are rare. For users on Windows, it is advisable to run JupyterHub within a Docker container or a Linux virtual machine to ensure optimal performance and compatibility. This approach not only enhances functionality but also simplifies the installation process for Windows users.

The Suite is designed to be both secure and scalable, featuring a contemporary and user-friendly interface that empowers scientists to have full control over the configuration of workflows for various techniques, modalities, and data types. The latest iteration, Signals VitroVivo 3.0, formerly known as Signal’s Screening, effectively converts raw data into practical insights, while Signals Inventa 3.0, previously called Signals Lead Discovery, serves as advanced analytics software that allows researchers to publish results effortlessly from diverse data sources. Additionally, it facilitates the capture of experimental data, oversees materials management, and streamlines collaboration workflows within an easy-to-navigate cloud-based electronic notebook. With adaptable visualizations and the ability to automate instrument data processing, the Suite enhances data quality and ensures reproducibility in research. It also provides a unified data management system for scientific outcomes, enriched with dynamic, interactive analytics. Furthermore, its extensibility allows for seamless integration with internal systems and partner processes, making it an invaluable tool for scientific discovery and innovation.

Partek bioinformatics software offers robust statistical and visualization capabilities through a user-friendly interface that caters to researchers of varying expertise. This innovation allows users to navigate genomic data with unprecedented speed and ease, truly embodying our motto, "We turn data into discovery®." With pre-installed workflows and pipelines in a simple point-and-click format, even complex NGS and array analyses become accessible to all scientists. Our combination of custom and public statistical algorithms works seamlessly to transform NGS data into valuable biological insights. Engaging visual tools like genome browsers, Venn diagrams, and heat maps illuminate the intricacies of next-generation sequencing and array data with vibrant clarity. Additionally, our team of Ph.D. scientists is always available to provide support for NGS analyses whenever queries arise. Tailored to meet the demanding computational requirements of next-generation sequencing, the software also offers flexible options for installation and user management, ensuring a comprehensive solution for research needs. As a result, users can focus more on their research and less on technical challenges.

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.

Prism is a free, cloud-based LaTeX workspace built specifically for scientific writing and collaboration. It combines drafting, compiling, and version control into one unified platform, eliminating the need for local environments or external tools. Prism integrates GPT-5.2 directly into the workflow, offering AI-powered proofreading, formatting assistance, and literature discovery. The platform supports unlimited collaborators with real-time editing and instant previews, removing version conflicts and manual merges. Project-aware AI understands the full manuscript context, helping refine structure, logic, equations, and references as drafts evolve. Built-in tools handle citation management, LaTeX rendering, and automated error detection. Prism allows researchers to focus more on ideas and less on formatting details. Features like voice-to-code, image-to-code, and AI-driven fixes further accelerate writing tasks. Unlimited projects and compile time make it suitable for both short papers and long-form research. Prism sets a new benchmark for collaborative scientific writing.

The Bioconductor initiative is dedicated to creating and distributing open-source software for the accurate and reproducible analysis of biological data. We promote a welcoming and cooperative environment for developers and data scientists alike. Our resources are designed to unlock the full potential of Bioconductor. From foundational tools to sophisticated functionalities, our extensive tutorials, guides, and documentation cater to all user needs. Utilizing the R programming language, Bioconductor embraces both open-source principles and collaborative development. It features biannual releases and boasts a vibrant user community. Additionally, Bioconductor offers Docker images for each release and facilitates its integration within AnVIL. Established in 2001, Bioconductor has become a prominent open-source project within the realms of bioinformatics and biomedical research. It encompasses over 2,000 R packages contributed by upwards of 1,000 developers and experiences more than 40 million annual downloads. Furthermore, Bioconductor has been referenced in over 60,000 scientific publications, underscoring its significant impact on the research community. The ongoing growth and evolution of Bioconductor continue to support advancements in biological data analysis.

