Best AI Development Platforms of 2024

Open source language models require time and specialized expertise. Taylor AI allows your engineering team focus on creating real business value rather than deciphering complicated libraries and setting up a training infrastructure. Working with third-party LLM vendors requires that your sensitive company data be exposed. Most providers reserve their right to retrain models using your data. Taylor AI allows you to own and control all of your models. Break free from the pay-per token pricing structure. Taylor AI only charges you for the training of the model. You can deploy and interact as much as you want with your AI models. Every month, new open source models are released. Taylor AI keeps up to date with the latest open source language models so that you don't need to. Train with the latest open-source models to stay ahead. You own the model so you can deploy according to your unique compliance standards and security standards.

Construct your model as a live interactive graph. View data flowing through the architecture of your visualized model. View and edit the model architecture at the atomic level. Graphbook offers X-ray transparency without black boxes. Graphbook checks data type and form in real-time, with clear error messages. This makes model debugging easy. Graphbook abstracts out software dependencies and configuration of the environment, allowing you to focus on your model architecture and data flows with the computing resources required. Cerbrec Graphbook transforms cumbersome AI modeling into a user friendly experience. Graphbook, which is backed by a growing community that includes machine learning engineers and data science experts, helps developers fine-tune their language models like BERT and GPT using text and tabular data. Everything is managed out of box, so you can preview how your model will behave.

Katonic Generative AI Platform allows you to build powerful enterprise-grade AI applications in minutes without any coding. Generative AI can boost your employees' productivity and improve your customer service. Create AI-powered digital assistants and chatbots that can access, process and refresh information from documents and dynamic content automatically using pre-built connectors. You can extract information from unstructured texts or uncover insights in specialized domains without creating templates. Transform dense text, such as financial reports, meeting transcripts, etc., into a personalized executive summary, capturing key information. Build recommendation systems to suggest products, content, or services based on past behavior and preferences.

Create, design, prototype and deploy custom AI workflows. Enhance customer engagement and team/personal productivity. Create and embed your website in just minutes. Connect your chatbot to your knowledge base. Instantly summarize and answer questions about audio, video, and website files. Create marketing copy, personalized emails, call summaries and graphics at large scale. Save time with a library of prebuilt pipelines, such as those for chatbots or document search. Share your pipelines to help the marketplace grow. Your data will not be stored on model providers' servers due to our zero-day retention policy and secure infrastructure. Our partnership begins with a free diagnostic, where we assess if your organization is AI-ready. We then create a roadmap to create a turnkey solution that fits into your processes.

Pezzo is an open-source LLMOps tool for developers and teams. With just two lines of code you can monitor and troubleshoot your AI operations. You can also collaborate and manage all your prompts from one place.

The prompt engineering platform allows you to experiment with different prompt versions. You can also evaluate and compare prompts in a series of tests, optimize prompts by one click, share and more. Optimize your AI development workflow. Key features that help you identify and get the best prompts for production use cases. Evaluation allows for a side-by-side comparison between prompts in test cases. Import test cases from CSV and define custom metrics for evaluation. Automatic template and prompt optimization can improve LLM results. View and manage all versions of the prompt and create OpenAI Functions. You can access all your prompts programmatically. This includes observability and analytics. Calculate the cost, latency and effectiveness of each prompt. Parea can help you improve your prompt engineering workflow. Parea helps developers improve the performance of LLM apps by implementing rigorous testing and versioning.

The list is not exhaustive. Our solution engineers will work with your team to customize Kolena to your workflows and business metrics. The aggregate metrics do not tell the whole story. Unexpected model behavior is the norm. The current testing processes are manual and error-prone. They also cannot be repeated. Models are evaluated based on arbitrary statistics that do not align with product objectives. It is difficult to track model improvement as data evolves. Techniques that are adequate for research environments do not meet the needs of production.

Braintrust is an enterprise-grade stack to build AI products. We take the uncertainty and tedium of integrating AI into your business out. From evaluations to prompt playgrounds to data management. Compare benchmarks, input/output pairs, and multiple prompts between runs. You can experiment with your draft or tinker it ephemerally. Braintrust can be integrated into your continuous integration workflow to track progress on the main branch and compare new experiments with what's already live before you ship. Easy capture and evaluate rated examples in staging & production. Then, incorporate them into "golden datasets". Datasets are stored in your cloud, and they are automatically versioned. This allows you to evolve them without risking affecting evaluations that rely on them.

Our low-code platform allows you to easily create AI solutions tailored to your specific needs. Our system is flexible and allows you to use a variety of AI algorithms including OpenAI, ChatGPT and your own data. OmniMind, a SaaS, allows you to search for AI answers using your own data and information. OmniMind allows you to process data without coding on AI rails. OmniMind.ai believes in providing users with an easy-to-use interface that makes creating custom AI systems a breeze. Our platform is designed to meet your needs, whether you are a newbie to AI or a seasoned developer.

