257 Integrations with R
View a list of R integrations and software that integrates with R below. Compare the best R integrations as well as features, ratings, user reviews, and pricing of software that integrates with R. Here are the current R integrations in 2026:
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1
Zepl
Zepl
Sync, search and manage all the work across your data science team. Zepl’s powerful search lets you discover and reuse models and code. Use Zepl’s enterprise collaboration platform to query data from Snowflake, Athena or Redshift and build your models in Python. Use pivoting and dynamic forms for enhanced interactions with your data using heatmap, radar, and Sankey charts. Zepl creates a new container every time you run your notebook, providing you with the same image each time you run your models. Invite team members to join a shared space and work together in real time or simply leave their comments on a notebook. Use fine-grained access controls to share your work. Allow others have read, edit, and run access as well as enable collaboration and distribution. All notebooks are auto-saved and versioned. You can name, manage and roll back all versions through an easy-to-use interface, and export seamlessly into Github. -
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RunCode
RunCode
RunCode offers online developer workspaces, which are environments that allow you to work on code projects in a web browser. These workspaces provide you with a full development environment, including a code editor, a terminal, and access to a range of tools and libraries. They are designed to be easy to use and allow you to get started quickly without the need to set up a local development environment on your own computer.Starting Price: $20/month/user -
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ERNIE Bot
Baidu
ERNIE Bot is an AI-powered conversational assistant developed by Baidu, designed to facilitate seamless and natural interactions with users. Built on the ERNIE (Enhanced Representation through Knowledge Integration) model, ERNIE Bot excels at understanding complex queries and generating human-like responses across various domains. Its capabilities include processing text, generating images, and engaging in multimodal communication, making it suitable for a wide range of applications such as customer support, virtual assistants, and enterprise automation. With its advanced contextual understanding, ERNIE Bot offers an intuitive and efficient solution for businesses seeking to enhance their digital interactions and automate workflows.Starting Price: Free -
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Kodezi
Kodezi
Let Kodezi auto-summarize your code in seconds. Kodezi is Grammarly for programmers. Generate, ask, search, and code anything in your codebase with KodeziChat. Your personal AI coding assistant! Kodezi doesn't just fix your code for you, it tells you why it’s wrong and how to prevent future bugs. Reduce unnecessary lines of code and syntax to ensure clean end results. Optimize your code for optimum efficiency. Debug code with detailed explanations. Swap from one framework or language to another in an instant, without losing context. When writing code, commenting and explanations are crucial for future maintenance. Generate code from text, input a project question or create an entire function all in seconds! Generate your code documentation. Translate code to another language. Optimize your code for optimum efficiency. Use our extension within your own IDE, never have to rely on opening up new tabs ever again. -
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ggplot2
ggplot2
ggplot2 is a system for declaratively creating graphics, based on The Grammar of Graphics. You provide the data, tell ggplot2 how to map variables to aesthetics, what graphical primitives to use, and it takes care of the details. ggplot2 is now over 10 years old and is used by hundreds of thousands of people to make millions of plots. That means, by-and-large, ggplot2 itself changes relatively little. When we do make changes, they will be generally to add new functions or arguments rather than changing the behavior of existing functions, and if we do make changes to existing behavior we will do them for compelling reasons. If you are new to ggplot2 you are better off starting with a systematic introduction, rather than trying to learn from reading individual documentation pages. -
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Amazon SageMaker provides all the tools and libraries you need to build ML models, the process of iteratively trying different algorithms and evaluating their accuracy to find the best one for your use case. In Amazon SageMaker you can pick different algorithms, including over 15 that are built-in and optimized for SageMaker, and use over 150 pre-built models from popular model zoos available with a few clicks. SageMaker also offers a variety of model-building tools including Amazon SageMaker Studio Notebooks and RStudio where you can run ML models on a small scale to see results and view reports on their performance so you can come up with high-quality working prototypes. Amazon SageMaker Studio Notebooks help you build ML models faster and collaborate with your team. Amazon SageMaker Studio notebooks provide one-click Jupyter notebooks that you can start working within seconds. Amazon SageMaker also enables one-click sharing of notebooks.