Wisio.app serves as a digital hub for scientists, researchers, and students to expedite the creation and dissemination of high-quality scientific content through advanced AI technology. By inputting your text and relevant keywords, the platform provides scientifically accurate suggestions to help you craft the ideal piece. Users can easily extract keywords and efficiently search through Pubmed to find the most relevant citations. This platform makes it possible to reach a worldwide audience with your scientific findings. Moreover, by simply entering your text, wisio.app can refine it into precise scientific English. Enhance your writing with our AI-driven English correction tool, which strives for near-perfect clarity and comprehension for both reviewers and peers, ultimately breaking down communication barriers in the scientific community. With its innovative features, wisio.app is redefining the way science is communicated and shared globally.

Project Jupyter is dedicated to the creation of open-source tools, standards, and services that facilitate interactive computing in numerous programming languages. At the heart of this initiative is JupyterLab, a web-based interactive development environment designed for Jupyter notebooks, coding, and data manipulation. JupyterLab offers remarkable flexibility, allowing users to customize and organize the interface to cater to various workflows in fields such as data science, scientific research, and machine learning. Its extensibility and modular nature enable developers to create plugins that introduce new features and seamlessly integrate with existing components. The Jupyter Notebook serves as an open-source web application enabling users to produce and share documents that incorporate live code, mathematical equations, visualizations, and descriptive text. Common applications of Jupyter include data cleaning and transformation, numerical simulations, statistical analysis, data visualization, and machine learning, among others. Supporting over 40 programming languages—including popular ones like Python, R, Julia, and Scala—Jupyter continues to be a valuable resource for researchers and developers alike, fostering collaborative and innovative approaches to computing challenges.

Opscidia serves as a collaborative platform that consolidates all scientific and technological knowledge into one accessible location. Utilizing cutting-edge AI technologies, it functions as a scientific hub equipped with various monitoring tools that allow users to access top-tier scientific information quickly and efficiently. Monitoring scientific and technological advancements can be a labor-intensive endeavor; however, it is crucial for fostering innovation. By addressing this challenge, Opscidia provides a streamlined approach that ensures the most relevant scientific data is just a few clicks away. This functionality enables organizations to make the most of their monitoring time, allowing their teams to dedicate more resources to research and development initiatives, client deliverables, and routine monitoring tasks. Among the key features of the Opscidia platform are the ability to identify emerging concepts, assess scientific trends related to specific products or technologies, accelerate the process of writing scientific reports through artificial intelligence, and facilitate collaboration and sharing of scientific information among users. Ultimately, Opscidia aims to enhance productivity while keeping teams informed and engaged with the latest developments in their fields.

Formulate a question to draw insights from academic research articles. Consensus leverages artificial intelligence to extract answers from scholarly papers, with the most effective approach being to pose a specific inquiry. Concentrate on topics that have been explored by researchers, spanning various fields, from biology to the social sciences. Scientific research represents an unparalleled reservoir of knowledge and insights. However, the primary audience for this information often overlaps with those generating it. Our mission is to create tools that democratize access to scientific knowledge, fostering a more informed society and ultimately enhancing the quality of life for everyone. Developed by experts in machine learning, science, and technology from some of the leading institutions globally, Consensus aims to bridge the gap between research and its application in real-world scenarios. This initiative is not just about accessing information; it's about transforming how we engage with and utilize scientific data for the betterment of society.

Noah AI serves as an advanced research assistant powered by artificial intelligence, specifically designed for professionals in the life sciences sector, with the goal of automating and expediting intricate workflows in biomedical research, clinical development, and strategic commercial planning. It features an “Agent” mode that efficiently manages and implements multi-step tasks through intelligent web searches, accessing credible scientific databases like PubMed and FDA/NIH resources, summarizing influential research papers, extracting data from clinical trials, and producing high-quality reports, while a simpler “Search” mode provides quick and trustworthy access to summaries of domain-specific content. By integrating extensive medical and public health data, alongside AI-generated insights and real-time tracking of global research and development activities as well as conference intelligence, Noah AI empowers researchers, biotech investors, and healthcare professionals to transform questions into insights significantly faster than traditional methods. This innovative approach not only enhances productivity but also fosters a more informed decision-making process in the ever-evolving landscape of life sciences.

