Alternatives to Axiomatic AI
Compare Axiomatic AI alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Axiomatic AI in 2026. Compare features, ratings, user reviews, pricing, and more from Axiomatic AI competitors and alternatives in order to make an informed decision for your business.
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1
TrustInSoft Analyzer
TrustInSoft
TrustInSoft Analyzer is a C/C++/Rust source code analyzer powered by formal methods, mathematical & logical reasonings that allow for exhaustive analysis of source code. This analysis can be run without false positives or false negatives, so that every real bug in the code is found. Developers receive several benefits: a user-friendly graphical interface that directs developers to the root cause of bugs, and instant utility to expand the coverage of their existing tests. Unlike traditional source code analysis tools, TrustInSoft’s solution is not only the most comprehensive approach on the market but is also progressive, instantly deployable by developers, even if they lack experience with formal methods, from exhaustive analysis up to a functional proof that the software developed meets specifications. Companies who use TrustInSoft Analyzer reduce their verification costs by 4, efforts in bug detection by 40, and obtain an irrefutable proof that their software is safe and secure. -
2
Leanstral
Mistral AI
Leanstral is an open-source code agent developed by Mistral AI specifically designed to work with the Lean 4 proof assistant. The model focuses on generating code while also formally verifying its correctness against strict mathematical or software specifications. Unlike traditional coding assistants, Leanstral integrates directly with formal proof systems to ensure that generated code satisfies defined logical requirements. Its architecture is optimized for proof engineering tasks and operates efficiently with sparse model parameters. Leanstral is released under the Apache 2.0 license, making it freely accessible for developers, researchers, and organizations to use and customize. The model is designed to operate within real-world formal repositories rather than isolated problem environments. By combining code generation with formal verification, Leanstral aims to reduce the need for manual human review in complex software and mathematical development.Starting Price: Free -
3
Noah AI
Noah AI
Noah AI is an AI-powered research assistant tailored specifically for life-sciences professionals, designed to automate and accelerate complex workflows across biomedical research, clinical development, and commercial strategy. It offers an “Agent” mode that plans and executes multi-step tasks by conducting intelligent web searches, querying trusted scientific databases (such as PubMed and FDA/NIH sources), summarizing high-impact papers, mining clinical-trial results, and generating professional-grade reports, while a lighter “Search” mode allows rapid, reliable access to domain-specific content summaries. With integrations across comprehensive medical/public-health data, AI-driven insights, and real-time news tracking of global R&D activity and conference intelligence, Noah AI enables researchers, biotech investors, and clinicians to go from question to insight in a fraction of the time.Starting Price: $12.40 per month -
4
Harmonic Aristotle
Harmonic
Aristotle is the first AI model built from the ground up as a Mathematical Superintelligence (MSI), designed to deliver provably correct solutions to complex quantitative problems without hallucinations. When prompted with natural‑language math questions, it formalizes them in Lean 4, solves them via formally verified proofs, and returns both the proof and a natural‑language explanation. Unlike conventional language models that rely on probabilistic outputs, Aristotle’s MSI architecture replaces guesswork with provable logic, transparently flagging any errors or inconsistencies. The AI is accessible through a web interface and a developer API, enabling researchers to integrate its rigorous reasoning into workflows across fields such as theoretical physics, engineering, and computer science. -
5
GPT-Rosalind
OpenAI
GPT-Rosalind is a purpose-built frontier reasoning model developed by OpenAI to accelerate scientific research across biology, drug discovery, and translational medicine. It is designed specifically for life sciences workflows, where researchers must navigate large volumes of literature, experimental data, and specialized databases to generate and validate new ideas. It combines deep domain understanding in areas such as chemistry, genomics, protein engineering, and disease biology with advanced tool-use capabilities, allowing it to interact with scientific databases, analyze experimental outputs, and support complex, multi-step reasoning tasks. It can assist with evidence synthesis, hypothesis generation, literature review, sequence interpretation, and experimental planning, helping scientists move faster from raw data to actionable insights. GPT-Rosalind transforms complex, time-intensive research processes into more efficient AI-assisted workflows. -
6
Edison Analysis
Edison Scientific
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.Starting Price: $50 per month -
7
Microsoft Discovery
Microsoft
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. -
8
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. -
9
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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OpenAI deep research
OpenAI
OpenAI's deep research is an AI-powered tool designed to autonomously conduct complex, multi-step research tasks across various domains, such as science, coding, and mathematics. By analyzing user-provided inputs—such as questions, text documents, images, PDFs, or spreadsheets—the system formulates a structured research plan, gathers relevant information, and delivers comprehensive responses within minutes. It also provides process summaries with citations, helping users verify sources. While this tool significantly accelerates research efficiency, it may occasionally produce inaccuracies or struggle to differentiate between authoritative sources and misinformation. Currently available to ChatGPT Pro users, deep research represents a step toward AI-driven knowledge discovery, with ongoing improvements planned for accuracy and response time. -
