Best AI Science Software

SciSure applies AI where it creates measurable value for scientists. Marketplace add-ons bring this into practice: an in-platform support assistant, automated data analysis, AI-assisted protocol generation, in silico toxicity prediction, and image analysis tools for cell and particle detection, plus specialized add-ons for areas like CAR-T research. Data control stays with the lab; models only see what's explicitly permitted, and outputs are built to be traceable rather than opaque. Teams can choose which AI tools to enable, keep them isolated to specific workflows, and add capability without disrupting the rest of the platform.

Sapio Sciences delivers the Sapio Platform, an agentic AI lab informatics platform that makes life in the lab easier and more productive for scientists. The unified, configurable, low code and scalable environment 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 and scientific co scientist, and Sapio Scientific Data Cloud, the scientific data unification solution with built in organization, search, charting, tools and AI. Biopharma R&D, biotech, CRO and clinical diagnostics organizations use Sapio to run complex workflows and keep samples, experiments and data connected in one place instead of juggling disconnected systems.

Edison Analysis is a next-generation scientific data-analysis agent built by Edison Scientific. It is the analytical engine underpinning their AI Scientist platform, Kosmos, and it’s available both on Edison’s platform and via API. Edison Analysis performs complex scientific data analysis by iteratively building and updating Jupyter notebooks in a dedicated environment; given a dataset plus a prompt, the agent explores, analyzes, and interprets the data to provide comprehensive insights, reports, and visualizations, very much like a human scientist. It supports execution of Python, R, and Bash code, and includes a full suite of common scientific-analysis packages in a Docker environment. Because all work is done within a notebook, the reasoning is fully transparent and auditable; users can inspect exactly how data was manipulated, which parameters were chosen, how conclusions were drawn, and can download the notebook and associated assets at any time.

L7 Enterprise Science Platform (L7|ESP®) is a unified platform that contextualizes data and eliminates business silos via process orchestration. It's a comprehensive solution that facilitates the digitalization of data and scientific processes in life sciences organizations. L7|ESP has native applications, including L7 LIMS, L7 Notebooks, L7 MES, L7 Scheduling, and more. It can integrate with existing third-party applications, lab instruments, and devices to capture all data in a single data model. It has a low-code/no-code workflow designer and hundreds of pre-built connectors to enable rapid time-to-value and end-to-end automation. By leveraging a single data model, L7|ESP enables advanced bioinformatics, AI, and ML to offer novel scientific and operational insights. L7|ESP addresses data and lab management needs in life sciences, particularly in: ● Research and Diagnostics ● Pharma and CDMO ● Clinical Sample Management Resource Center: l7informatics dot com/resource-center

Scispot powers life science labs with a unified LabOS™ platform, combining ELN, LIMS, SDMS, QMS, and AI in one configurable, no-code system. Built for CROs, Molecular Diagnostics, Pathology, Pharma QC, and Drug Discovery, Scispot streamlines sample management, inventory automation, and regulatory compliance. Connect with 200+ lab instruments and thousands of apps to eliminate data silos while maintaining FDA 21 CFR Part 11, GxP, GDPR, and HIPAA compliance. Scispot's AI tools transform experimental data into actionable insights, with flexible workflows that adapt as research evolves—without IT support. Trusted by 1000+ scientists globally, Scispot enables rapid deployment so teams focus on science, not administration. Accelerate discoveries, ensure compliance, and scale operations with a platform purpose-built for modern biotech innovation.

Alchemite provides AI-augmented physical modeling and solutions that help organizations extract actionable insights from experimental and simulation data by combining machine learning with physics-informed models to improve prediction accuracy, reduce experimental costs, and optimize product and process development. Its solutions span materials discovery and design, predictive modelling of performance and reliability, multiscale modelling that connects atomistic to macroscopic behaviour, and automation of workflow tasks such as data integration, surrogate modelling, and model validation. It supports physics-aware neural networks and hybrid modelling approaches that respect underlying scientific laws while learning from data to enable faster and more accurate simulations, reduced reliance on expensive physical testing, and improved decision-making. Intellegens’ tools are applied in areas such as battery performance prediction, chemical process optimization, etc.

