Alternatives to OpenCopilot

CORE is a high performance computing platform that can be used for a variety of applications. CORE is easy to use with its point-and-click interface. You can run the most complex applications. CORE provides unlimited computing power on-demand. Cloud computing is available without the high-cost. CORE for teams offers powerful tools that allow you to sort, filter, create, connect, and create users, machines, networks, and machines. With an intuitive and simple GUI, it's easier than ever to see all of your infrastructure from one place. It is easy to add Active Directory integration or VPN through our simple but powerful management console. It's now possible to do things that used to take days, or even weeks. Even complex network configurations can be managed with just a few clicks.

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).

Instantly provide your enterprise clients with answers and insights based on their business data. You are in a race against time to launch your product and balancing accuracy, latency and costs can be a nightmare. SaaS teams can use pre-configured copilots or custom rulebooks to create the latest technology. Our agents answer questions in simple english. The output is presented in smart insights, visualisations and other formats. Our advanced LLMs detects and generates all of your proactive insights. Our advanced LLMs automatically detect & prioritize & executes actions for you.

NVIDIA Base Command™ is an enterprise-class AI software service that allows businesses and their data scientists accelerate AI development. Base Command Platform, which is part of the NVIDIA DGX™ platform provides centralized, hybrid controls for AI training projects. It is compatible with NVIDIA DGX cloud and NVIDIA DGX superPOD. Base Command Platform in conjunction with NVIDIA's accelerated AI infrastructure provides a cloud hosted solution for AI development. Users can avoid the overheads and pitfalls associated with deploying and operating a DIY platform. Base Command Platform configures and manages AI workflows, provides integrated dataset management and executes them using the right-sized resources, ranging from a single GPU up to large-scale multi-node cloud clusters or on-premises. The platform is constantly updated by NVIDIA engineers and researchers, who rely on it daily.

Laminar is a platform that allows you to create the best LLM products. The quality of your LLM application is determined by the data you collect. Laminar helps collect, understand, and use this data. You can collect valuable data and get a clear view of the execution of your LLM application by tracing it. You can use this data to create better evaluations, dynamic examples and fine-tune your application. All traces are sent via gRPC in the background with minimal overhead. Audio models will be supported soon. Tracing text and image models are supported. You can use LLM-as a judge or Python script evaluators on each span. Evaluators can label spans. This is more scalable than manual labeling and is especially useful for smaller teams. Laminar allows you to go beyond a simple prompt. You can create and host complex chains including mixtures of agents, or self-reflecting LLM pipes.

Discuro is an all-in-one platform that allows developers to quickly build, test and consume complex AI workflows. Our UI makes it easy to define your workflow. When you are ready to execute, just make one API call to Discuro with any inputs and any meta-data. You can use an Orchestrator to feed the generated data back into GPT-3. Integrate with OpenAI to extract the data you need quickly. In minutes, create and consume your own flows. Everything you need to integrate OpenAI at scale has been built by us so that you can concentrate on the product. Integrating with OpenAI is not easy. We'll help you extract the data you need by collecting input/output descriptions. You can easily chain completions together to create large data sets. You can use our iterative input feature for GPT-3 output to feed back in and have us make successive calls to expand your data set. Easy to build and test complex, self-transforming AI workflows and datasets.

Use AI algorithms to receive intelligent suggestions about your API design. Automated recommendations tailored to your project will accelerate development. AI can automatically generate your database. Streamline deployment and increase productivity. Create and implement automated workflows to ensure a smooth, efficient development cycle. Customize automation processes to meet your project requirements. Workflows that are adaptable will allow you to create a personalized experience. Enjoy the flexibility to manage diverse data sources in a single, organized workspace. Workspaces can be designed to reflect the structure of projects. Create dedicated workspaces that can house multiple data sources seamlessly. Streamlining tasks by automating processes, increasing efficiency, and reducing the amount of manual effort. Each user has their own instance(s). Custom logic can be used to handle complex data operations.

