Best AI Science Software - Page 2
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FigEditor
FigEditor
FigEditor is an AI scientific figure generator built to turn research ideas, sketches, references, and existing images into polished, editable visuals for papers, posters, and presentations. Start with a text prompt describing a mechanism, pathway, workflow, experiment, or architecture, upload a rough sketch, or provide a reference image to guide composition, palette, density, and visual hierarchy. FigEditor creates a structured draft with clear labels, arrows, and organized layout, then lets researchers revise text, shapes, colors, connectors, modules, and individual regions without rebuilding the entire figure. Existing PNG or JPG figures can also be vectorized into scalable assets for further editing. Its AI Scientific Illustration workflow uses a multi-step pipeline to generate a draft, detect visual elements, extract clean assets, assemble a structured SVG, and refine the final vector output.Starting Price: $9.50 per month -
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ResoluteAI
ResoluteAI
ResoluteAI's secure platform lets you search aggregated scientific, regulatory, and business databases simultaneously. Combined with our interactive analytics and downloadable visualizations, you can make connections that lead to breakthrough discoveries. Nebula is ResoluteAI's enterprise search product for science. We apply structured metadata and a range of AI capabilities to your institutional knowledge. This includes NLP, OCR, image recognition, and transcription, making your proprietary information easily findable and accessible. With Nebula, you have the power to unlock the hidden value in your research, experiments, market intelligence, and acquired assets. Structured metadata created from unstructured text, semantic expansion, conceptual search, and document similarity search. -
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ScienceDesk
ScienceDesk
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. -
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BenchSci
BenchSci
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. -
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Iris.ai
Iris.ai
Iris.ai is a world-leading and award-winning AI engine for scientific text understanding. It is a comprehensive platform for all research-related knowledge processing needs. Our Researcher Workspace solution provides smart search and a wide range of smart filters, reading list analysis, auto-generated summaries, autonomous extraction, and systematising of data. Iris.ai allows humans to focus on value creation by saving 75% of a researcher’s time, doing specialised, interdisciplinary field analysis to an above human level of accuracy. Its 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. Its machine builds a comprehensive knowledge graph containing all entities and their linkages to allow humans to learn from it, use it, and give feedback to the system. Applying these features to scientific and technical text is a complicated challenge few others can achieve. -
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Recursion
Recursion
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. -
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AlphaFold
DeepMind
These exquisite, intricate machines are proteins. They underpin not just the biological processes in your body but every biological process in every living thing. They’re the building blocks of life. Currently, there are around 100 million known distinct proteins, with many more found every year. Each one has a unique 3D shape that determines how it works and what it does. But figuring out the exact structure of a protein remains an expensive and often time-consuming process, meaning we only know the exact 3D structure of a tiny fraction of the proteins known to science. Finding a way to close this rapidly expanding gap and predict the structure of millions of unknown proteins could not only help us tackle disease and more quickly find new medicines but perhaps also unlock the mysteries of how life itself works. -
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NVIDIA BioNeMo
NVIDIA
BioNeMo is an AI-powered drug discovery cloud service and framework built on NVIDIA NeMo Megatron for training and deploying large biomolecular transformer AI models at a supercomputing scale. The service includes pre-trained large language models (LLMs) and native support for common file formats for proteins, DNA, RNA, and chemistry, providing data loaders for SMILES for molecular structures and FASTA for amino acid and nucleotide sequences. The BioNeMo framework will also be available for download for running on your own infrastructure. ESM-1, based on Meta AI’s state-of-the-art ESM-1b, and ProtT5 are transformer-based protein language models that can be used to generate learned embeddings for tasks like protein structure and property prediction. OpenFold, a deep learning model for 3D structure prediction of novel protein sequences, will be available in BioNeMo service. -
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NVIDIA Clara
NVIDIA
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. -
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NVIDIA Parabricks
NVIDIA
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. -
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Reliant AI
Reliant AI
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. -
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Cure AI
Cure AI
Cure AI is an advanced medical research engine that utilizes artificial intelligence to provide comprehensive access to over 26 million scientific articles from PubMed. It offers AI-powered natural language search capabilities, allowing users to input research queries in conversational language, which the system interprets to deliver precise results. The platform features advanced search parameters, enabling users to refine results by journal, publication date, and other criteria for tailored research needs. Cure AI ranks evidence based on quality and relevance, considering factors such as journal h5-index, citation count, and publication type, ensuring that users receive the most pertinent and verified information. Additionally, it provides seamless navigation between AI-generated insights and primary literature sources, facilitating efficient literature review and analysis. The platform includes quick citation tools, allowing users to copy or share citations with a single click.Starting Price: $15 per month -
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biologit MLM-AI
biologit
