Best Artificial Intelligence Software for Java - Page 7

Compare the Top Artificial Intelligence Software that integrates with Java as of July 2025 - Page 7

This a list of Artificial Intelligence software that integrates with Java. Use the filters on the left to add additional filters for products that have integrations with Java. View the products that work with Java in the table below.

  • 1
    SourceAI

    SourceAI

    SourceAI

    Open to all (even for non-developers), straightforward and simple to use, clear and intuitive interface. Save time in development, generate your code in one click and use your time more efficiently. Powered by GPT-3 and Codex, the most advanced AI technology, and next-generation development. Sometimes SourceAI will have trouble understanding what you want, so you'll have to explain it in more detail. At SourceAI, we are a close-knit team of empathetic and optimistic developers who care deeply about accelerating human progress by making programming accessible to all. Our mission is to give everyone the opportunity to create valuable customized software. We build a self-contained system that can create software at the level of the world's most skilled engineers. We have developed a stand-alone system based on the GPT-3 language model. SourceAI is a tool that can generate code for you in any language from a plain text description.
  • 2
    Granica

    Granica

    Granica

    The Granica AI efficiency platform reduces the cost to store and access data while preserving its privacy to unlock it for training. Granica is developer-first, petabyte-scale, and AWS/GCP-native. Granica makes AI pipelines more efficient, privacy-preserving, and more performant. Efficiency is a new layer in the AI stack. Byte-granular data reduction uses novel compression algorithms, cutting costs to store and transfer objects in Amazon S3 and Google Cloud Storage by up to 80% and API costs by up to 90%. Estimate in 30 mins in your cloud environment, on a read-only sample of your S3/GCS data. No need for budget allocation or total cost of ownership analysis. Granica deploys into your environment and VPC, respecting all of your security policies. Granica supports a wide range of data types for AI/ML/analytics, with lossy and fully lossless compression variants. Detect and protect sensitive data even before it is persisted into your cloud object store.
  • 3
    Editor.do

    Editor.do

    Editor.do

    Editor.do is an all-in-one online IDE and hosting platform that allows you to create, code, host and deploy stunning & fast static websites in seconds. You can easily deploy your site files or a zip containing all your project files to our NVMe SSD storage servers, ensuring the fastest possible loading speed for your site. Our IDE supports over 150 programming languages with real-time code rendering and a panel of shortcuts and tools to search, replace, cut, select, and quickly manipulate your code. Editor.do offers over 1000 free and open-source templates covering a wide range of categories and libraries that can be imported directly from GitHub. Plus, ChatGPT is integrated and is always close at hand to help you correct, complete, or improve your code or text. Editor.do is an ideal platform for developers and designers of all skill levels who want to create stunning, fast, and secure websites in a fraction of the time.
    Starting Price: $3 per month
  • 4
    StableCode

    StableCode

    Stability AI

    StableCode offers a unique way for developers to become more efficient by using three different models to help in their coding. The base model was first trained on a diverse set of programming languages from the stack-dataset (v1.2) from BigCode and then trained further with popular languages like Python, Go, Java, Javascript, C, markdown and C++. In total, we trained our models on 560B tokens of code on our HPC cluster. After the base model had been established, the instruction model was then tuned for specific use cases to help solve complex programming tasks. ~120,000 code instruction/response pairs in Alpaca format were trained on the base model to achieve this result. StableCode is the ideal building block for those wanting to learn more about coding, and the long-context window model is the perfect assistant to ensure single and multiple-line autocomplete suggestions are available for the user. This model is built to handle a lot more code at once.
  • 5
    ExoCoding

    ExoCoding

    ExoCoding

    ExoCoding is a code generation online platform that empowers software developers to build better software faster. It uses model-based AI-powered assistants to generate boilerplate code and streamline repetitive tasks. Developers can create apps containing modules with Database Management, Logic Building, and Interface Design. There are also more features like sharing prototypes, task planning, and a marketplace with pre-built templates that enhance the developer’s experience. After generating code (backend and frontend), everything is business as usual with the same IDE and other dev tools, but with much work already accomplished.
  • 6
    Cosine Genie
    Whether it’s high-level or nuanced, Cosine can understand and provide superhuman level answers. We're not just an LLM wrapper – we combine multiple heuristics including static analysis, semantic search and others. Simply ask Cosine how to add a new feature or modify existing code and we’ll generate a step by step guide. Cosine indexes and understands your codebase on multiple levels. From a graph relationship between files and functions to a deep semantic understanding of the code, Cosine can answer any question you have about your codebase. Genie is the best AI software engineer in the world by far - achieving a 30% eval score on the industry standard benchmark SWE-Bench. Genie is able to solve bugs, build features, refactor code, and everything in between either fully autonomously or paired with the user, like working with a colleague, not just a copilot.
  • 7
    Selenic