A system that can scale to millions of users, without requiring an engineering team. Create, customize and deploy your chat-based AI. Finance chatbot. xFinance is a 13-billion-parameter model fine-tuned using LoRA. Our goal was show that impressive results can be achieved in financial NLP without breaking the bank. Your own AI assistant to chat with documents. Single or multiple documents. Simple or complex questions. Easy-to-use deep learning platform, hardware efficient algorithms that speed up inference and lower costs. Real-time monitoring and logging of resource usage and cloud costs for deployed models. xTuring, an open-source AI software for personalization, is a powerful tool. xTuring provides a simple interface for personalizing LLMs based on your data and application.

Lunary is a platform for AI developers that helps AI teams to manage, improve and protect chatbots based on Large Language Models (LLM). It includes features like conversation and feedback tracking as well as analytics on costs and performance. There are also debugging tools and a prompt directory to facilitate team collaboration and versioning. Lunary integrates with various LLMs, frameworks, and languages, including OpenAI, LangChain and JavaScript, and offers SDKs in Python and JavaScript. Guardrails to prevent malicious prompts or sensitive data leaks. Deploy Kubernetes/Docker in your VPC. Your team can judge the responses of your LLMs. Learn what languages your users speak. Experiment with LLM models and prompts. Search and filter everything in milliseconds. Receive notifications when agents do not perform as expected. Lunary's core technology is 100% open source. Start in minutes, whether you want to self-host or use the cloud.

AI-FLOW, an innovative open-source software platform, simplifies the way creators and innovators harness artificial intelligence. AI-FLOW's drag-and-drop user interface allows you to easily connect and combine AI models to create custom AI tools tailored to meet your needs. Key Features: Diverse AI Model Integration: Access a range of top-tier AI Models, including GPT-4 and DALL-E 3. 2. Drag-and-Drop: Create complex AI workflows without coding thanks to our intuitive design. 3. Custom AI Tool Creation: Create AI solutions that are tailored to your needs, from image generation through to language processing. 4. Local Data Storage: Take full control of your data by storing it locally and exporting it as JSON files.

TorchScript allows you to seamlessly switch between graph and eager modes. TorchServe accelerates the path to production. The torch-distributed backend allows for distributed training and performance optimization in production and research. PyTorch is supported by a rich ecosystem of libraries and tools that supports NLP, computer vision, and other areas. PyTorch is well-supported on major cloud platforms, allowing for frictionless development and easy scaling. Select your preferences, then run the install command. Stable is the most current supported and tested version of PyTorch. This version should be compatible with many users. Preview is available for those who want the latest, but not fully tested, and supported 1.10 builds that are generated every night. Please ensure you have met the prerequisites, such as numpy, depending on which package manager you use. Anaconda is our preferred package manager, as it installs all dependencies.

Open Agent Studio is more than just another copilot. It's a co-pilot builder with no code that allows solutions that are not possible in any other RPA tool today. We believe that other tools will copy our idea, and so we are giving our customers a head start in the next few months. They can target markets previously untapped by AI using their deep industry insights. Subscribers can access a 4-week free course that teaches them how to evaluate product concepts and launch a customized agent with a white label enterprise-grade. You can easily build agents by recording your keyboard and mice actions, such as scraping data and detecting a start node. The agent recorder allows you to build generalized agents in as little time as possible. Record once and then share it across your organization for future-proof agents.

Describe examples of API requests and responses. Define API logic in natural language. Test your API endpoints, and fine-tune prompt, response structure, or request structure. Integrate API endpoints into your applications with just a click. In less than one minute, you can build and deploy sophisticated application logic with no code. No need for individual LLM accounts. Sign up for Backengine and get started building. Our super-fast backend architecture is available immediately. All endpoints have been secured and protected, so that only you and your application can use them. Manage your team members easily so that everyone can work on Backengine endpoints. Add persistent data to your Backengine endpoints. A complete replacement for the backend. Use external APIs to integrate your endpoints.

