Best AI Development Platforms with a Free Trial of 2025 - Page 3

Intel® Tiber™ AI Studio serves as an all-encompassing machine learning operating system designed to streamline and unify the development of artificial intelligence. This robust platform accommodates a diverse array of AI workloads and features a hybrid multi-cloud infrastructure that enhances the speed of ML pipeline creation, model training, and deployment processes. By incorporating native Kubernetes orchestration and a meta-scheduler, Tiber™ AI Studio delivers unparalleled flexibility for managing both on-premises and cloud resources. Furthermore, its scalable MLOps framework empowers data scientists to seamlessly experiment, collaborate, and automate their machine learning workflows, all while promoting efficient and cost-effective resource utilization. This innovative approach not only boosts productivity but also fosters a collaborative environment for teams working on AI projects.

The best data will help you achieve peak model performance. Create and manage training data for any visual modality. Debug models, boost performance and make foundation models yours. Expert review, QA, and QC workflows will help you deliver better datasets to your artificial-intelligence teams, improving model performance. Encord's Python SDK allows you to connect your data and models, and create pipelines that automate the training of ML models. Improve model accuracy by identifying biases and errors in your data, labels, and models.

Superpowered AI offers a comprehensive knowledge retrieval system specifically designed for large language model (LLM) applications. By simplifying complex infrastructure into mere API calls, it allows LLMs to access confidential information that was not included in their initial training data, such as internal company files. You can archive previous messages in a Knowledge Base, making it possible to extract the most pertinent ones whenever a user initiates a new message. This approach helps minimize inaccuracies by incorporating relevant factual data directly into prompts and guiding the LLM to rely solely on the information provided. Employing a retrieval solution like Superpowered AI empowers you to gather the appropriate data and seamlessly integrate it into your LLM interactions, significantly enhancing the relevance of responses given to users. You can effortlessly build a knowledge base from local files, folders, or URLs, enabling queries through a REST API with less than ten lines of code. With its cutting-edge multi-stage knowledge retrieval pipeline, Superpowered AI ensures that you receive the most relevant results tailored to your needs. This innovative technology not only streamlines the retrieval process but also improves user satisfaction by delivering accurate and contextually appropriate information.

Developing open source language models demands both time and expertise. Taylor AI enables your engineering team to prioritize delivering genuine business value instead of grappling with intricate libraries and establishing training frameworks. Collaborating with external LLM providers often necessitates the exposure of your organization's confidential information. Many of these providers retain the authority to retrain models using your data, which can pose risks. With Taylor AI, you maintain ownership and full control over your models. Escape the conventional pay-per-token pricing model; with Taylor AI, your payments are solely for training the model itself. This allows you the liberty to deploy and engage with your AI models as frequently as desired. New open source models are released monthly, and Taylor AI ensures you stay updated with the latest offerings, relieving you of the burden. By choosing Taylor AI, you position yourself to remain competitive and train with cutting-edge models. As the owner of your model, you can deploy it according to your specific compliance and security requirements, ensuring your organization’s standards are met. Additionally, this autonomy allows for greater innovation and agility in your projects.

Develop your personalized AI backend in just a few minutes, effortlessly design intricate AI workflows using an intuitive point-and-click interface, and accomplish everything with a single API call. This streamlined process allows you to focus on creativity while minimizing technical barriers.

Parea is a prompt engineering platform designed to allow users to experiment with various prompt iterations, assess and contrast these prompts through multiple testing scenarios, and streamline the optimization process with a single click, in addition to offering sharing capabilities and more. Enhance your AI development process by leveraging key functionalities that enable you to discover and pinpoint the most effective prompts for your specific production needs. The platform facilitates side-by-side comparisons of prompts across different test cases, complete with evaluations, and allows for CSV imports of test cases, along with the creation of custom evaluation metrics. By automating the optimization of prompts and templates, Parea improves the outcomes of large language models, while also providing users the ability to view and manage all prompt versions, including the creation of OpenAI functions. Gain programmatic access to your prompts, which includes comprehensive observability and analytics features, helping you determine the costs, latency, and overall effectiveness of each prompt. Embark on the journey to refine your prompt engineering workflow with Parea today, as it empowers developers to significantly enhance the performance of their LLM applications through thorough testing and effective version control, ultimately fostering innovation in AI solutions.