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7
Wasmer
Wasmer
Create apps that run everywhere, publish, share with the community, and deploy to the edge, globally. Serve sandboxed WebAssembly apps anywhere through a single runtime and do in days what others do in months. Using a binary for each platform and chip is the past. Rise above with lightweight containerized apps that simply run everywhere. Supports almost every programming language. Truly universal, runs everywhere & fast as native. Packages are limited by their languages no more. Collaborate across stacks, leverage the ecosystem, and contribute your own packages. Get the scalability of serverless and the reusability of the cloud. Deploy to the edge, save your users time and yourself money. Faster, affordable & indefinitely scalable. All languages are fully containerized & collaborative. Plug your own backend, compiler, or runner. Run apps at close to native speed and outperform the competition. -
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Shakker
Shakker
With Shakker you can turn your imagination into images, in seconds. AI image generation doesn't have to be clunky when you use Shakker. Whether you want to create images, change styles, combine components, or paint any parts, Shakker makes it smoother than ever for you with prompt suggestions and precise designs. Shakker revolutionizes image creation, you can simply upload a reference photo, and it recommends styles from a library of vast images, making it easy to craft the perfect image. Beyond style transformation, Shakker offers advanced editing tools like segmentation, quick selection, and lasso for precise inpainting. Shakker.AI operates on sophisticated AI algorithms that analyze input and generate images accordingly. It interprets user commands or prompts to produce images that align with specified styles and themes. The underlying technology seamlessly blends AI's computational power with artistic creativity, delivering both unique and high-quality outputs. -
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Gemma
Google
Gemma is a family of lightweight, state-of-the-art open models built from the same research and technology used to create the Gemini models. Developed by Google DeepMind and other teams across Google, Gemma is inspired by Gemini, and the name reflects the Latin gemma, meaning “precious stone.” Accompanying our model weights, we’re also releasing tools to support developer innovation, foster collaboration, and guide the responsible use of Gemma models. Gemma models share technical and infrastructure components with Gemini, our largest and most capable AI model widely available today. This enables Gemma 2B and 7B to achieve best-in-class performance for their sizes compared to other open models. And Gemma models are capable of running directly on a developer laptop or desktop computer. Notably, Gemma surpasses significantly larger models on key benchmarks while adhering to our rigorous standards for safe and responsible outputs. -
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XetaBase
Zetta Genomics
The unique XetaBase platform simplifies tertiary analysis, aggregating, indexing, and enriching secondary genomic data, enabling continual re-interpretation to unlock research and clinical insight. XetaBase accelerates data management and the cost-effective application of genomic data in the lab and clinic. XetaBase encompasses genomic scale, the greater the volume and complexity, the greater the insight and outcomes. XetaBase is a genomic-native technology, built on the open-source, OpenCB software platform to meet the scale, speed, and re-interpretation demands of genomic medicine. Zetta Genomics delivers genomic data management fit for the precision medicine age. XetaBase is a completely novel solution to the challenges of genomic data. It sweeps away obsolete flat file approaches to bring meaningful and actionable genomic data into the lab and the clinic. XetaBase empowers continual re-interpretation while scaling seamlessly as databases grow to encompass genome sequences. -
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Gemma 2
Google
A family of state-of-the-art, light-open models created from the same research and technology that were used to create Gemini models. These models incorporate comprehensive security measures and help ensure responsible and reliable AI solutions through selected data sets and rigorous adjustments. Gemma models achieve exceptional comparative results in their 2B, 7B, 9B, and 27B sizes, even outperforming some larger open models. With Keras 3.0, enjoy seamless compatibility with JAX, TensorFlow, and PyTorch, allowing you to effortlessly choose and change frameworks based on task. Redesigned to deliver outstanding performance and unmatched efficiency, Gemma 2 is optimized for incredibly fast inference on various hardware. The Gemma family of models offers different models that are optimized for specific use cases and adapt to your needs. Gemma models are large text-to-text lightweight language models with a decoder, trained in a huge set of text data, code, and mathematical content. -
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ModelOp
ModelOp