LMOps is a stack that allows you to launch production-ready applications for monitoring, model management and more. Portkey is a replacement for OpenAI or any other provider APIs. Portkey allows you to manage engines, parameters and versions. Switch, upgrade, and test models with confidence. View aggregate metrics for your app and users to optimize usage and API costs Protect your user data from malicious attacks and accidental exposure. Receive proactive alerts if things go wrong. Test your models in real-world conditions and deploy the best performers. We have been building apps on top of LLM's APIs for over 2 1/2 years. While building a PoC only took a weekend, bringing it to production and managing it was a hassle! We built Portkey to help you successfully deploy large language models APIs into your applications. We're happy to help you, regardless of whether or not you try Portkey!

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.

Fully managed infrastructure, tools and workflows allow you to build, train and deploy models faster. Scale inference and deploy custom AI & LLMs in seconds on any infrastructure. Schedule batch jobs to handle your most demanding tasks, and only pay per second. Optimize costs by utilizing GPUs, spot instances, and automatic failover. YAML simplifies complex infrastructure setups by allowing you to train with a single command. Automate the scaling up of workers during periods of high traffic, and scaling down to zero when inactive. Deploy cutting edge models with persistent endpoints within a serverless environment to optimize resource usage. Monitor system and inference metrics, including worker counts, GPU utilization, throughput, and latency in real-time. Split traffic between multiple models to evaluate.

Martian outperforms GPT-4 across OpenAI's evals (open/evals). Martian outperforms GPT-4 in all OpenAI's evaluations (open/evals). We transform opaque black boxes into interpretable visual representations. Our router is our first tool built using our model mapping method. Model mapping is being used in many other applications, including transforming transformers from unintelligible matrices to human-readable programs. Automatically reroute your customers to other providers if a company has an outage or a high latency period. Calculate how much money you could save using the Martian Model Router by using our interactive cost calculator. Enter the number of users and tokens per session. Also, specify how you want to trade off between cost and quality.

Transform your business operations with our cutting-edge AI-powered solutions. Harness the potential of historical data to drive innovation, optimize efficiency, and propel your growth – revolutionizing your business processes, one task at a time. At Ever Efficient AI, we understand the value of your historical data and its untapped potential. By analyzing historical data in new and creative ways, we unlock opportunities for process efficiency, enhanced decision-making, waste reduction & drive growth. Ever Efficient AI's task automation is designed to take the strain out of your daily operations. Our AI systems can manage and automate a wide range of tasks, from scheduling to data management, allowing you and your team to focus on what truly matters - your core business.

Graphlit simplifies the process of building an AI copilot or chatbot or adding LLMs to your existing application. Graphlit is a serverless platform that automates complex data processes, including data ingestion and extraction, LLM conversations. It also integrates webhooks, alerting, semantic search, and alerting. Graphlit's workflow as code approach allows you to programmatically define every step in the workflow. Data ingestion, metadata indexing, data preparation and data enrichment. Integration with your applications is achieved through event-based webhooks, API integrations, and integrations with event-based Webhooks.

Deploy LLMs, and other AI - commercial, homegrown, or open-source - on your private network based on a AI-optimized foundation. AI Core is an accurate, real-time representation of your entire business, including all decisions, actions, and processes. Use the Action Graph on top of the AI Core to set specific scopes for LLMs and models - such as hand-off procedures and auditable calculations. Monitor and control LLM activities and reach in real time to help users promote compliance.

Minerva, our proprietary AI platform, is used internally to create AI applications that can perform real-world tasks that require human-level understanding. Minerva's reach increases through the deployment domain-specific AI apps. Minerva adds knowledge, performs more general tasks, and connects dots that humans cannot. These powerful components are used to build our scalable AI apps such as Argus or Supernova. Minerva allows you to create your own AI workforce, and to transcend information complexity to make faster, more accurate decisions. Minerva allows natural user interaction via various dashboards or APIs that allow for the consumption of insight, feedback, and secure integration of Accrete's AI apps into existing enterprise workflows.