    Selenic

    Parasoft

    Selenium tests are often unstable and difficult to maintain. Parasoft Selenic fixes common Selenium problems within your existing projects with no vendor lock. When your team is using Selenium to develop and test the UI for your software applications, you need confidence that your testing process is identifying real issues, creating meaningful and appropriate tests, and reducing test maintenance. While Selenium offers many benefits, you want to get more out of your UI testing while leveraging your current practice. Find the real UI issues and get quick feedback on test execution so you can deliver better software faster with Parasoft Selenic. Improve your existing library of Selenium web UI tests, or quickly create new ones, with a flexible Selenium companion that integrates seamlessly with your environment. Parasoft Selenic fixes common Selenium problems with AI-powered self-healing to minimize runtime failures, test impact analysis to dramatically reduce test execution time, etc.
  • 8
    Code to Flowchart

    Code to Flowchart

    Code to Flowchart

    Turn code into interactive flowcharts with AI, and simplify complex logic instantly.
    Starting Price: Free
  • 9
    Gemma

    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.
  • 10
    Gemma 2

    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.
  • 11
    ModelOp

    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.
  • 12
    KaneAI

    KaneAI

    LambdaTest

    Advanced AI-powered platform built on modern Large Language Models (LLMs). A unique approach to create, debug, and evolve end to end tests using natural language. Test generation & evolution effortlessly using natural language inputs, simplifying the testing process with intelligent automation. Intelligent test planner automatically generates and automates test steps using high-level objectives. Multi-language code export converts your automated tests in all major languages and frameworks. Convert your actions into natural language instructions to generate bulletproof tests. Express sophisticated conditions and assertions in natural language. As easy as conversing and communicating with your team. Convey the same instructions to KaneAI and watch it automate your tests. Generate your tests with just high-level objectives. Develop tests across your stack on both web and mobile devices for extensive test coverage.
  • 13
    StackGen

    StackGen

    StackGen

    Generate context-aware, secure IaC from application code without code changes. We love infrastructure as code, but that doesn’t mean there isn’t room for improvement. StackGen uses an application’s code to generate consistent, secure, and compliant IaC. Remove bottlenecks, liabilities, and error-prone manual processes between DevOps, developers, and security to get your application to market faster. Allow developers a better, more productive experience without becoming infrastructure experts. Consistency, security, and policy guardrails are incorporated by default when IaC is auto-generated. Context-aware IaC is auto-generated, with no code changes required, supported, and rightsized with least-privileged access controls. No need to rebuild your pipelines. StackGen works alongside your existing workflows to remove silos between teams. Enable developers to auto-generate IaC that complies with your provisioning checklist.
  • 14
    Algoreus

    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​.
  • 15
    Stellar

    Stellar

    Vstellar

    Speed up your testing processes with Stellar’s low-code automation platform. Enhance efficiency, minimize errors, and achieve smarter software testing with effortless solutions for UI, API, mobile, performance, and accessibility testing. Empower your team to test more and stress less with effortless integration and advanced analytics.
  • 16
    Gemini 2.0 Flash-Lite
    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.
  • 17
    Gemini 2.0 Pro
    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.
  • 18
    Artelys Knitro
    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.
  • 19
    Navie AI

    Navie AI

    AppMap

    AppMap Navie is an AI-powered development assistant designed to enhance software development by providing actionable insights and troubleshooting support. It combines static and runtime application analysis to guide developers in understanding and optimizing their codebases more effectively. Navie integrates seamlessly with development environments, offering flexible deployment configurations and support for enterprise-grade security, including options for using GitHub Copilot or custom language models. The platform provides valuable context for AI-driven suggestions, such as HTTP requests, function parameters, and database queries, improving code quality and accelerating problem-solving. Navie is ideal for developers looking to streamline workflows, solve complex coding issues, and enhance overall application performance.
  • 20
    Augoor