Clevis provides users with the ability to design AI-driven applications without any coding knowledge required. By utilizing a variety of ready-made processing modules, individuals can easily build, launch, and promote applications that include functionalities such as generating text, creating images, and scraping web data. Discover how to develop an application that produces recipes tailored to specific dietary needs, or one that generates character bios and illustrations using merely a name and a year of birth. You can create your app by integrating various features like text and image generation alongside API requests for a seamless experience. To get started quickly, you can utilize one of our pre-designed app templates. Share a publicly accessible link to allow anyone to use your app with ease. Clevis is equipped with an extensive range of tools that make constructing your AI application straightforward. Moreover, you have the option to monetize your app through a usage-based pricing model, ensuring you can generate revenue from your creations. Launching your app is as simple as making an HTTP request with your own API key, paving the way for a smooth user experience. This platform opens up endless possibilities for innovators looking to leverage AI technology in their projects.

Braintrust serves as a robust platform tailored for the development of AI products within enterprises. By streamlining evaluations, providing a prompt playground, and managing data effectively, we eliminate the challenges and monotony associated with integrating AI into business operations. Users can compare various prompts, benchmarks, and the corresponding input/output pairs across different runs. You have the option to experiment in a transient manner or transform your initial draft into a comprehensive experiment for analysis across extensive datasets. Incorporate Braintrust into your continuous integration processes to monitor advancements on your primary branch and automatically juxtapose new experiments with existing live versions prior to deployment. Effortlessly gather rated examples from both staging and production environments, assess them, and integrate these insights into curated “golden” datasets. These datasets are stored in your cloud infrastructure and come with built-in version control, allowing for seamless evolution without jeopardizing the integrity of evaluations that rely on them, ensuring a smooth and efficient workflow as your AI capabilities expand. With Braintrust, businesses can confidently navigate the complexities of AI integration while fostering innovation and reliability.

By combining the advantages of a notebook with the functionality of an IDE, experts are empowered to analyze data while simultaneously developing reliable code, all supported by a fully automated cloud infrastructure. Zerve revolutionizes the data science development environment, providing teams focused on data science and machine learning with a cohesive platform to explore, collaborate, construct, and deploy their AI projects like never before. This innovative tool ensures true language interoperability, allowing users to seamlessly integrate Python, R, SQL, or Markdown within the same workspace, facilitating the connection of various code blocks. Zerve eliminates the frustrations of lengthy code execution or cumbersome containers by enabling unlimited parallel processing throughout the entire development process. Furthermore, artifacts generated during analysis are automatically serialized, versioned, stored, and preserved, making it simple to modify any step in the data pipeline without the need to reprocess earlier stages. Users also benefit from precise control over computing resources and additional memory, which is essential for handling intricate data transformations. With Zerve, data science teams can enhance their workflow efficiency and streamline project management significantly.

RagaAI stands out as the premier AI testing platform, empowering businesses to minimize risks associated with artificial intelligence while ensuring that their models are both secure and trustworthy. By effectively lowering AI risk exposure in both cloud and edge environments, companies can also manage MLOps expenses more efficiently through smart recommendations. This innovative foundation model is crafted to transform the landscape of AI testing. Users can quickly pinpoint necessary actions to address any dataset or model challenges. Current AI-testing practices often demand significant time investments and hinder productivity during model development, leaving organizations vulnerable to unexpected risks that can lead to subpar performance after deployment, ultimately wasting valuable resources. To combat this, we have developed a comprehensive, end-to-end AI testing platform designed to significantly enhance the AI development process and avert potential inefficiencies and risks after deployment. With over 300 tests available, our platform ensures that every model, data, and operational issue is addressed, thereby speeding up the AI development cycle through thorough testing. This rigorous approach not only saves time but also maximizes the return on investment for businesses navigating the complex AI landscape.

Enhance the precision of your machine learning models by leveraging publicly accessible datasets. Streamline the process of data discovery and preparation with curated datasets that are not only readily available for machine learning applications but also easily integrable through Azure services. It is essential to consider real-world factors that could influence business performance. By integrating features from these curated datasets into your machine learning models, you can significantly boost the accuracy of your predictions while minimizing the time spent on data preparation. Collaborate and share datasets with an expanding network of data scientists and developers. Utilize Azure Open Datasets alongside Azure’s machine learning and data analytics solutions to generate insights at an unprecedented scale. Most Open Datasets come at no extra cost, allowing you to pay solely for the Azure services utilized, including virtual machine instances, storage, networking, and machine learning resources. This curated open data is designed for seamless access on Azure, empowering users to focus on innovation and analysis. In this way, organizations can unlock new opportunities and drive informed decision-making.