ScienceDesk data automation demystifies the use of artificial intelligence in materials sciences. A practical tool for your team to add and apply the newest AI algorithms on an everyday basis. Customizable properties, universal identifiers, QR-codes and a powerful textual-numeric search engine that links sample and experimental data. ScienceDesk is an innovative platform for scientists and engineers to interact with, collaborate on and obtain insights into their experimental data. Unfortunately, the potential of this asset is not fully exploited due to the variety of data formats and the strong dependence on experts to manually extract specific information. The ScienceDesk research data management system solves this problem by combining documentation and data analysis in a cleverly-engineered data structure. Researchers and scientists are empowered by our algorithms to gain total control of their data. They can not only share datasets, but even the analysis know-how.

Eliminate inefficiencies and errors in the entire reagent and model system selection process that cause costly experimental failure. Accelerate projects by selecting reagents and model systems in 30 seconds vs. 12 weeks. Reduce hard cost of consumables and save millions per year. Empower organizational purpose by restoring research time to scientists. See real business impact from AI with a proven, turnkey application. Over 41,200 scientists in 15 of the top 20 pharmaceutical companies and more than 4,450 academic institutions use BenchSci’s AI-Assisted Antibody Selection to plan more successful experiments, with proven savings of millions per year in hard costs alone. But antibodies constitute just 40-50% of reagent failures. Get comprehensive experimental evidence, reagent and model system catalog data, and independent validations within a single intuitive interface. Real world experiment data from 11.2 million scientific publications, including closed-access papers.

Recursion is a TechBio company focused on transforming drug discovery by combining biology, data, and artificial intelligence. Founded over a decade ago, the company pioneered the use of large-scale cellular imaging to train AI models that decode the biological drivers of disease. Recursion’s mission is to deliver better medicines through novel insights and precision design, reducing the high failure rates of traditional drug development. Its proprietary Recursion OS platform integrates massive biological datasets with machine learning to accelerate discovery from target identification to clinical development. The company has built an advanced pipeline of potential first-in-class and best-in-class therapies targeting aggressive cancers and rare diseases. Automated wet labs and robotics enable millions of experiments per week, feeding continuous learning into its AI models.

Clara’s domain-specific tools, AI pre-trained models, and accelerated applications are enabling AI breakthroughs in numerous fields, including medical devices, imaging, drug discovery, and genomics. Explore the end-to-end pipeline of medical device development and deployment with the Holoscan platform. Build containerized AI apps with the Holoscan SDK and MONAI, and streamline deployment in next-generation AI devices with the NVIDIA IGX developer kits. The NVIDIA Holoscan SDK includes healthcare-specific acceleration libraries, pre-trained AI models, and reference applications for computational medical devices.

NVIDIA® Parabricks® is the only GPU-accelerated suite of genomic analysis applications that delivers fast and accurate analysis of genomes and exomes for sequencing centers, clinical teams, genomics researchers, and high-throughput sequencing instrument developers. NVIDIA Parabricks provides GPU-accelerated versions of tools used every day by computational biologists and bioinformaticians—enabling significantly faster runtimes, workflow scalability, and lower compute costs. From FastQ to Variant Call Format (VCF), NVIDIA Parabricks accelerates runtimes across a series of hardware configurations with NVIDIA A100 Tensor Core GPUs. Genomic researchers can experience acceleration across every step of their analysis workflows, from alignment to sorting to variant calling. When more GPUs are used, a near-linear scaling in compute time is observed compared to CPU-only systems, allowing up to 107X acceleration.