At Iris.ai we have spent the last 6 years building an award-winning AI engine for scientific text understanding. Our algorithms for text similarity, tabular data extraction, domain-specific entity representation learning and entity disambiguation and linking measure up to the best in the world. On top of that, our machine builds a comprehensive knowledge graph containing all entities and their linkages to allow humans to learn from it, use it and also give feedback to the system. The Iris.ai Researcher Workspace is a flexible tool suite that allows to approach a project in a variety of ways. Modules include content based explorative search, machine analysis of document sets, extracting and systematizing data points, automatically writing summaries of multiple documents - and very powerful filters based on context descriptions, the machine’s analysis, or specific data points or entities. The Iris.ai engine for scientific text understanding is a powerful interdisciplinary system that can be automatically reinforced on a specific research field for much more nuanced machine understanding - without human training or annotation.

Signals Inventa, which was previously referred to as Signals Lead Discovery, represents an advanced data management solution designed for the evaluation of scientific findings. Utilizing the cutting-edge Signals Data Factory technology from PerkinElmer, it allows users to seamlessly access and analyze all scientific data gathered throughout the research and development process. Regardless of your project, Signals Inventa aids in determining which tests yield the most promising outcomes, guides decisions on future developments, and identifies areas for further testing, among many other capabilities. The platform ensures that data is standardized, organized, and primed for exploration. Additionally, Signals Inventa enhances scientific insight through various analytical techniques such as R-group decomposition, chemical clustering, matched molecular pair analysis, the identification of maximum chemical substructures, as well as blast searches across both internal and external databases, and sequence alignment. This comprehensive approach not only streamlines data analysis but also fosters innovative discoveries in the field.

An integrated platform that bridges scientific reasoning, compound development, and computational tools is now available. Chemaxon’s Design Hub supports medicinal chemistry by facilitating the analysis and prioritization of innovative ideas. This unified platform allows users to design compounds and manage concepts seamlessly. Transitioning from traditional PowerPoint presentations to dynamic, visually engaging, and chemically searchable hypotheses enhances the compound design workflow. Users can conveniently utilize established physicochemical properties, computational models, novelty considerations, or accessible compound catalogs within an interactive visual setting. Collaborate with your Contract Research Organizations (CROs) in the compound development journey through this secure online resource. Furthermore, assess the gathered data from biological assays or experimental structural insights to derive Structure-Activity Relationships (SAR) and generate fresh hypotheses for subsequent optimization cycles. Your scientific ideas can be conveniently organized in a “designer's electronic lab notebook,” which features chemically aware drawing tools that streamline the design process. This comprehensive approach ensures that every step of compound development is efficient and well-documented, paving the way for future innovations.

Leverage the capabilities of biomedical data through the Polly Platform, which is designed to enhance the scalability of batch jobs, workflows, coding environments, and visualization tools. By facilitating resource pooling, Polly optimally allocates resources according to your specific usage needs and leverages spot instances whenever feasible. This functionality contributes to increased optimization, improved efficiency, quicker response times, and reduced costs associated with resource utilization. Additionally, Polly provides a real-time dashboard for monitoring resource consumption and expenses, effectively reducing the burden of resource management on your IT department. An essential aspect of Polly's framework is its commitment to version control, ensuring that your workflows and analyses maintain consistency through a strategic combination of dockers and interactive notebooks. Furthermore, we've implemented a system that enables seamless co-existence of data, code, and the computing environment, enhancing collaboration and reproducibility. With cloud-based data storage and project sharing capabilities, Polly guarantees that every analysis you conduct can be reliably reproduced and verified. Thus, Polly not only optimizes your workflow but also fosters a collaborative environment for continuous improvement and innovation.

OmicsBox, a leading bioinformatics tool, offers end-toend data analysis for genomes, transcriptomes and metagenomes. It also provides genetic variation studies. The application, which is used by leading private and public research institutes worldwide, allows researchers to process large and complicated data sets and streamline their analytical process. It is designed to be efficient, user-friendly and equipped with powerful tools to extract biological insight from omics data. The software is divided into modules, each of which has a set of tools and features designed to perform specific types of analyses, such as de novo genome assemblies, genetic variations analysis, differential expression analyses, taxonomic classifications, and taxonomic classes of microbiome, including the interpretation of results and rich visualizations. The functional analysis module uses the popular Blast2GO annotating methodology, making OmicsBox a great tool for non-model organisms research.