11
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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NVIDIA PhysicsNeMo
NVIDIA
NVIDIA PhysicsNeMo is an open source Python deep-learning framework for building, training, fine-tuning, and inferring physics-AI models that combine physics knowledge with data to accelerate simulations, create high-fidelity surrogate models, and enable near-real-time predictions across domains such as computational fluid dynamics, structural mechanics, electromagnetics, weather and climate, and digital twin applications. It provides scalable, GPU-accelerated tools and Python APIs built on PyTorch and released under the Apache 2.0 license, offering curated model architectures including physics-informed neural networks, neural operators, graph neural networks, and generative AI–based approaches so developers can harness physics-driven causality alongside observed data for engineering-grade modeling. PhysicsNeMo includes end-to-end training pipelines from geometry ingestion to differential equations, reference application recipes to jump-start workflows.Starting Price: Free -
13
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. -
14
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. -
15
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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Alchemite
Intellegens
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. -
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FigCanvas
FigCanvas
FigCanvas is an AI scientific figure generator for researchers, built to create scientific illustrations, flowcharts, and data visualizations in one place. Users can describe a figure in plain language, paste methodology text, or upload a dataset, then get a first draft in under two minutes. It supports workflows for scientific illustration, data visualization, and flowchart creation, helping researchers generate pathway diagrams, cell biology figures, molecular mechanism figures, lab schematics, bar charts, scatter plots, heatmaps, volcano plots, and other research visuals without design skills or coding knowledge. FigCanvas is built specifically for scientific communication, using research-specific visual training informed by real scientific figures so outputs better match the structure, composition, and style expected in academic work.Starting Price: $12.50 per month -
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ChemCopilot
ChemCopilot
ChemCopilot is an AI-native chemical formulation and product lifecycle management platform designed to transform how scientists, engineers, and R&D teams design, test, optimize, and manage chemical products and processes by combining advanced artificial intelligence with domain-specific chemistry knowledge, regulatory data, simulation capabilities, and real-time insights. It automates validation of product labels, ingredient restrictions, and safety data sheets against global compliance frameworks, eliminating disconnected spreadsheets and manual review while providing audit trails and real-time alerts to support regulatory adherence. ChemCopilot accelerates innovation by simulating chemical reactions, molecular interactions, and process workflows to predict formulation performance and outcomes that traditional general-purpose tools cannot provide, and it integrates real-time data from laboratory and industrial systems to drive data-driven decisions. -
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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. -
20
ESMC
Biohub
ESMC is the latest in the ESM family of protein language models, establishing a new frontier in representation learning for protein biology. Trained on billions of evolutionary sequences, it learns representations that reflect a mechanistic reduction of protein structure and function. The model is built on a transformer architecture, supports sequences as its core modality, and is trained on up to 6 billion proteins. ESMC is designed for protein science research, including structure prediction, function annotation, protein design, and understanding evolutionary relationships between proteins. It can generate novel proteins from partial sequence, structure, or functional constraints, helping researchers explore new possibilities in protein design and biological discovery. The Biohub Platform provides access to ESMC through the API and the ESM Python package, with quickstart resources for installing the package, creating an API key, connecting to the platform.Starting Price: Free -
21
DeepSeek R1
DeepSeek
DeepSeek-R1 is an advanced open-source reasoning model developed by DeepSeek, designed to rival OpenAI's Model o1. Accessible via web, app, and API, it excels in complex tasks such as mathematics and coding, demonstrating superior performance on benchmarks like the American Invitational Mathematics Examination (AIME) and MATH. DeepSeek-R1 employs a mixture of experts (MoE) architecture with 671 billion total parameters, activating 37 billion parameters per token, enabling efficient and accurate reasoning capabilities. This model is part of DeepSeek's commitment to advancing artificial general intelligence (AGI) through open-source innovation.Starting Price: Free -
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Ansys Lumerical Multiphysics is a photonics component simulation software that enables the seamless design of photonic components by capturing multiphysics effects, including optical, thermal, electrical, and quantum well interactions, within a unified design environment. Tailored for design engineering workflows, this intuitive product design software offers a fast user experience, facilitating rapid design exploration and providing detailed insights into real-world product performance. It combines live physics and accurate high-fidelity simulation into an easy-to-use interface, supporting faster time-to-market. Key features include a finite element design environment, integrated multiphysics workflows, comprehensive material models, and capabilities for automation and optimization. The suite of solvers and seamless workflows in Lumerical Multiphysics accurately capture the interplay of physical effects in modeling both passive and active photonic components.