ModelOp is the leading AI governance software that helps enterprises safeguard all AI initiatives, including generative AI, Large Language Models (LLMs), in-house, third-party vendors, embedded systems, etc., without stifling innovation. Corporate boards and C‑suites are demanding the rapid adoption of generative AI but face financial, regulatory, security, privacy, ethical, and brand risks. Global, federal, state, and local-level governments are moving quickly to implement AI regulations and oversight, forcing enterprises to urgently prepare for and comply with rules designed to prevent AI from going wrong. Connect with AI Governance experts to stay informed about market trends, regulations, news, research, opinions, and insights to help you balance the risks and rewards of enterprise AI. ModelOp Center keeps organizations safe and gives peace of mind to all stakeholders. Streamline reporting, monitoring, and compliance adherence across the enterprise. -
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Decentriq
Decentriq
Privacy-minded organizations work with Decentriq. With the latest advancements in encryption and privacy-enhancing technologies such as synthetic data, differential privacy, and confidential computing, your data stays under your control at all times. End-to-end encryption keeps your data private to all other parties. Decentriq cannot see or access your data. Remote attestation gives you verification that your data is encrypted and only approved analyses are running. Built-in partnership with market-leading hardware and infrastructure providers. Designed to handle even advanced AI and machine learning models, the platform keeps your data inaccessible no matter the challenge. With processing speeds approaching typical cloud levels, you don’t have to sacrifice scalability for excellent data protection. Our growing network of data connectors supports more streamlined workflows across leading data platforms. -
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Algoreus
Turium AI
All your data needs are delivered in one powerful platform. From data ingestion/integration, transformation, and storage to knowledge catalog, graph networks, data analytics, governance, monitoring, and, sharing. An AI/ML platform that lets enterprises, train, test, troubleshoot, deploy, and govern models at scale to boost productivity while maintaining model performance in production with confidence. A dedicated solution for training models with minimal effort through AutoML or training your case-specific models from scratch with CustomML. Giving you the power to connect essential logic from ML with data. An integrated exploration of possible actions. Integration with your protocols and authorization models. Propagation by default; extreme configurability at your service. Leverage internal lineage system, for alerting and impact analysis. Interwoven with the security paradigm; provides immutable tracking. -
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Gemini 2.0 Flash-Lite
Google
Gemini 2.0 Flash-Lite is Google DeepMind's lighter AI model, designed to offer a cost-effective solution without compromising performance. As the most economical model in the Gemini 2.0 lineup, Flash-Lite is tailored for developers and businesses seeking efficient AI capabilities at a lower cost. It supports multimodal inputs and features a context window of one million tokens, making it suitable for a variety of applications. Flash-Lite is currently available in public preview, allowing users to explore its potential in enhancing their AI-driven projects. -
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Gemini 2.0 Pro
Google
Gemini 2.0 Pro is Google DeepMind's most advanced AI model, designed to excel in complex tasks such as coding and intricate problem-solving. Currently in its experimental phase, it features an extensive context window of two million tokens, enabling it to process and analyze vast amounts of information efficiently. A standout feature of Gemini 2.0 Pro is its seamless integration with external tools like Google Search and code execution environments, enhancing its ability to provide accurate and comprehensive responses. This model represents a significant advancement in AI capabilities, offering developers and users a powerful resource for tackling sophisticated challenges. -
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Artelys Knitro
Artelys
Artelys Knitro is a leading solver for large-scale nonlinear optimization problems, offering a suite of advanced algorithms and features to address complex challenges across various industries. It provides four state-of-the-art algorithms: two interior-point/barrier methods and two active-set/sequential quadratic programming methods, enabling efficient and robust solutions for a wide range of optimization problems. Additionally, Knitro includes three algorithms specifically designed for mixed-integer nonlinear programming, incorporating heuristics, cutting planes, and branching rules to effectively handle discrete variables. Key features of Knitro encompass parallel multi-start capabilities for global optimization, automatic and parallel tuning of option settings, and smart initialization strategies for rapid infeasibility detection. The solver supports various interfaces, including object-oriented APIs for C++, C#, Java, and Python. -
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Cytel