Biologit offers a comprehensive suite of software and services designed to enhance safety surveillance across various industries. Their flagship product, biologit MLM-AI, is an all-inclusive global and local medical literature monitoring platform powered by AI. This scientific literature monitoring platform is simple to use, fully web-enabled, and validated for compliance, providing productivity gains for human and veterinary pharmacovigilance. Key features include integrated search and configurable literature screening workflows delivering up to 70% productivity gains powered by AI, a flexible and validated SaaS platform that is GxP-ready and CFR-11 compliant, and a database hosting major global and local literature sources with automatic article de-duplication. In addition to its software solutions, Biologit offers consultancy services covering pharmacovigilance, veterinary pharmacovigilance, and more. -
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PubHive Navigator
PubHive
PubHive Navigator is an AI-powered software platform that streamlines scientific literature and safety workflows for life science companies of all sizes. It offers centralized end-to-end workflow solutions for literature review, curation, annotation, collaboration, searching, reporting, citing, and managing research. The platform features AI-powered smart workspaces for centralized literature management, collaborative research writing and team communication, reuse rights and document delivery integrations, and out-of-the-box workflows for different operation units. PubHive Navigator is designed to simplify enterprise scientific literature and safety information workflows, making it a flexible software platform for teams in drug safety and pharmacovigilance, medical affairs, clinical affairs, and R&D. -
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Evo 2
Arc Institute
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. -
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FutureHouse
FutureHouse
FutureHouse is a nonprofit AI research lab focused on automating scientific discovery in biology and other complex sciences. FutureHouse features superintelligent AI agents designed to assist scientists in accelerating research processes. It is optimized for retrieving and summarizing information from scientific literature, achieving state-of-the-art performance on benchmarks like RAG-QA Arena's science benchmark. It employs an agentic approach, allowing for iterative query expansion, LLM re-ranking, contextual summarization, and document citation traversal to enhance retrieval accuracy. FutureHouse also offers a framework for training language agents on challenging scientific tasks, enabling agents to perform tasks such as protein engineering, literature summarization, and molecular cloning. Their LAB-Bench benchmark evaluates language models on biology research tasks, including information extraction, database retrieval, etc. -
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Zochi
Intology
Zochi is the first AI system capable of autonomously completing the entire scientific research process, from hypothesis generation to peer-reviewed publication, producing state-of-the-art results. Unlike prior systems limited to narrow, predefined tasks, Zochi excels in addressing research challenges at the forefront of artificial intelligence. Its effectiveness is validated by multiple peer-reviewed publications accepted at ICLR 2025 workshops, underscoring Zochi's ability to generate novel and academically rigorous contributions. Zochi identified a critical bottleneck in AI development: cross-skill interference in parameter-efficient fine-tuning. When adapting models to multiple tasks simultaneously, improvements in one skill often degrade others. To address this, Zochi developed CS-ReFT (Compositional Subspace Representation Fine-tuning), focusing on representation editing rather than weight modifications. -
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Sciscoper
Sciscoper
Sciscoper is an AI powered research assistant that is used to streamline and accelerate the literature review process for STEM researchers, academics, and R&D teams. Researchers often deal with hundreds or thousands of scientific papers scattered across different sources, making it difficult to extract meaningful insights efficiently. Sciscoper solves this by using AI and natural language processing to automatically: Summarize scientific papers and research findings. Extract key insights, concepts, and relationships across documents. Generate literature reviews with citations in multiple reference styles. Organize and index papers into a structured, searchable knowledge base for easy discovery. This allows users to focus less on manual reading and note-taking, and more on analyzing results, identifying research gaps, and producing new scientific knowledge.Starting Price: $20/user/month -
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Claude Science
Anthropic
Claude Science is an AI-powered scientific research application that helps researchers perform data analysis, literature review, computational workflows, and manuscript preparation within a single environment. Built on Claude models, the application integrates scientific databases, research tools, electronic lab notebooks, HPC systems, and domain-specific software to support end-to-end research workflows. It manages computational environments across local machines, Linux systems, and high-performance computing clusters while maintaining reproducible records of every analysis. Researchers can generate publication-quality figures, perform complex analyses, and trace every result back to the underlying code, environment, and conversation. Claude Science also supports specialized fields including genomics, proteomics, single-cell biology, structural biology, and cheminformatics through preconfigured scientific capabilities. -
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Gemini 3 Deep Think
Google
The most advanced model from Google DeepMind, Gemini 3, sets a new bar for model intelligence by delivering state-of-the-art reasoning and multimodal understanding across text, image, and video. It surpasses its predecessor on key AI benchmarks and excels at deeper problems such as scientific reasoning, complex coding, spatial logic, and visual-/video-based understanding. The new “Deep Think” mode pushes the boundaries even further, offering enhanced reasoning for very challenging tasks, outperforming Gemini 3 Pro on benchmarks like Humanity’s Last Exam and ARC-AGI. Gemini 3 is now available across Google’s ecosystem, enabling users to learn, build, and plan at new levels of sophistication. With context windows up to one million tokens, more granular media-processing options, and specialized configurations for tool use, the model brings better precision, depth, and flexibility for real-world workflows. -
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Prism
OpenAI
Prism is a free, LaTeX-native scientific writing workspace designed to streamline research collaboration and publishing. It brings drafting, compiling, and collaboration into a single cloud-based environment with no local setup required. Prism integrates GPT-5.2 directly into the writing workflow, providing AI-assisted proofreading, formatting, and literature search. Researchers can collaborate with unlimited contributors in real time while viewing instant compiled previews of their work. The platform is fully project-aware, allowing AI to understand the full context of a paper, including equations, references, and revisions. Built-in LaTeX rendering, citation management, and error checking reduce time spent on manual cleanup. Prism is designed to meet scientists where they already work, making it a modern standard for scientific writing. -