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23
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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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. -
25
Noteweave
Noteweave
Noteweave is an Intelligent Research Machines platform that helps teams go from research to executable production plans. It is built to stress-test scientific research, translate papers into validated experiments, and run R&D faster from one research-first workspace. Deep Analysis pressure-tests methods, evaluations, and robustness so failure modes surface before they reach production, helping teams detect production faults in academic papers pre-emptively, find missing evals, set up discrepancies, or misleading robustness trends, and identify technical faults faster. Explore searches across millions of papers, datasets, and code repositories, then synthesizes them into runnable production plans with traceable evidence. Noteweave helps users discover relevant research signals across 3 million+ AI/ML publications, optimize plans against constraints such as GPU utilization, translate academic methods into reproducible steps, and validate evaluation strategies more reliably.Starting Price: $18.99 per month -
26
Kosmos
Edison Scientific
Kosmos is the next-generation “AI Scientist” developed to perform autonomous discovery by reading vast amounts of scientific literature and executing code to reach novel conclusions. It uses structured world models to efficiently incorporate information gathered over hundreds of agent trajectories and maintain coherence throughout tens of millions of tokens, thereby transcending the context-length limits of earlier language-model-based tools. A typical Kosmos run might read about 1,500 papers and execute 42,000 lines of analysis code, enabling it to perform in one day what beta users estimated would take a human scientist six months. Its outputs are fully traceable; each conclusion in a Kosmos report can be linked to the specific lines of code and passages in the literature that inspired it, allowing for full auditability of its reasoning.Starting Price: $50 per month -
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OPTIMICA Compiler Toolkit
MODELON
Modelon’s OPTIMICA Compiler Toolkit, the most advanced Modelica-based mathematical engine on the market, offers users a powerful solution for the automation, simulation and optimization of system behaviors throughout the model-based design cycle. Trusted as the compiler for Modelon Impact, OPTIMICA enables users to build multi-domain physical systems by choosing from thousands of available model components. OPTIMICA’s state-of-the-art solvers empower evaluation of complex physical systems – supporting transient simulations as well as steady-state computations and dynamic optimization. The sophisticated mathematical engine can manipulate and simplify models to improve performance and robustness, serving industries and applications ranging from automotive and active safety to energy and power plant optimization. To meet the increased need for regulating power in today’s energy market, start-up optimization of thermal power plants is a key industrial need. -
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Raylectron
Raylectron
Raylectron took many years of research and testing. Creating such software is not an easy task. While Raytracing exist already for many years prior to Raylectron, they are not photorealistic. To achieve photorealism, tracing the light path to illuminate the objects in a scene requires the understanding of the law of physics, such as photons and how they interact with the surface of the object they hit. In real life, photons travel at the speed of light, hence everything is illuminated almost instantly (to our perception). But as a computer program, this can not be done so easily. First, speed is a big issue. Computers do not calculate anywhere near the speed of light. Furthermore, the mathematics involved is extremely complex. All of the features combined into one single software. Select from a wide range of illumination and a combination of them. Texturing your model has never been so easy, in real-time!Starting Price: $99.95 per license -
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HeyScience
HeyScience
Finding, reading, and analyzing every relevant scientific research article can quickly turn into a time-consuming, tedious task. Designed by fellow academics, our AI-powered scientific research assistant lets you focus on what you love doing most: conducting research. Stay current with an overview of what researchers in your field are working on, familiarize yourself with a specific scientist’s contributions, and assess the possibility of future collaborations. Conduct a month’s worth of literature research in a few minutes. Search and sort through millions of papers across all academic fields to find relevant knowledge in one click. Read a short, simplified summary of scientific articles and grasp key concepts and findings within minutes. Leverage our dedicated AI-reviewer for instant feedback on your manuscript prior to conference or journal submission. -
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SciDraw
SciDraw