Cytel
Cytel is a leading global provider of clinical trial design software, biometric services, and advanced analytics, specializing in optimizing clinical trials and assisting pharmaceutical companies in unlocking the full potential of their clinical and real-world data. Founded in 1987 by distinguished statisticians Cyrus Mehta and Nitin Patel, Cytel has been at the forefront of adaptive clinical trial technology and biostatistical science. Our software solutions, including the East Horizon platform, empower precise trial design and simulation, utilizing adaptive and Bayesian tools to optimize protocols and accelerate drug development. The East Horizon platform integrates key components of Cytel's trusted software portfolio into a unified solution with R integration, enhancing trial design capabilities. Additionally, Cytel offers the Xact software suite, a comprehensive toolkit for statistical analyses of small datasets, and sparse, and missing data. -
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ERNIE X1
Baidu
ERNIE X1 is an advanced conversational AI model developed by Baidu as part of their ERNIE (Enhanced Representation through Knowledge Integration) series. Unlike previous versions, ERNIE X1 is designed to be more efficient in understanding and generating human-like responses. It incorporates cutting-edge machine learning techniques to handle complex queries, making it capable of not only processing text but also generating images and engaging in multimodal communication. ERNIE X1 is often used in natural language processing applications such as chatbots, virtual assistants, and enterprise automation, offering significant improvements in accuracy, contextual understanding, and response quality.Starting Price: $0.28 per 1M tokens -
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MLlib
Apache Software Foundation
Apache Spark's MLlib is a scalable machine learning library that integrates seamlessly with Spark's APIs, supporting Java, Scala, Python, and R. It offers a comprehensive suite of algorithms and utilities, including classification, regression, clustering, collaborative filtering, and tools for constructing machine learning pipelines. MLlib's high-quality algorithms leverage Spark's iterative computation capabilities, delivering performance up to 100 times faster than traditional MapReduce implementations. It is designed to operate across diverse environments, running on Hadoop, Apache Mesos, Kubernetes, standalone clusters, or in the cloud, and accessing various data sources such as HDFS, HBase, and local files. This flexibility makes MLlib a robust solution for scalable and efficient machine learning tasks within the Apache Spark ecosystem. -
21
Gemini 2.5 Flash
Google
Gemini 2.5 Flash is a powerful, low-latency AI model introduced by Google, designed for high-volume applications where speed and cost-efficiency are key. It delivers optimized performance for use cases like customer service, virtual assistants, and real-time data processing. With its dynamic reasoning capabilities, Gemini 2.5 Flash automatically adjusts processing time based on query complexity, offering granular control over the balance between speed, accuracy, and cost. It is ideal for businesses needing scalable AI solutions that maintain quality and efficiency. -
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DeepSeek-Coder-V2
DeepSeek
DeepSeek-Coder-V2 is an open source code language model designed to excel in programming and mathematical reasoning tasks. It features a Mixture-of-Experts (MoE) architecture with 236 billion total parameters and 21 billion activated parameters per token, enabling efficient processing and high performance. The model was trained on an extensive dataset of 6 trillion tokens, enhancing its capabilities in code generation and mathematical problem-solving. DeepSeek-Coder-V2 supports over 300 programming languages and has demonstrated superior performance on benchmarks such surpassing other models. It is available in multiple variants, including DeepSeek-Coder-V2-Instruct, optimized for instruction-based tasks; DeepSeek-Coder-V2-Base, suitable for general text generation; and lightweight versions like DeepSeek-Coder-V2-Lite-Base and DeepSeek-Coder-V2-Lite-Instruct, designed for environments with limited computational resources. -
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The Rapid Analytics Platform is ICE Mortgage Technology’s cloud-based solution designed to streamline the analysis of large datasets and the creation of analytic models. It offers a turnkey environment where users can access diverse data assets and perform advanced analytics with real-time, high-speed processing capabilities, delivering exceptionally fast results even in complex scenarios. RAP supports multiple programming languages, including SQL, Python, R, and Scala, and features a familiar integrated development environment for writing and organizing code, running queries, and building advanced analytics. It provides daily refreshed data managed in the cloud, ensuring easy access to the most current information. Users can share analytics and code snippets across their enterprise and integrate data and analytics with business-intelligence tools like Tableau and Power BI, with multiple pre-built dashboards available.