Release high-quality LLM applications quickly without compromising testing. Never let the subjective and complex nature of LLM interactions hold you back. Generative AI produces subjective results. A subject matter expert must manually check a generated text to determine its quality. You probably know if you're developing an LLM application that you cannot release it without addressing numerous constraints and edge cases. Hallucinations and other issues, such as incorrect answers, bias and deviations from policy, harmful material, and others, need to be identified, investigated, and mitigated both before and after the app is released. Deepchecks allows you to automate your evaluation process. You will receive "estimated annotations", which you can only override if necessary. Our LLM product has been extensively tested and is robust. It is used by more than 1000 companies and integrated into over 300 open source projects. Validate machine-learning models and data in the research and production phases with minimal effort.

Discover. Analyze. Optimize. Use [impaction.ai]’s intuitive semantic search to easily sift conversational data. Type 'find me conversation where ...', and let our engine handle the rest. Meet Columbus, your intelligent data co-pilot. Columbus analyzes conversations and highlights key trends. It can even recommend which dialogues you should pay attention to. Take data-driven action to improve user engagement and create a smarter and more responsive AI product. Columbus is not only a great source of information, but also offers suggestions on how to improve the situation.

Learn how to choose the right LLM based on your needs, and how you can optimize quality, speed and cost-efficiency. With a single API and standard API, you can access all LLMs from all providers. Set your own constraints for output speed, latency and cost. Define your own quality metric. Personalize your router for your requirements. Send your queries to the fastest providers based on the latest benchmark data for the region you are in, updated every 10 minutes. Unify's dedicated walkthrough will help you get started. Discover the features that you already have and our upcoming roadmap. Create a Unify Account to access all models supported by all providers using a single API Key. Our router balances output speed, quality, and cost according to user preferences. The quality of the output is predicted using a neural scoring system, which predicts each model's ability to respond to a given prompt.

Capture production data. Evaluate outputs together and fine-tune the performance of your LLM. A detailed log overview will help you understand what is happening in production. Work with domain experts, product managers and engineers to create reliable model outputs. Track AI metrics, such as speed, token usage, and quality scores. Copilot automates model evaluations and improvements for your use cases. Create, manage, or optimize prompts for precise and relevant interactions between AI models and users. Compare fine-tuned models and foundation models to improve prompt performance. Build a fine-tuning dataset with your team. Create custom fine-tuning data to optimize model performance.

Your platform for developing generative AI and custom copilots. Use pre-built and customizable AI model on your data to build solutions faster. Explore a growing collection of models, both open-source and frontier-built, that are pre-built and customizable. Create AI models using a code first experience and an accessible UI validated for accessibility by developers with disabilities. Integrate all your OneLake data into Microsoft Fabric. Integrate with GitHub codespaces, Semantic Kernel and LangChain. Build apps quickly with prebuilt capabilities. Reduce wait times by personalizing content and interactions. Reduce the risk for your organization and help them discover new things. Reduce the risk of human error by using data and tools. Automate operations so that employees can focus on more important tasks.

SuperAGI SuperCoder combines AI-native development platform & AI agents in order to enable fully autonomous software creation starting with the python programming language & frameworks. SuperCoder 2.0 leverages Large Action Models (LAMs) and LLMs fine-tuned to python code creation leading to one-shot or few-shot python functional programming with significantly higher accuracy on SWE-bench and Codebench SuperCoder 2.0 is an autonomous system that combines software guardrails for Flask & Django development frameworks with SuperAGI's Generally Intelligent Developer Agents in order to deliver complex real-world software systems SuperCoder 2.0 integrates deeply with existing developer stacks such as Jira or Github, Jenkins, CSPs, and QA solutions like BrowserStack/Selenium Clouds, to ensure a seamless experience in software development.

A 2-way bridge that can be programmed between your copilot and your application (client or cloud). Supports third-party integrations (e.g. Salesforce and Zendesk).

Simulations based on historical data can be used to improve models and update them incrementally. Data governance, access control, and versioning allow for easy collaboration. Ikigai has a wide range of integrations that make it easy to integrate with tools already in your workflow. Ikigai has 200+ connectors that allow you to connect to almost any data source. Want to push your ML to a dashboard or website? Integrate directly using Ikigai’s web integrations. Triggers can be used to run data synchronizations, and retrieve updates every time you run an automation flow. You can integrate Ikigai seamlessly by using your own APIs or creating APIs for your data stack.