SciDraw AI is an AI-powered scientific figure and illustration maker for creating publication-ready figures, diagrams, data charts, graphical abstracts, posters, theses, slides, and teaching visuals through a UI-first web workflow. It combines scientific illustration and data visualization in one platform, helping researchers, graduate students, educators, and science communicators move from idea to polished visual without needing design experience. Users can start with a template or describe a scientific concept, then refine the result through multi-round AI optimization and download the finished figure for a paper, thesis, slide deck, or poster. SciDraw AI supports text-to-image generation for professional scientific illustrations, sketch and image editing for transforming hand-drawn sketches or references into polished visuals, and smart data charts that turn CSV or Excel data into publication-ready figures.Starting Price: $10 per month -
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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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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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Edison Scientific
Edison Scientific
Edison Scientific is an AI platform designed to automate and accelerate scientific research, enabling users to move from hypothesis to validated results within a single environment. The platform integrates literature synthesis, data analysis, and molecular design workflows, allowing research teams to complete end-to-end scientific investigations at dramatically increased speed. At its core is Kosmos, an autonomous research system that performs hundreds of research tasks in parallel, transforming multimodal datasets into comprehensive reports with validated findings and publication-ready figures. Kosmos synthesizes scientific literature, public databases, and proprietary datasets, identifies novel therapeutic targets, uncovers biological mechanisms, and supports the iterative design and optimization of molecular candidates. Validated in real research settings, Kosmos has demonstrated the ability to achieve results that typically require months of human effort in a single day.Starting Price: $50 per month -
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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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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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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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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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COMSOL Multiphysics
Comsol Group
Simulate real-world designs, devices, and processes with multiphysics software from COMSOL. General-purpose simulation software based on advanced numerical methods. Fully coupled multiphysics and single-physics modeling capabilities. Complete modeling workflow, from geometry to postprocessing. User-friendly tools for building and deploying simulation apps. The COMSOL Multiphysics® software brings a user interface and experience that is always the same, regardless of engineering application and physics phenomena. Add-on modules provide specialized functionality for electromagnetics, structural mechanics, acoustics, fluid flow, heat transfer, and chemical engineering. Choose from a list of LiveLink™ products to interface directly with CAD and other third-party software. Deploy simulation applications with COMSOL Compiler™ and COMSOL Server™. Create physics-based models and simulation applications with this software platform. -
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Symbiotic EDA Suite
Symbiotic EDA
Find bugs early and raise the confidence in your design by using formal checks and formal properties. Apply formal early on in the design process wherever it makes sense for your application. Use formal cover traces to further your design understanding and answer hard questions about the design under test. Apply formal safety properties to produce shorter and more insightful traces than simulation could ever generate. Employ formal proofs to ensure correctness of your design, use mutation cover to gain confidence in your simulation-based verification strategy, and speed up writing of test cases by guiding the process with formal cover traces. Unbounded and bounded verification of safety properties. Reachability-check and bounds-detection for cover properties -
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Tezos
Tezos
Security focused. Upgradable. Built to last. Tezos is an open-source platform for assets and applications backed by a global community of validators, researchers, and builders. Tezos addresses key barriers facing blockchain adoption to date: smart contract safety, long-term upgradability, and open participation. Tezos is designed to provide the safety and code correctness required for assets and other high value use cases. Its native smart contract language, Michelson, facilitates formal verification, a methodology commonly used in mission-critical environments such as the aerospace, nuclear, and semiconductor industries. Tezos’ modular architecture and formal upgrade mechanism allow the network to propose and adopt new technological innovations smoothly as they emerge. These aspects, combined with Tezos’ on-chain invoicing mechanism, enable the protocol to remain the state-of-the-art long into the future — without sacrificing community consensus. -