Accuracy, speed, confidence. Introducing generative AI to commercial biopharma. Simplify the labor-intensive process of collecting, organizing, and inspecting vast amounts of complex data. Get straight to decision-critical insights with 100% confidence, every time. With our AI-powered data manipulation and verification platform, you'll never lose track of your workstreams again. Gather, refine, and check your data, all in one place. Search public and private databases by key drug characteristics. Segment drugs and trials by detailed patient profiles. Extract the data you need in plain English. Support your findings by linking answers back to their source. Focus your time and energy on synthesizing high-quality outputs from data rather than menially sifting through it. Our specialized LLMs enable researchers to perform asset scans 4.8x faster than by hand. We index over 38M scientific publications, conference abstracts, and clinical trials. All the data you need, when you need it.

Evo 2 is a genomic foundation model capable of generalist prediction and design tasks across DNA, RNA, and proteins. It utilizes a frontier deep learning architecture to model biological sequences at single-nucleotide resolution, achieving near-linear scaling of compute and memory relative to context length. Trained with 40 billion parameters and a 1 megabase context length, Evo 2 processes over 9 trillion nucleotides from diverse eukaryotic and prokaryotic genomes. This extensive training enables Evo 2 to perform zero-shot function prediction across multiple biological modalities, including DNA, RNA, and proteins, and to generate novel sequences with plausible genomic architecture. The model's capabilities have been demonstrated in tasks such as designing functional CRISPR systems and predicting disease-causing mutations in human genes. Evo 2 is publicly accessible via Arc's GitHub repository and is integrated into the NVIDIA BioNeMo framework.

Biohub is an open platform for building on the world model of protein biology. It provides access to the ESM family of models, including ESMC, ESMFold2, and ESM3, along with interactive tools and developer resources for protein science research. ESMC is a state-of-the-art protein language model trained on billions of evolutionary sequences, building representations that capture fundamental mechanisms of protein structure and function. It powers functional analysis, structure prediction, protein design, and the exploration of evolutionary relationships between proteins. ESMFold2 predicts high-resolution, all-atom 3D structures of biomolecular complexes directly from sequence, with optional multiple sequence alignment input for enhanced accuracy on challenging targets. ESM3 jointly models sequence, structure, and function, enabling controllable generation of novel proteins by conditioning on any combination of these modalities.

Opscidia is a collaborative platform that brings all the scientific and technological information. It is a scientific hub based on the latest AI technologies with multiple monitoring features to view the best scientific information in a few clicks. Scientific and technological monitoring is a time-consuming process, but essential for innovation. Opscidia has taken up the challenge of offering the best scientific information in a few clicks. Opscidia's scientific hub allows businesses to optimize monitoring time so that teams can invest more in R&D projects, client deliverables, and daily monitoring tasks. The features of the Opscidia platform include: - Identify emerging concepts - Measure scientific trends related to a product or a technology - Write scientific reports faster thanks to artificial intelligence - Collaborate and share scientific information

Microsoft Discovery is a new agentic platform designed to revolutionize research and development (R&D) by empowering scientists and engineers with AI-driven collaboration and high-performance computing (HPC). Built on Azure, this platform enables researchers to work alongside specialized AI agents that help accelerate the discovery process through advanced knowledge reasoning, hypothesis formulation, and experimental simulations. The platform's graph-based knowledge engine facilitates complex, contextual reasoning over vast amounts of scientific data, promoting transparency and accountability while speeding up the discovery cycle. By automating and enhancing research tasks, Microsoft Discovery offers an extensible, enterprise-ready solution that integrates seamlessly with existing tools and datasets.

Scitara DLX™ offers a rapid connectivity infrastructure for any instrument in the life science laboratory in a fully compliant and auditable cloud-based platform. Scitara DLX™ is a universal digital data infrastructure that connects any instrument, resource, app and software in the laboratory. The cloud-based, fully auditable platform connects all data sources across the lab, allowing the free flow of data across multiple end points. This allows scientists to devote their time to scientific research, not waste it solving data issues. DLX curates and corrects data in flight to support the development of accurate, properly structured data models that feed AI and ML systems. This supports a successful digital transformation strategy in the pharma and biopharma industries. Unlocking insights from scientific data enables faster decision-making in drug discovery and development, helping bring drugs to market more quickly.