Get a complete picture of the performance of your model. Log inputs and out-puts, and enrich them with metadata. Find out what your model is doing and where it can be improved. Monitor for errors, and identify underperforming cohorts or use cases. The best models are based on user data. To retrain your model, you can programmatically gather examples that are unusual or underperforming. When changing your model or prompt, stop manually reviewing thousands outputs. Apps powered by LLM can be evaluated programmatically. Detect and fix degradations fast. Monitor new deployments and edit your app in real-time. Connect your data sources to your self-hosted model or third-party model. Our serverless streaming dataflow engines can handle large amounts of data. Gantry is SOC-2-compliant and built using enterprise-grade authentication.

Confident AI is used by companies of all sizes to prove that their LLM is worth being in production. On a single, central platform, you can evaluate your LLM workflow. Deploy LLM with confidence to ensure substantial benefits, and address any weaknesses within your LLM implementation. Provide ground truths to serve as benchmarks for evaluating your LLM stack. Ensure alignment with predefined output expectation, while identifying areas that need immediate refinement and adjustments. Define ground facts to ensure that your LLM behaves as expected. Advanced diff tracking for iterating towards the optimal LLM stack. We guide you through the process of selecting the right knowledge bases, altering the prompt templates and selecting the best configurations for your use case. Comprehensive analytics to identify focus areas. Use out-of-the box observability to identify use cases that will bring the greatest ROI for your organization. Use metric insights to reduce LLM costs and delays over time.

Create your own AI backend within minutes. Build complex AI workflows using a simple point and click interface.

You will find the tools to adapt cutting-edge AI to your specific needs using your own data. Combine the expertise of multiple cutting-edge AI agents to create super-intelligent AI. All AI models on the platform are available as open-source. The datasets that they were trained on, as well as their limitations and biases, are all available.

Import data, such as text or images, from any source, including documents, cloud services or APIs, and launch a ChatGPT interface based upon your preferred large-language model, like GPT-4 or FLAN, and answer user questions based on imported data. A comprehensive list of sample queries that can be sent to an LLM connected through ZBrain to a company’s private data source. ZBrain can be seamlessly integrated into your existing products and tools as a prompt response service. You can enhance your deployment experience by choosing secure options such as ZBrain Cloud, or self-hosting on a private infrastructure. ZBrain Flow allows you to create business rules without writing code. The intuitive flow interface lets you connect multiple large language and prompt templates, image and video models, and extraction and parsing to build powerful, intelligent applications.

RapidCanvas is a no-code AI platform that helps businesses go from idea to live AI solution within hours. Our AutoAI technology automates the AI build and deploy process, reducing time to value by 90% or more. We work with you to understand your needs and create out-of-the-box AI solutions that are tailored to your specific business requirements. Our data science experts are available to help you optimize the results and ensure that you are satisfied with the performance of your AI solution. RapidCanvas is used by leaders in the Financial Services, Retail, Renewable Energy, and Manufacturing industries. We are committed to helping businesses of all sizes get the most out of AI.

BenchLLM allows you to evaluate your code in real-time. Create test suites and quality reports for your models. Choose from automated, interactive, or custom evaluation strategies. We are a group of engineers who enjoy building AI products. We don't want a compromise between the power, flexibility and predictability of AI. We have created the open and flexible LLM tool that we always wanted. CLI commands are simple and elegant. Use the CLI to test your CI/CD pipeline. Monitor model performance and detect regressions during production. Test your code in real-time. BenchLLM supports OpenAI (Langchain), and any other APIs out of the box. Visualize insightful reports and use multiple evaluation strategies.

Monitor your LLMs during production and discover and correct hallucinations and errors related to accuracy and quality with LLM outputs. Check your outputs to see if they contain hallucinations, misinformation or other issues. Configurable for any LLM application. Segment data to analyze in depth your cost, accuracy and response times. To debug generation, you can search, sort and filter your inference calls and trace your queries, retrievals and responses. Explore your conversations to learn what your users feel and what they are saying. You can also find out which conversations were unsuccessful. Compare your performance metrics between different models and prompts. Our insights will guide you to the best model for each use case. Our evaluators analyze and improve the outputs by using your data, configurations and feedback.