41
Claude Opus 3
Anthropic
Opus, our most intelligent model, outperforms its peers on most of the common evaluation benchmarks for AI systems, including undergraduate level expert knowledge (MMLU), graduate level expert reasoning (GPQA), basic mathematics (GSM8K), and more. It exhibits near-human levels of comprehension and fluency on complex tasks, leading the frontier of general intelligence. All Claude 3 models show increased capabilities in analysis and forecasting, nuanced content creation, code generation, and conversing in non-English languages like Spanish, Japanese, and French.Starting Price: Free -
42
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. -
43
Sapio Sciences
Sapio Sciences
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. -
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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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L-Edit Photonics
Siemens
Design your photonic integrated circuit in a layout-centric flow. The designer can implement their design using either a drag-and-drop or a script-driven methodology. Both of those are in the same full custom IC design layout editor that drives the physical verification and tape-out processes. L-Edit Photonics enables the fast creation of a photonic design using a drag-and-drop methodology in an IC layout editor, without having to write a single line of code. Once the design is completed, a netlist can be extracted for photonic simulation. PIC design in a complete IC layout editor, Create a layout without writing a line of code. Supports a layout-centric design flow where a schematic is not needed. Schematic flow optional with S-Edit. A simulation netlist can be created as input into a photonic simulator. Photonic simulation is supported through integration with our partners. Photonic PDKs are available from multiple foundries. -
46
Breathe
Breathe
Breathe Battery Technologies provides a physics-based battery software toolchain that enables engineers and OEMs to design, simulate, validate, and control advanced battery systems with greater speed, accuracy, and performance than traditional empirical workflows. Its suite spans from cell design and simulation software, allowing rapid evaluation of ageing, thermal behavior, SoC/SoH estimators and system-level trade-offs, to embedded adaptive charging firmware that dynamically manages internal electrochemical states to deliver faster charging and longer life without hardware changes. Breathe’s software integrates physics-based modelling and real-time control into the battery development lifecycle so teams can reduce risk, iterate quickly, and make data-driven decisions while lowering cost and increasing flexibility. Breathe’s products are trusted by global brands and partners, including Volvo and OPPO, for applications that improve charging performance, extend cycle life, etc.Starting Price: Free -
47
L7|ESP
L7 Informatics
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 -
48
Scitara DLX
Scitara
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. -
49
Sci-Bot
Sci-Bot
Sci-Bot is an AI-powered research assistant built on top of Sci-Hub, designed to answer user questions by directly searching and analyzing scientific literature instead of generating responses from general training data. It works by scanning a vast database of full-text academic papers and extracting relevant findings to produce answers grounded in published research, often including references and links to the original studies. It presents itself as a simple interface where users can ask questions in multiple languages, and the system automatically searches for relevant keywords, retrieves academic articles, and synthesizes information into a structured response. It follows a step-by-step process similar to a human researcher, showing intermediate searches and sources before delivering a final answer. A key focus is on reducing hallucinations by relying on existing scientific papers rather than purely generative outputs, and it can provide direct access to full-text documents.Starting Price: Free -
50
Charlie
Emerit Science
Charlie is a sovereign AI scientific agent for researchers and laboratories, specialized in biomedical research and built to accelerate scientific work with precise, sourced answers. It helps users conduct literature reviews, analyze scientific documents, organize research information, and move faster through R&D workflows while keeping traceability at the center of every response. Researchers can ask questions in natural language and get answers extracted directly from scientific documents, with page-level citations that make each source verifiable. Charlie can search simultaneously through hundreds of PDFs, synthesize information, compare articles, understand scientific context, and help users focus on discoveries instead of manual document review. Its research workspace includes libraries, projects, notes, shared collections, PDF reading, highlighting, annotation, and team collaboration, so important passages, references, and insights stay organized across devices.Starting Price: €12 per month