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BenevolentAI
BenevolentAI
BenevolentAI is an AI-enabled drug discovery platform and scientific technology company that unites advanced artificial intelligence, machine learning, and domain-specific science to accelerate the discovery, design, and development of new medicines for complex diseases by making sense of vast, diverse biomedical data and generating actionable scientific insights faster than traditional methods. Its proprietary Benevolent Platform ingests and harmonizes structured and unstructured biomedical information, including literature, genomics, clinical information, and multi-omics data, into a comprehensive knowledge graph, enabling scientists to reason across biological systems, generate hypotheses, predict novel drug targets, and design candidate molecules with higher confidence and lower failure rates. -
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Gemini for Science
Google
Gemini for Science powers scientific discovery with AI tools and resources built to support scientific endeavors. It brings together experimental tools on Google Labs and science workflows in Google Antigravity to accelerate research, sharpen reasoning, and help researchers explore the future of AI-powered scientific discovery. Literature Insights synthesizes scholarly literature to identify new research opportunities, create grounded research artifacts, and extract paper data into queryable tables mapped directly to source evidence. Hypothesis Generation uses a multi-agent system that simulates the scientific method to identify knowledge gaps, generate potential research directions, and propose testable research plans for breakthrough discoveries. Computational Discovery helps researchers discover models and algorithms by using an agentic research engine that generates and scores code variations based on user-defined optimization metrics. -
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Biohub
Biohub
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. -
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Everstar
Everstar
Everstar is an AI-native platform for accelerating nuclear power deployment through document intelligence, licensing support, regulatory workflows, engineering analysis, and nuclear compliance automation. Built for nuclear professionals, Everstar helps teams turn complex documentation into active intelligence so they can draft regulator-ready filings, surface precedents in minutes, compress siting timelines, and streamline work across the nuclear value chain without compromising safety. Its AI-powered nuclear intelligence is designed to solve the industry’s hardest administrative, regulatory, and engineering challenges with accuracy, traceability, and secure workflows. Everstar’s platform supports operating reactor licensing, reactor operations and engineering, new reactor licensing, radioactive materials users, manufacturing and supply chain teams, and regulators. -
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Voquill
Voquill
Voquill is the agentic OS for medical labs, built AI-native to run the lab’s core workflow from accessioning and case routing to reporting and sign-out, with agentic AI built into every step. Instead of forcing modern labs to work around legacy systems that do not scale or plug into today’s AI, Voquill provides a modern LIS where every stage of the case has an agent working alongside the team. For accessioning, agents read the requisition and build the order, so intake stops being data entry. Labs can scan the paper requisition and have an agent pull patient information, tests, and specimen details into a structured order, while the team reviews and approves instead of retyping. The original scan is kept forever, with a confidence score on every extracted field. For case distribution, cases route themselves to the right pathologist by subspecialty, current workload, and turnaround pressure, without a rules engine to babysit or morning triage to manage. -
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Differential Bio
Differential Bio
Differential Bio is a virtual scale-up platform for bioprocess optimization that makes microbial growth more predictable, scalable, and cost-effective through robotic lab automation and AI-driven insights. Its workflow begins with automated, high-throughput experiments that mimic large-scale stress factors in microliter environments and generate industry-relevant wet-lab data through liquid handling, fermentation, and measurement. Specialized AI models use that data to predict outcomes such as biomass growth, protein expression, cell viability, titer, production rate, yield, and cost. Through the web-based platform, teams can configure optimization goals and parameter ranges, run unlimited in-silico experiments, compare simulated fermentation outcomes, perform multi-objective optimization, and identify process conditions to implement at scale. -
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Opscidia
Opscidia
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 -
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Consensus
Consensus
Ask a question, get conclusions from research papers. Consensus uses AI to find answers in research papers. The best way to search is to ask a question. Focus on questions that researchers may have studied. Topics range from biology to social sciences. Scientific research is the most valuable, insight-filled source of data to ever exist. Yet, the current consumers of this information are the same people who are creating it. We are striving to build the tools that democratize scientific evidence and make the world a better place, by making it a more informed place. Consensus is built by machine learning, science, and technology experts from some of the world’s most innovative institutions. -
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Causaly
Causaly
Leverage the power of AI to expedite the journey from bench research and laboratory insights to the launch of life-changing therapies. Gain up to 90% in research productivity by reducing your reading time from months to minutes. Cut through the noise with a high-precision, high-accuracy search to navigate the ever-growing volume of scientific literature with ease. Save time, reduce bias and increase odds of novel discoveries. Deeply explore disease biology and conduct advanced target discovery. Causaly’s high-precision knowledge graph consolidates evidence from millions of publications, making deep, unbiased scientific exploration possible. Rapidly navigate biological cause-and-effect relationships without being an expert. Get a view of all scientific documents and uncover hidden connections. Causaly’s powerful AI machine reads millions of published biomedical literature to support better decision-making and research outcomes.