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AuroraPrime
AlphaLife Sciences
AuroraPrime is a generative AI-powered platform designed specifically for content authoring and documentation in the life sciences. It automates the end-to-end creation of complex documents such as Clinical Study Reports (CSRs), protocols, and safety narratives. Built on a modular AI and LLM framework, the AuroraPrime platform integrates flexibly with existing enterprise systems to streamline the product development lifecycle. Key features include AI automation that speeds up writing by generating accurate medical documents quickly with minimal manual effort, compliance assurance through automatic checks against standards to ensure accuracy and regulatory compliance, and content management that keeps all knowledge, templates, and documents organized for easy access and reuse. -
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Mistral Code
Mistral AI
Mistral Code is an AI-powered coding assistant designed to enhance software engineering productivity in enterprise environments by integrating powerful coding models, in-IDE assistance, local deployment options, and comprehensive enterprise tooling. Built on the open-source Continue project, Mistral Code offers secure, customizable AI coding capabilities while maintaining full control and visibility inside the customer’s IT environment. It supports over 80 programming languages and advanced functionalities such as multi-step refactoring, code search, and chat assistance, enabling developers to complete entire tickets, not just code completions. The platform addresses common enterprise challenges like proprietary repo connectivity, model customization, broad task coverage, and unified service-level agreements (SLAs). Major enterprises such as Abanca, SNCF, and Capgemini have adopted Mistral Code, using hybrid cloud and on-premises deployments. -
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Gemini 2.5 Flash-Lite
Google
Gemini 2.5 is Google DeepMind’s latest generation AI model family, designed to deliver advanced reasoning and native multimodality with a long context window. It improves performance and accuracy by reasoning through its thoughts before responding. The model offers different versions tailored for complex coding tasks, fast everyday performance, and cost-efficient high-volume workloads. Gemini 2.5 supports multiple data types including text, images, video, audio, and PDFs, enabling versatile AI applications. It features adaptive thinking budgets and fine-grained control for developers to balance cost and output quality. Available via Google AI Studio and Gemini API, Gemini 2.5 powers next-generation AI experiences. -
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Grok 4 Heavy
xAI
Grok 4 Heavy is the most powerful AI model offered by xAI, designed as a multi-agent system to deliver cutting-edge reasoning and intelligence. Built on the Colossus supercomputer, it achieves a 50% score on the challenging HLE benchmark, outperforming many competitors. This advanced model supports multimodal inputs including text and images, with plans to add video capabilities. Grok 4 Heavy targets power users such as developers, researchers, and technical enthusiasts who require top-tier AI performance. Access is provided through the premium “SuperGrok Heavy” subscription priced at $300 per month. xAI has enhanced moderation and removed problematic system prompts to ensure responsible and ethical AI use. -
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Macrobond
Macrobond
From the first question to the final chart, Macrobond powers the entire research process by centralizing data management, advanced analysis, visualization, and reporting in a seamless workflow. Users consolidate their work by tapping into a clean, searchable library of over 2,400 global financial and economic sources; analyze in‑platform using built‑in calculation and comparison functions without exporting data; visualize results instantly with customizable charting tools that communicate insights clearly; and publish polished, up‑to‑date reports ready for presentation. Macrobond’s end‑to‑end platform streamlines research steps, accelerates time to insight, and ensures consistency and accuracy across projects, so teams can think fast and make faster, data‑driven decisions. -
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Claude Opus 4.1
Anthropic
Claude Opus 4.1 is an incremental upgrade to Claude Opus 4 that boosts coding, agentic reasoning, and data-analysis performance without changing deployment complexity. It raises coding accuracy to 74.5 percent on SWE-bench Verified and sharpens in-depth research and detailed tracking for agentic search tasks. GitHub reports notable gains in multi-file code refactoring, while Rakuten Group highlights its precision in pinpointing exact corrections within large codebases without introducing bugs. Independent benchmarks show about a one-standard-deviation improvement on junior developer tests compared to Opus 4, mirroring major leaps seen in prior Claude releases. -
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Claude Sonnet 4.5
Anthropic
Claude Sonnet 4.5 is Anthropic’s latest frontier model, designed to excel in long-horizon coding, agentic workflows, and intensive computer use while maintaining safety and alignment. It achieves state-of-the-art performance on the SWE-bench Verified benchmark (for software engineering) and leads on OSWorld (a computer use benchmark), with the ability to sustain focus over 30 hours on complex, multi-step tasks. The model introduces improvements in tool handling, memory management, and context processing, enabling more sophisticated reasoning, better domain understanding (from finance and law to STEM), and deeper code comprehension. It supports context editing and memory tools to sustain long conversations or multi-agent tasks, and allows code execution and file creation within Claude apps. Sonnet 4.5 is deployed at AI Safety Level 3 (ASL-3), with classifiers protecting against inputs or outputs tied to risky domains, and includes mitigations against prompt injection. -
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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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Claude Opus 4.5
Anthropic
Claude Opus 4.5 is Anthropic’s newest flagship model, delivering major improvements in reasoning, coding, agentic workflows, and real-world problem solving. It outperforms previous models and leading competitors on benchmarks such as SWE-bench, multilingual coding tests, and advanced agent evaluations. Opus 4.5 also introduces stronger safety features, including significantly higher resistance to prompt injection and improved alignment across sensitive tasks. Developers gain new controls through the Claude API—like effort parameters, context compaction, and advanced tool use—allowing for more efficient, longer-running agentic workflows. Product updates across Claude, Claude Code, the Chrome extension, and Excel integrations expand how users interact with the model for software engineering, research, and everyday productivity. Overall, Claude Opus 4.5 marks a substantial step forward in capability, reliability, and usability for developers, enterprises, and end users. -
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Grok 4.1 Thinking is xAI’s advanced reasoning-focused AI model designed for deeper analysis, reflection, and structured problem-solving. It uses explicit thinking tokens to reason through complex prompts before delivering a response, resulting in more accurate and context-aware outputs. The model excels in tasks that require multi-step logic, nuanced understanding, and thoughtful explanations. Grok 4.1 Thinking demonstrates a strong, coherent personality while maintaining analytical rigor and reliability. It has achieved the top overall ranking on the LMArena Text Leaderboard, reflecting strong human preference in blind evaluations. The model also shows leading performance in emotional intelligence and creative reasoning benchmarks. Grok 4.1 Thinking is built for users who value clarity, depth, and defensible reasoning in AI interactions.