    Augoor

    Augoor

    Augoor transforms static code into dynamic knowledge, enabling teams to navigate, document, and optimize complex systems effortlessly. By extracting structures, relationships, and context, Augoor builds a living knowledge graph that accelerates the development lifecycle. Its AI-driven code navigation tool accelerates new developer productivity, integrating them into projects from day one. Augoor reduces maintenance efforts and enhances code integrity by pinpointing problematic code segments, saving costs, and reinforcing your codebase. It automatically generates clear, updated code explanations, preserving knowledge, especially for complex legacy systems. The AI navigation system cuts down time spent searching through code, allowing developers to focus more on coding, speeding up feature development, and fostering innovation in large codebases. Augoor's advanced AI-driven visualizations uncover hidden patterns, map complex dependencies, and reveal critical relationships.
  • 21
    Undrstnd

    Undrstnd

    Undrstnd

    ​Undrstnd Developers empowers developers and businesses to build AI-powered applications with just four lines of code. Experience incredibly fast AI inference times, up to 20 times faster than GPT-4 and other leading models. Our cost-effective AI services are designed to be up to 70 times cheaper than traditional providers like OpenAI. Upload your own datasets and train models in under a minute with our easy-to-use data source feature. Choose from a variety of open source Large Language Models (LLMs) to fit your specific needs, all backed by powerful, flexible APIs. Our platform offers a range of integration options to make it easy for developers to incorporate our AI-powered solutions into their applications, including RESTful APIs and SDKs for popular programming languages like Python, Java, and JavaScript. Whether you're building a web application, a mobile app, or an IoT device, our platform provides the tools and resources you need to integrate our AI-powered solutions seamlessly.
  • 22
    ERNIE X1
    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
  • 23
    MLlib

    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. ​
  • 24
    AlphaCodium
    AlphaCodium is a research-driven AI tool developed by Qodo to enhance coding with iterative, test-driven processes. It helps large language models improve their accuracy by enabling them to engage in logical reasoning, testing, and refining code. AlphaCodium offers an alternative to basic prompt-based approaches by guiding AI through a more structured flow paradigm, which leads to better mastery of complex code problems, particularly those involving edge cases. It improves performance on coding challenges by refining outputs based on specific tests, ensuring more reliable results. AlphaCodium is benchmarked to significantly increase the success rates of LLMs like GPT-4o, OpenAI o1, and Sonnet-3.5. It supports developers by providing advanced solutions for complex coding tasks, allowing for enhanced productivity in software development.
  • 25
    Gemini 2.5 Flash
    Gemini 2.5 Flash is a powerful, low-latency AI model introduced by Google on Vertex AI, 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.
  • 26
    DeepSeek-Coder-V2
    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.
  • 27
    Mistral Code

    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.
  • 28
    Gemini 2.5 Flash-Lite
    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.
  • 29
    String.com

    String.com

    Pipedream

    String is the first text-to-agent platform by Pipedream that lets you prompt, run, edit, and deploy AI agents in seconds, no drag-and-drop canvases, just natural language commands that generate production-ready code. Backed by Pipedream’s five years of experience building thousands of app integrations and Internet-scale agent infrastructure, String connects to over 2,700 APIs and embeds 10,000+ tools with managed authentication, so your agents can solve ten times more use cases than typical no-code builders. The intuitive web interface guides you through creating agents that monitor GitHub issues and automate ticket creation, schedule meetings, analyze data, send Slack messages, post to social media, update databases, and much more, all with full audit trails, customizable queues, and built-in data stores. Real-time dashboards display agent performance, logs, and metrics, while built-in security and privacy controls (SOC 2 Type II, ISO 27001, HIPAA, GDPR) ensure safe operation.
  • 30
    XBOW

    XBOW

    XBOW

    XBOW is an AI-powered offensive security platform that autonomously discovers, verifies, and exploits vulnerabilities in web applications without human intervention. By executing high-level commands against benchmark descriptions and reviewing outputs it solves a wide array of challenges, from CBC padding oracle and IDOR attacks to remote code execution, blind SQL injection, SSTI bypasses, and cryptographic exploits, achieving success rates up to 75 percent on standard web security benchmarks. Given only general instructions, XBOW orchestrates reconnaissance, exploit development, debugging, and server-side analysis, drawing on public exploits and source code to craft custom proofs-of-concept, validate attack vectors, and generate detailed exploit traces with full audit trails. Its ability to adapt to novel and modified benchmarks demonstrates robust scalability and continuous learning, dramatically accelerating penetration-testing workflows.