Elevate your distributed applications, enhance your workflows for resilience, and safeguard against software malfunctions and outages with Orkes, the top orchestration solution for developers. Create expansive distributed systems that integrate microservices, serverless solutions, AI models, event-driven frameworks, and more, using any programming language or development framework. Your creativity, your code, your application—crafted, built, and satisfying users at an unprecedented speed. Orkes Conductor provides the quickest route to develop and upgrade all your applications. Visualize your business logic as effortlessly as if sketching on a whiteboard, implement the components using your preferred language and framework, deploy them at scale with minimal setup, and monitor your extensive distributed environment—all while benefiting from robust enterprise-level security and management features that are inherently included. This comprehensive approach ensures that your systems are not only scalable but also resilient to the challenges of modern software development.

Emly Labs, an AI framework, is designed to make AI accessible to users of all technical levels via a user-friendly interface. It offers AI project-management with tools that automate workflows for faster execution. The platform promotes team collaboration, innovation, and data preparation without code. It also integrates external data to create robust AI models. Emly AutoML automates model evaluation and data processing, reducing the need for human input. It prioritizes transparency with AI features that are easily explained and robust auditing to ensure compliance. Data isolation, role-based accessibility, and secure integrations are all security measures. Emly's cost effective infrastructure allows for on-demand resource provisioning, policy management and risk reduction.

The Saagie cloud data factory serves as a comprehensive platform that enables users to develop and oversee their data and AI initiatives within a unified interface, all deployable with just a few clicks. By utilizing the Saagie data factory, you can securely develop use cases and evaluate your AI models. Launch your data and AI projects seamlessly from a single interface while centralizing team efforts to drive swift advancements. Regardless of your experience level, whether embarking on your initial data project or cultivating a data and AI-driven strategy, the Saagie platform is designed to support your journey. Streamline your workflows to enhance productivity and make well-informed decisions by consolidating your work on one platform. Transform raw data into valuable insights through effective orchestration of your data pipelines, ensuring quick access to critical information for better decision-making. Manage and scale your data and AI infrastructure with ease, significantly reducing the time it takes to bring your AI, machine learning, and deep learning models into production. Additionally, the platform fosters collaboration among teams, enabling a more innovative approach to data-driven challenges.

Introducing an advanced enterprise studio designed for AI developers to effectively train, validate, fine-tune, and deploy AI models. The IBM® watsonx.ai™ AI studio is an integral component of the IBM watsonx™ AI and data platform, which unifies innovative generative AI capabilities driven by foundation models alongside traditional machine learning techniques, creating a robust environment that covers the entire AI lifecycle. Users can adjust and direct models using their own enterprise data to fulfill specific requirements, benefiting from intuitive tools designed for constructing and optimizing effective prompts. With watsonx.ai, you can develop AI applications significantly faster and with less data than ever before. Key features of watsonx.ai include: comprehensive AI governance that empowers enterprises to enhance and amplify the use of AI with reliable data across various sectors, and versatile, multi-cloud deployment options that allow seamless integration and execution of AI workloads within your preferred hybrid-cloud architecture. This makes it easier than ever for businesses to harness the full potential of AI technology.

DagsHub serves as a collaborative platform tailored for data scientists and machine learning practitioners to effectively oversee and optimize their projects. By merging code, datasets, experiments, and models within a cohesive workspace, it promotes enhanced project management and teamwork among users. Its standout features comprise dataset oversight, experiment tracking, a model registry, and the lineage of both data and models, all offered through an intuitive user interface. Furthermore, DagsHub allows for smooth integration with widely-used MLOps tools, which enables users to incorporate their established workflows seamlessly. By acting as a centralized repository for all project elements, DagsHub fosters greater transparency, reproducibility, and efficiency throughout the machine learning development lifecycle. This platform is particularly beneficial for AI and ML developers who need to manage and collaborate on various aspects of their projects, including data, models, and experiments, alongside their coding efforts. Notably, DagsHub is specifically designed to handle unstructured data types, such as text, images, audio, medical imaging, and binary files, making it a versatile tool for diverse applications. In summary, DagsHub is an all-encompassing solution that not only simplifies the management of projects but also enhances collaboration among team members working across different domains.