Distributed training is possible without changing the model code. Determined takes care of provisioning, networking, data load, and fault tolerance. Our open-source deep-learning platform allows you to train your models in minutes and hours, not days or weeks. You can avoid tedious tasks such as manual hyperparameter tweaking, re-running failed jobs, or worrying about hardware resources. Our distributed training implementation is more efficient than the industry standard. It requires no code changes and is fully integrated into our state-ofthe-art platform. With its built-in experiment tracker and visualization, Determined records metrics and makes your ML project reproducible. It also allows your team to work together more easily. Instead of worrying about infrastructure and errors, your researchers can focus on their domain and build upon the progress made by their team.

Stop wasting your time managing integrations and fighting the limitations of "black-box" "solutions". Instantly integrate data from any source into your app in the format you prefer. 500+ API & DB Sources, connector SDKs, OAuth flows and flexible data models. Instant vector embeddings. Managed transactional & analytic storage. Instant SQL, REST & GraphQL APIs. Arch allows you to build AI-powered features based on your customer's data, without having to worry and maintain bespoke data infrastructure.

Create and manage AI applications without the need to move data to complex vector databases and pipelines. Integrate AI, vector search and real-time inference directly with your database. Python is all you need. All your AI models can be deployed in a single, scalable deployment. The AI models and APIs are automatically updated as new data is processed. You don't need to duplicate your data or create an additional database to use vector searching and build on it. SuperDuperDB allows vector search within your existing database. Integrate and combine models such as those from Sklearn PyTorch HuggingFace, with AI APIs like OpenAI, to build even the most complicated AI applications and workflows. With simple Python commands, deploy all your AI models in one environment to automatically compute outputs in your datastore (inference).

Train, fine-tune and generate text and image AI based on your data. We use the best open-source models for image and text generation, and can train them within minutes using LoRA fine tuning. Click the share button to generate a link or bot to your session. You can deploy your own private infrastructure. Create a free Stable Diffusion XL account to start chatting and generating images using open source language models. Drag'n'drop is the easiest way to fine-tune your model using your own text or images. It takes between 3-10 minutes. You can chat with the models and create images using a familiar chat interface.

Write a prompt and train it using your own content, knowledge, documents, and data. Create a cohesive interface for multiple apps that reflects the style of your brand. All can be accessed via a single link. Collect emails, charge customers, and upsell other services and products. Chipp's customized chat interfaces are trained to interact with your unique datasets, files, and documents. Our chatbots can be used for interactive storytelling or customer service. They provide relevant, context aware dialogues that reflect your brand voice.

With a fully automated cloud infrastructure, experts can explore data and write stable codes at the same time. Zerve’s data science environment gives data scientists and ML teams a unified workspace to explore, collaborate and build data science & AI project like never before. Zerve provides true language interoperability. Users can use Python, R SQL or Markdown in the same canvas and connect these code blocks. Zerve offers unlimited parallelization, allowing for code blocks and containers to run in parallel at any stage of development. Analysis artifacts can be automatically serialized, stored and preserved. This allows you to change a step without having to rerun previous steps. Selecting compute resources and memory in a fine-grained manner for complex data transformation.

Lazy AI is an innovative platform that allows users to create applications without coding. It requires a low level of skill and offers a library of pre-configured workflows. It allows users to jumpstart the application development journey by adding functionality using natural language, instead of writing code. Lazy AI not only works with frontend apps, but also backend apps. It deploys them automatically. Lazy AI makes the creation of applications easier than ever. Our customizable app templates allow you to easily create AI tools, Bots and Dev Tools for Finance, Marketing, Finance, and Marketing. Users can also browse by technology, such as Laravel, Twilio (Twitter), YouTube Selenium Webflow Stripe etc.

RagaAI is a leading AI testing platform which helps enterprises to mitigate AI risks, and make their models reliable and secure. Intelligent recommendations will reduce AI risk across cloud or edge deployments, and optimize MLOps cost. A foundation model designed specifically to revolutionize AI testing. You can easily identify the next steps for fixing dataset and model problems. AI-testing methods are used by many today, and they increase time commitments and reduce productivity when building models. They also leave unforeseen risks and perform poorly after deployment, wasting both time and money. We have created an end-toend AI testing platform to help enterprises improve their AI pipeline and prevent inefficiencies. 300+ tests to identify, fix, and accelerate AI development by identifying and fixing every model, data and operational issue.