Easily switch between command and editor modes using just one keystroke while navigating through cells with arrow keys. Take advantage of all standard Jupyter shortcuts for a smoother experience. Experience fully interactive outputs positioned directly beneath the cell for enhanced visibility. When working within code cells, benefit from intelligent code suggestions, real-time error detection, quick-fix options, streamlined navigation, and many additional features. You can operate with local Jupyter notebooks or effortlessly connect to remote Jupyter, JupyterHub, or JupyterLab servers directly within the IDE. Execute Python scripts or any expressions interactively in a Python Console, observing outputs and variable states as they happen. Split your Python scripts into code cells using the #%% separator, allowing you to execute them one at a time like in a Jupyter notebook. Additionally, explore DataFrames and visual representations in situ through interactive controls, all while enjoying support for a wide range of popular Python scientific libraries, including Plotly, Bokeh, Altair, ipywidgets, and many others, for a comprehensive data analysis experience. This integration allows for a more efficient workflow and enhances productivity while coding.

Collaborating closely with our in-house teams of chemists and biologists, as well as our clients, we create products that excel in both performance and scientific insight. Chemaxon's diverse product lineup includes ready-to-use solutions for researchers, backend resources for IT professionals, additional components for enhanced functionality, and seamless integrations that allow our technology to be accessed through third-party applications such as Microsoft Excel and KNIME. With a user base exceeding one million, Chemaxon has established itself as a leader in developing software that facilitates scientific innovation through advanced calculation, searching, and drawing capabilities. Our tools are extensively utilized in life sciences research and educational settings, serving a broad spectrum of industries, including numerous major pharmaceutical companies. We maintain a global presence with offices in Budapest, Basel, Boston, and San Diego, supported by a network of distributors worldwide. Our commitment to scientific excellence ensures that we remain at the forefront of technological advancements in the life sciences sector.

The QIAGEN CLC Geneomics Workbench is a powerful tool that works for all workflows. It is easy to overcome data analysis challenges with cutting-edge technology, unique features and algorithms that are widely used by scientists in industry and academia. Bioinformatics software solutions that are user-friendly allow for comprehensive analysis and interpretation of your NGS data. This includes de novo assembly and transcriptome assembly, resequencing analysis, WES and targeted panel support, variant calling, variant calling, RNA–seq, ChIP–seq and DNA methylation analysis (bisulfite sequence analysis). You can analyze your RNA-seq (miRNA, smallRNA) and smallRNA (lncRNA), data using easy-to-use transcriptomics workflows that allow for differential expression analysis at both gene and transcript levels. QIAGEN CLC Genomics Workbench was designed to support a wide variety of NGS bioinformatics programs.

Streamline the entire selection process for reagents and model systems to eliminate costly inefficiencies and errors that lead to experimental failures. Accelerate project timelines by facilitating the selection of reagents and model systems in a mere 30 seconds, compared to the traditional 12-week duration. This transformation can significantly cut the hard costs associated with consumables, saving organizations millions annually. By restoring valuable research time to scientists, you can enhance the organization’s mission. Experience tangible business benefits from AI through a proven, ready-to-use application. More than 41,200 scientists across 15 of the leading 20 pharmaceutical companies, as well as over 4,450 academic institutions, leverage BenchSci’s AI-Assisted Antibody Selection to design more effective experiments, resulting in documented savings of millions per year in hard costs alone. However, it's important to note that antibodies account for only 40-50% of reagent-related failures. Access a comprehensive array of experimental evidence, along with catalog data for reagents and model systems, all within one user-friendly interface. This platform integrates real-world experiment data sourced from 11.2 million scientific publications, including those published in closed-access journals, providing an unparalleled resource for researchers. With this level of detailed information, scientists can make informed decisions that significantly enhance their research outcomes.