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GPT-5.2-Codex
OpenAI
GPT-5.2-Codex is OpenAI’s most advanced agentic coding model, built for complex, real-world software engineering and defensive cybersecurity work. It is a specialized version of GPT-5.2 optimized for long-horizon coding tasks such as large refactors, migrations, and feature development. The model maintains full context over extended sessions through native context compaction. GPT-5.2-Codex delivers state-of-the-art performance on benchmarks like SWE-Bench Pro and Terminal-Bench 2.0. It operates reliably across large repositories and native Windows environments. Stronger vision capabilities allow it to interpret screenshots, diagrams, and UI designs during development. GPT-5.2-Codex is designed to be a dependable partner for professional engineering workflows. -
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GPT-5.3-Codex
OpenAI
GPT-5.3-Codex is OpenAI’s most advanced agentic coding model, designed to handle complex professional work on a computer. It combines frontier-level coding performance with advanced reasoning and real-world task execution. The model is faster than previous Codex versions and can manage long-running tasks involving research, tools, and deployment. GPT-5.3-Codex supports real-time interaction, allowing users to steer progress without losing context. It excels at software engineering, web development, and terminal-based workflows. Beyond code generation, it assists with debugging, documentation, testing, and analysis. GPT-5.3-Codex acts as an interactive collaborator rather than a single-turn coding tool. -
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Gemini 3.1 Pro
Google
Gemini 3.1 Pro is Google’s upgraded core intelligence model designed for complex tasks that require advanced reasoning. Building on the Gemini 3 series, it delivers significant improvements in problem-solving performance and logical pattern recognition. On the ARC-AGI-2 benchmark, Gemini 3.1 Pro achieved a verified score of 77.1%, more than doubling the reasoning performance of Gemini 3 Pro. The model is engineered for challenges where simple answers are insufficient, enabling deeper analysis, synthesis, and creative output. It can generate practical outputs such as animated, website-ready SVGs directly from text prompts, combining intelligence with real-world usability. Gemini 3.1 Pro is rolling out in preview across consumer, developer, and enterprise platforms including the Gemini app, NotebookLM, Gemini API, Gemini Enterprise Agent Platform, and Android Studio. With expanded access for Google AI Pro and Ultra users, 3.1 Pro sets a stronger baseline for agentic workflows. -
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Gemini 3.1 Flash-Lite
Google
Gemini 3.1 Flash-Lite is Google’s fastest and most cost-efficient model in the Gemini 3 series, designed for high-volume developer workloads. It delivers strong performance at scale while maintaining affordability, with pricing set at $0.25 per million input tokens and $1.50 per million output tokens. The model significantly improves speed, offering a 2.5x faster time to first answer token and a 45% increase in output speed compared to Gemini 2.5 Flash. Despite its lower cost tier, it achieves high benchmark results, including an Elo score of 1432 and strong performance across reasoning and multimodal evaluations. Gemini 3.1 Flash-Lite supports adaptive “thinking levels,” allowing developers to control how much reasoning power is used for different tasks. It is suitable for large-scale applications such as translation, content moderation, user interface generation, and simulation building. -
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Raven
Raven
Raven is a runtime application security platform designed to protect cloud-native applications by operating directly inside the application during execution, rather than relying on external defenses. It provides real-time visibility into how code actually runs, allowing it to understand execution flows, libraries, and function-level behavior in order to detect and stop malicious activity before it occurs. Unlike traditional tools such as WAF or EDR that monitor from the outside, Raven embeds itself within the application, enabling it to prevent exploits, supply chain attacks, and zero-day threats even when no known vulnerability or CVE exists. It continuously monitors runtime behavior, identifies abnormal patterns or misuse of legitimate logic, and responds immediately to block harmful execution. It also helps teams prioritize security efforts by filtering out the majority of irrelevant vulnerabilities and focusing only on those that are truly exploitable. -
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ERNIE 5.1
Baidu