Public datasets can help you improve the accuracy of your machine-learning models. Use curated datasets to save time on data preparation and discovery. These datasets are ready for use in machine-learning workflows and can be accessed from Azure services. Consider real-world factors which can have an impact on business outcomes. By incorporating features of curated datasets in your machine learning model, you can improve the accuracy and reduce the time required for data preparation. Share datasets with the growing community of data analysts and developers. Azure Open Datasets can be used to deliver insights at hyperscale with Azure's machine-learning and data analytics solutions. Open Datasets are free to use. Open Datasets are free to use, but you'll only be charged for the Azure services you consume, such as virtual machines, storage, networking resources and machine learning. Open data that has been curated and made available on Azure.

Build your RAG system intuitively with fewer abstractions than solutions like LangChain. You can choose from a variety of hosted and remote providers, including vector databases, datasets and Large Language Models. SciPhi allows you to version control and deploy your system from anywhere using Git. SciPhi's platform is used to manage and deploy an embedded semantic search engine that has over 1 billion passages. The team at SciPhi can help you embed and index your initial dataset into a vector database. The vector database will be integrated into your SciPhi workspace along with your chosen LLM provider.

AIxBlock is an end-to-end blockchain-based platform for AI that harnesses unused computing resources of BTC miners, as well as all global consumer GPUs. Our platform's training method is a hybrid machine learning approach that allows simultaneous training on multiple nodes. We use the DeepSpeed-TED method, a three-dimensional hybrid parallel algorithm which integrates data, tensor and expert parallelism. This allows for the training of Mixture of Experts models (MoE) on base models that are 4 to 8x larger than the current state of the art. The platform will identify and add compatible computing resources from the computing marketplace to the existing cluster of training nodes, and distribute the ML model for unlimited computations. This process unfolds dynamically and automatically, culminating in decentralized supercomputers which facilitate AI success.

Langtail is a platform that allows for the rapid development and deployment of Language Model (LLM) applications. It allows companies to quickly experiment, collaborate and launch production-grade LLM applications. The following are the key features: 1. No-code LLM Playground for quick debugging and ideas 2. Collaborative workspaces to share prompts and insights 3. Comprehensive observability suite including logging and analytics 4. Evaluation framework for systematically evaluating prompt performance 5. Deployment infrastructure to serve prompts via API across multiple environments 6. Future fine-tuning features to improve models based on user feedback Langtail enables both technical and nontechnical teams alike to quickly find LLM use cases that are high-value, refine prompts to ensure reliable performance, and deploy apps with ease. It's an all-in-one solution that will take your LLM project from prototype to production quicker than ever.

Thunderbit allows users to create their own AI apps and automations in just one click. Choose a template for a use-case, fill out a form, and the app/automation is created. Each app and automation can be configured using a no-code user interface. Thunderbit comes with a web assistant to help business users enhance SaaS applications. Our no code editor was built for the AI age: business users can quickly set up each step using natural language. Thunderbit offers a wide range of AI apps and automations, and a pricing model based on usage. Apps include AI web clipper and voice apps for updating CRM.

At competitive prices, you can access dedicated machines that are pre-configured with professional AI development tools. Apolo offers everything from HPC resources to a complete AI platform with a built-in ML toolkit. Apolo is available in a distributed architecture or as a dedicated enterprise cloud. It can also be deployed as a white-label multi-tenant solution that supports dedicated instances or self service cloud. Apolo creates a fully-fledged AI development environment, with all the tools needed at your fingertips. Apolo automates and manages the infrastructure for successful AI development. Apolo's AI services seamlessly integrate your on-prem resources and cloud resources. They also deploy pipelines and integrate your commercial and open-source development tools. Apolo provides enterprises with the resources and tools necessary to achieve breakthroughs when it comes to AI.

Infosys Nia™, an enterprise-grade AI platform, simplifies the AI adoption process for IT and Business. Infosys Nia supports the entire enterprise AI journey, from data management, digitization and image capture, model development, and operationalization. Nia's modular, scalable and advanced capabilities meet enterprise needs. Nia Data provides highly efficient tools and frameworks to support further ML experimentation using the Nia AML Workbench. The Nia DocAI platform automates all aspects of document processing, from ingestion to consumption. It uses AI capabilities like InfoExtractor and NLP, cognitive search, and computer vision.

Enterprise AI applications can be built, deployed, and operated. C3 AI®, Suite uses a unique model driven architecture to speed delivery and reduce the complexity of developing enterprise AI apps. The C3 AI model-driven architecture allows developers to create enterprise AI applications using conceptual models, rather than long code. This has significant benefits: AI applications and models can be used to optimize processes for every product or customer across all regions and businesses. You will see results in just 1-2 quarters. Also, you can quickly roll out new applications and capabilities. You can unlock sustained value - hundreds to billions of dollars annually - through lower costs, higher revenue and higher margins. C3.ai's unified platform, which offers data lineage as well as governance, ensures enterprise-wide governance for AI.