Logilab® ELN from Agaram is a proven Electronic Lab Notebook (ELN) solution that offers laboratories the ability to become completely paperless by recording, executing, and storing their tests, experiments, and lab tasks in a secure database. This ELN solution is suitable for laboratories operating in various scientific fields, as well as researchers and organizations engaged in regulated and non-regulated product and project development. Logilab® ELN helps laboratory organizations achieve higher productivity, better quality, and compliance with various statutory standards and Good Lab Practices (GxP) principles of data integrity. The product includes several features to assist laboratories, such as a simple interface to design lab templates for tasks and experiments, dynamic inventory management with re-order levels and expiry dates, barcode printing, and inventory validation, user-configured dynamic reports, and document creation. It also automates instrument data capture, enabling the parsing of data from instrument output files and port-based instruments, making it a valuable asset to any laboratory.

Sciscoper is an AI-driven research assistant designed to enhance and expedite the literature review process for professionals in STEM fields, including researchers, academics, and R&D teams. Given the challenge researchers face with managing extensive collections of scientific papers from various sources, extracting valuable insights can often become a cumbersome task. To address this issue, Sciscoper leverages AI and natural language processing capabilities to automatically: - Summarize scientific articles and research outcomes. - Identify crucial insights, concepts, and interconnections within documents. - Create literature reviews complete with citations in diverse referencing formats. - Organize and categorize papers into a well-structured, searchable knowledge repository for convenient access. As a result, users can minimize the time spent on tedious reading and note-taking, allowing them to concentrate more on analyzing findings, recognizing areas for further research, and contributing to the advancement of scientific knowledge. Ultimately, Sciscoper transforms the literature review process, making it more efficient and effective for its users.

Cure AI represents a cutting-edge medical research platform that harnesses the power of artificial intelligence to grant users access to an extensive library of over 26 million scientific publications sourced from PubMed. With its AI-driven natural language processing capabilities, users can pose research questions in a conversational manner, which the system accurately decodes to return specific and relevant results. It also boasts sophisticated search filters that allow users to narrow down findings by factors such as journal, date of publication, and various other criteria, catering to individual research requirements. Additionally, Cure AI evaluates evidence based on its quality and significance, taking into account metrics like the journal's h5-index, citation tally, and the type of publication, thereby ensuring users obtain the most relevant and credible information available. The platform further enhances user experience by allowing easy transitions between AI-generated insights and original literature, streamlining the process of literature review and analysis. Moreover, it comes equipped with convenient citation tools that enable users to quickly copy or share references with just one click, simplifying the documentation process. Finally, the intuitive design of Cure AI encourages researchers to explore new avenues of inquiry with confidence and ease.

Dolcera's Majjanti incorporates state-of-the-art AI technology, enabling us to deliver the most precise and insightful analysis available. We sift through a wide range of content, from scientific studies to product launches, curating crucial information and presenting it in a user-friendly format that is easy to navigate. Whether you are an entrepreneur, researcher, engineer, or professional within the science and technology sectors, our service ensures you have timely access to essential data, empowering you to maintain a competitive edge. In addition to this, research and development teams often possess a wealth of technical documentation, including slide presentations, lab notebooks, patents, and supplier contact details. Fortunately, all of this material can be efficiently processed through OCR technology, systematically categorized, tagged, and uploaded to the cloud, making it searchable and secure, all while minimizing the workload for engineers and scientists. As a result, organizations can streamline their knowledge management processes and enhance collaboration across teams.

Harness the capabilities of artificial intelligence to accelerate the transition from laboratory research and experimental findings to the introduction of transformative therapies. Achieve a remarkable increase in research efficiency, potentially improving productivity by as much as 90% by cutting down your literature review time from several months to mere minutes. Eliminate distractions and enhance your search capabilities with a precise and accurate tool that simplifies the navigation of the expanding landscape of scientific publications. This approach not only saves time but also minimizes bias and enhances the likelihood of discovering groundbreaking insights. Delve deeply into the intricacies of disease biology and engage in sophisticated target identification. Causaly's advanced knowledge graph integrates data from countless publications, enabling thorough and objective scientific investigations. Effortlessly explore the intricate biological cause-and-effect dynamics without requiring extensive expertise. Access a comprehensive array of scientific documents and reveal previously overlooked connections. Causaly’s robust AI system processes millions of biomedical articles, facilitating improved decision-making and enhancing research outcomes, ultimately leading to a more informed and innovative scientific community. By utilizing such tools, researchers can significantly transform their methodologies and enhance their contributions to medicine.