ERNIE 5.1 is Baidu’s latest large language model designed to deliver advanced reasoning, agentic AI capabilities, creative writing, and world knowledge performance while operating with significantly improved efficiency. The model builds on the foundation of ERNIE 5.0 while reducing total parameters and training costs, allowing it to achieve flagship-level intelligence at a fraction of the computational expense of comparable models. ERNIE 5.1 performs strongly across international benchmarks for reasoning, search, knowledge, and agentic tasks, ranking among the top global AI models and leading among Chinese-developed models on multiple leaderboards. The platform introduces a new fully asynchronous reinforcement learning infrastructure that improves training efficiency, scalability, and stability for complex long-horizon AI tasks. ERNIE 5.1 also features advanced creative writing capabilities. -
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Gemini 3.5 Pro
Google
Gemini 3.5 Pro is Google’s anticipated next-generation Pro model in the Gemini 3.5 series, designed for advanced reasoning, coding, multimodal understanding, and agentic workflows. It is expected to build on Google’s Gemini 3 family with stronger performance for complex tasks that require planning, context handling, tool use, and deep problem solving. The model is aimed at users who need more power than faster Flash models for demanding development, research, automation, and enterprise AI use cases. Gemini 3.5 Pro is expected to support sophisticated workflows across text, code, files, multimodal inputs, and connected tools. Developers and organizations will likely use it through Google’s AI platforms for building assistants, agents, coding tools, analysis systems, and productivity applications. As an upcoming Pro-tier model, Gemini 3.5 Pro is positioned for high-value workloads where accuracy, reasoning quality, and advanced task execution matter more than maximum speed. -
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Diom
Svix
Diom is a backend components platform for building robust services, offering a set of well-integrated infrastructure primitives for backend and data engineers, including caching, key-value storage, rate-limiting, idempotency, queues, and streams. It is designed so engineers no longer need to build fragile, slow, and hard-to-maintain solutions on top of Redis, Postgres, or other data stores, and can instead rely on powerful, performant, well-tested components built for common backend patterns. Diom can replace multiple services such as Redis, RabbitMQ, and Kafka for many use cases, reducing service dependencies, operational complexity, monitoring overhead, backups, configuration work, and deployment costs. Its components support low-latency operations, minimal round-trip, HTTP-based APIs, SDKs for popular languages, and deployment in common backend environments. -
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Rapidminer AI Studio
Siemens
RapidMiner AI Studio is a dedicated environment for rapidly developing and prototyping AI solutions, helping teams unify the complete data science lifecycle from data exploration and machine learning to model operations and visualization. It allows data scientists and engineers to build, train, and test AI models locally, giving organizations full control and flexibility for initial exploration and development. It connects directly to enterprise data sources, including files, databases, data lakes, cloud data platforms, warehouses, SQL databases, and Internet of Things data streams, helping teams unify data, prevent errors, and power accurate, explainable AI. RapidMiner AI Studio supports both domain experts and technical teams: users without coding experience can quickly build effective machine learning models with an intuitive drag-and-drop canvas, while data scientists can create complex models in a fully integrated notebook environment using Python and R. -
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Visplore
Visplore GmbH
Visplore is a visual analytics software solution for rapid industrial troubleshooting and root-cause analysis. When KPIs and simple trends are not enough and action is time-critical, it complements dashboards with guided forensic “why” analyses that deliver insights for problem-solving and process optimization. It works across the entire IT/OT landscape, from process and asset data to quality and material data, and is easy to use for all engineers. - Guided, transparent root-cause analysis with intuitive visuals — no black boxes, no complex modeling - Works with your data, where it lives - Seamless IT/OT connectivity - From troubleshooting to standardized best practice - Proven templates, excellent expert support, and workflows that scale into automated monitoring and reporting. Compared to other data analysis tools such as Seeq and TrendMiner, Visplore is built for everyday engineering use, making industrial data analysis accessible, repeatable, and ready for action. -
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Bayesforge
Quantum Programming Studio