Conducting real-world simulations, assessments, and audits for generative AI agents is crucial for a thorough understanding of their capabilities. Implementing automated testing across intricate scenarios allows for the examination of their functionality, performance, security, and adherence to regulations. When evaluating AI-powered shopping assistants, it is essential to ensure they provide precise product details, personalized suggestions, and effective fraud detection, all while complying with consumer protection regulations. Similarly, validating AI healthcare agents is vital to guarantee that they disseminate medically accurate information, protect patient privacy in accordance with HIPAA and GDPR, and adhere to industry compliance benchmarks for diagnostics and patient interactions. Additionally, it is important that customer service AI agents maintain data integrity, comply with various regulatory frameworks like GDPR and PCI DSS, and offer robust fraud prevention measures while safeguarding sensitive customer information. Running extensive simulations of real-world interactions with the entire suite of agents ensures that they perform effectively under various conditions. Furthermore, testing your AI prior to deployment and continuously monitoring its performance with regular reports will help maintain quality and compliance in the long run. This proactive approach not only enhances trust but also fosters innovation in the use of AI technologies across different sectors.

Kitten Stack serves as a comprehensive platform designed for the creation, enhancement, and deployment of LLM applications, effectively addressing typical infrastructure hurdles by offering powerful tools and managed services that allow developers to swiftly transform their concepts into fully functional AI applications. By integrating managed RAG infrastructure, consolidated model access, and extensive analytics, Kitten Stack simplifies the development process, enabling developers to prioritize delivering outstanding user experiences instead of dealing with backend complications. Key Features: Instant RAG Engine: Quickly and securely link private documents (PDF, DOCX, TXT) and real-time web data in just minutes, while Kitten Stack manages the intricacies of data ingestion, parsing, chunking, embedding, and retrieval. Unified Model Gateway: Gain access to over 100 AI models (including those from OpenAI, Anthropic, Google, and more) through a single, streamlined platform, enhancing versatility and innovation in application development. This unification allows for seamless integration and experimentation with a variety of AI technologies.

Orq.ai stands out as the leading platform tailored for software teams to effectively manage agentic AI systems on a large scale. It allows you to refine prompts, implement various use cases, and track performance meticulously, ensuring no blind spots and eliminating the need for vibe checks. Users can test different prompts and LLM settings prior to launching them into production. Furthermore, it provides the capability to assess agentic AI systems within offline environments. The platform enables the deployment of GenAI features to designated user groups, all while maintaining robust guardrails, prioritizing data privacy, and utilizing advanced RAG pipelines. It also offers the ability to visualize all agent-triggered events, facilitating rapid debugging. Users gain detailed oversight of costs, latency, and overall performance. Additionally, you can connect with your preferred AI models or even integrate your own. Orq.ai accelerates workflow efficiency with readily available components specifically designed for agentic AI systems. It centralizes the management of essential phases in the LLM application lifecycle within a single platform. With options for self-hosted or hybrid deployment, it ensures compliance with SOC 2 and GDPR standards, thereby providing enterprise-level security. This comprehensive approach not only streamlines operations but also empowers teams to innovate and adapt swiftly in a dynamic technological landscape.

Vertesia serves as a comprehensive, low-code platform for generative AI that empowers enterprise teams to swiftly design, implement, and manage GenAI applications and agents on a large scale. Tailored for both business users and IT professionals, it facilitates a seamless development process, enabling a transition from initial prototype to final production without the need for lengthy timelines or cumbersome infrastructure. The platform accommodates a variety of generative AI models from top inference providers, granting users flexibility and reducing the risk of vendor lock-in. Additionally, Vertesia's agentic retrieval-augmented generation (RAG) pipeline boosts the precision and efficiency of generative AI by automating the content preparation process, which encompasses advanced document processing and semantic chunking techniques. With robust enterprise-level security measures, adherence to SOC2 compliance, and compatibility with major cloud services like AWS, GCP, and Azure, Vertesia guarantees safe and scalable deployment solutions. By simplifying the complexities of AI application development, Vertesia significantly accelerates the path to innovation for organizations looking to harness the power of generative AI.