Bayesforge™ is a Linux machine image that curates the very best open source software for the data scientist who needs advanced analytical tools, as well as for quantum computing and computational mathematics practitioners who seek to work with one of the major QC frameworks. The image combines common machine learning frameworks, such as PyTorch and TensorFlow, with open source software from D-Wave, Rigetti as well as the IBM Quantum Experience and Google's new quantum computing language Cirq, as well as other advanced QC frameworks. For instance our quantum fog modeling framework, and our quantum compiler Qubiter which can cross-compile to all major architectures. All software is made accessible through the Jupyter WebUI which, due to its modular architecture, allows the user to code in Python, R, and Octave. -
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Betteromics
Betteromics
Betteromics is deployed as a Private SaaS in your VPC so you can draw connections on all your data. Reproducibly validate your structured and unstructured data using configurable rules. Trace and audit your data from input to analysis with complete data provenance. Use natural language processing and large language models to abstract data elements from clinical records for QC, labeling, and analysis. Quickly develop and tune models specific to your task/data: detect anomalies, make predictions, understand your data, and optimize your processes. Enhance and complement your analysis and machine learning with integration-ready public datasets. Clinical-grade security including full encryption, data traceability, and role-based access controls. -
47
Unremot
Unremot
Unremot is a go-to place for anyone aspiring to build an AI product - with 120+ pre-built APIs, you can build and launch AI products 2X faster, at 1/3rd cost. Even, some of the most complicated AI product APIs take less than a few minutes to deploy and launch, with minimal code or even no-code. Choose an AI API that you want to integrate to your product from 120+ APIs we have on Unremot. Provide your API private key to authenticate Unremot to access the API. Use unremot unique URL to connect the product API - the whole process takes only minutes, instead of days and weeks. -
48
IBM SPSS Modeler
IBM
IBM SPSS Modeler is a leading visual data science and machine learning (ML) solution designed to help enterprises accelerate time to value by speeding up operational tasks for data scientists. Organizations worldwide use it for data preparation and discovery, predictive analytics, model management and deployment, and ML to monetize data assets. IBM SPSS Modeler automatically transforms data into the best format for the most accurate predictive modeling. It now only takes a few clicks for you to analyze data, identify fixes, screen out fields and derive new attributes. Leverage IBM SPSS Modeler’s powerful graphics engine to bring your insights to life. The smart chart recommender finds the perfect chart for your data from among dozens of options, so you can share your insights quickly and easily using compelling visualizations. -
49
CodeGemma
Google
CodeGemma is a collection of powerful, lightweight models that can perform a variety of coding tasks like fill-in-the-middle code completion, code generation, natural language understanding, mathematical reasoning, and instruction following. CodeGemma has 3 model variants, a 7B pre-trained variant that specializes in code completion and generation from code prefixes and/or suffixes, a 7B instruction-tuned variant for natural language-to-code chat and instruction following; and a state-of-the-art 2B pre-trained variant that provides up to 2x faster code completion. Complete lines, and functions, and even generate entire blocks of code, whether you're working locally or using Google Cloud resources. Trained on 500 billion tokens of primarily English language data from web documents, mathematics, and code, CodeGemma models generate code that's not only more syntactically correct but also semantically meaningful, reducing errors and debugging time. -
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CZ CELLxGENE Discover
CZ CELLxGENE
Select two custom cell groups based on metadata to find their top differentially expressed genes. Leverage millions of cells from the integrated CZ CELLxGENE corpus for powerful analysis. Execute interactive analyses on a dataset to explore how patterns of gene expression are determined by spatial, environmental, and genetic factors using an interactive speed no-code UI. Understand published datasets or use them as a launchpad to identify new cell sub-types and states. Census provides access to any custom slice of standardized cell data available on CZ CELLxGENE Discover in R and Python. Explore an interactive encyclopedia of 700+ cell types that provides detailed definitions, marker genes, lineage, and relevant datasets in one place. Browse and download hundreds of standardized data collections and 1,000+ datasets characterizing the functionality of healthy mouse and human tissues.