NeuroSplit is an innovative adaptive-inferencing technology that employs a unique method of "slicing" a neural network's connections in real time, resulting in the creation of two synchronized sub-models; one that processes initial layers locally on the user's device and another that offloads the subsequent layers to cloud GPUs. This approach effectively utilizes underused local computing power and can lead to a reduction in server expenses by as much as 60%, all while maintaining high levels of performance and accuracy. Incorporated within Skymel’s Orchestrator Agent platform, NeuroSplit intelligently directs each inference request across various devices and cloud environments according to predetermined criteria such as latency, cost, or resource limitations, and it automatically implements fallback mechanisms and model selection based on user intent to ensure consistent reliability under fluctuating network conditions. Additionally, its decentralized framework provides robust security features including end-to-end encryption, role-based access controls, and separate execution contexts, which contribute to a secure user experience. To further enhance its utility, NeuroSplit also includes real-time analytics dashboards that deliver valuable insights into key performance indicators such as cost, throughput, and latency, allowing users to make informed decisions based on comprehensive data. By offering a combination of efficiency, security, and ease of use, NeuroSplit positions itself as a leading solution in the realm of adaptive inference technologies.

ModelArk is the central hub for ByteDance’s frontier AI models, offering a comprehensive suite that spans video generation, image editing, multimodal reasoning, and large language models. Users can explore high-performance tools like Seedance 1.0 for cinematic video creation, Seedream 3.0 for 2K image generation, and DeepSeek-V3.1 for deep reasoning with hybrid thinking modes. With 500,000 free inference tokens per LLM and 2 million free tokens for vision models, ModelArk lowers the barrier for innovation while ensuring flexible scalability. Pricing is straightforward and cost-effective, with transparent per-token billing that allows businesses to experiment and scale without financial surprises. The platform emphasizes security-first AI, featuring full-link encryption, sandbox isolation, and controlled, auditable access to safeguard sensitive enterprise data. Beyond raw model access, ModelArk includes PromptPilot for optimization, plug-in integration, knowledge bases, and agent tools to accelerate enterprise AI development. Its cloud GPU resource pools allow organizations to scale from a single endpoint to thousands of GPUs within minutes. Designed to empower growth, ModelArk combines technical innovation, operational trust, and enterprise scalability in one seamless ecosystem.

The Databricks Data Intelligence Platform empowers every member of your organization to leverage data and artificial intelligence effectively. Constructed on a lakehouse architecture, it establishes a cohesive and transparent foundation for all aspects of data management and governance, enhanced by a Data Intelligence Engine that recognizes the distinct characteristics of your data. Companies that excel across various sectors will be those that harness the power of data and AI. Covering everything from ETL processes to data warehousing and generative AI, Databricks facilitates the streamlining and acceleration of your data and AI objectives. By merging generative AI with the integrative advantages of a lakehouse, Databricks fuels a Data Intelligence Engine that comprehends the specific semantics of your data. This functionality enables the platform to optimize performance automatically and manage infrastructure in a manner tailored to your organization's needs. Additionally, the Data Intelligence Engine is designed to grasp the unique language of your enterprise, making the search and exploration of new data as straightforward as posing a question to a colleague, thus fostering collaboration and efficiency. Ultimately, this innovative approach transforms the way organizations interact with their data, driving better decision-making and insights.

Build, test and optimize Generative AI apps that unlock the value in your data. Our industry-leading ML expertise, our state-of-the art test and evaluation platform and advanced retrieval augmented-generation (RAG) pipelines will help you optimize LLM performance to meet your domain-specific needs. We provide an end-toend solution that manages the entire ML Lifecycle. We combine cutting-edge technology with operational excellence to help teams develop high-quality datasets, because better data leads better AI.

Transform your concepts into reality effortlessly — our intuitive interface allows you to create an AI-driven application in just a few minutes. Integrate GPT-3 online using a Web Search block, gather information through an HTTP request block, or link various Large Language Model (LLM) blocks together seamlessly. You can either share your application globally with a user interface or harness the capabilities of language by deploying it as a Discord bot for your community. With this flexibility, the possibilities for innovation are endless.