Nyckel makes it easy to auto-label images and text using AI. We say ‘easy’ because trying to do classification through complicated AI tools is hard. And confusing. Especially if you don't know machine learning. That’s why Nyckel built a platform that makes image and text classification easy. In just a few minutes, you can train an AI model to identify attributes of any image or text. Our goal is to help anyone spin up an image or text classification model in just minutes, regardless of technical knowledge.

ClearML is an open-source MLOps platform that enables data scientists, ML engineers, and DevOps to easily create, orchestrate and automate ML processes at scale. Our frictionless and unified end-to-end MLOps Suite allows users and customers to concentrate on developing ML code and automating their workflows. ClearML is used to develop a highly reproducible process for end-to-end AI models lifecycles by more than 1,300 enterprises, from product feature discovery to model deployment and production monitoring. You can use all of our modules to create a complete ecosystem, or you can plug in your existing tools and start using them. ClearML is trusted worldwide by more than 150,000 Data Scientists, Data Engineers and ML Engineers at Fortune 500 companies, enterprises and innovative start-ups.

With a single command, you can train and serve large AI models in scale. You can simply point to your S3 bucket. We take care of the rest: orchestration, efficiency and node failures. Simple and scalable. MosaicML allows you to train and deploy large AI model on your data in a secure environment. Keep up with the latest techniques, recipes, and foundation models. Our research team has developed and rigorously tested these recipes. In just a few easy steps, you can deploy your private cloud. Your data and models will never leave the firewalls. You can start in one cloud and continue in another without missing a beat. Own the model trained on your data. Model decisions can be better explained by examining them. Filter content and data according to your business needs. Integrate seamlessly with your existing data pipelines and experiment trackers. We are cloud-agnostic and enterprise-proven.

PromptQL, a platform created by Hasura, allows Large Language Models to interact with structured data through agentic querying. This approach allows AI agents retrieve and process data using a human-like interface, improving their ability to handle real-world queries. PromptQL allows LLMs to manipulate and query data accurately by providing them with a Python interface and a standard SQL interface. The platform allows users to create AI assistants that are tailored to their needs by integrating with different data sources such as GitHub repositories or PostgreSQL database. PromptQL overcomes the limitations of traditional search retrieval methods, allowing AI agents to perform tasks like gathering relevant emails and identifying follow-ups more accurately. Users can start by connecting their data, adding the LLM API key and building with AI.

Metal is a fully-managed, production-ready ML retrieval platform. Metal embeddings can help you find meaning in unstructured data. Metal is a managed services that allows you build AI products without having to worry about managing infrastructure. Integrations with OpenAI and CLIP. Easy processing & chunking of your documents. Profit from our system in production. MetalRetriever is easily pluggable. Simple /search endpoint to run ANN queries. Get started for free. Metal API Keys are required to use our API and SDKs. Authenticate by populating headers with your API Key. Learn how to integrate Metal into your application using our Typescript SDK. You can use this library in JavaScript as well, even though we love TypeScript. Fine-tune spp programmatically. Indexed vector data of your embeddings. Resources that are specific to your ML use case.

Connecting every data source with analytics services on a single AI-powered platform will transform how people access, manage, and act on data and insights. All your data. All your teams. All your teams in one place. Create an open, lake-centric hub to help data engineers connect data from various sources and curate it. This will eliminate sprawl and create custom views for all. Accelerate analysis through the development of AI models without moving data. This reduces the time needed by data scientists to deliver value. Microsoft Teams, Microsoft Excel, and Microsoft Teams are all great tools to help your team innovate faster. Connect people and data responsibly with an open, scalable solution. This solution gives data stewards more control, thanks to its built-in security, compliance, and governance.

Build complex backend agents using multiple steps with an action-based orchestration. All LLMs are supported. Build a fully customized UI without writing a line of code for your agent, and serve it on your own domain. Track your agent's every move, literally, to cope with the nondeterministic nature LLMs. Access control can be built at a finer grain for your application, data and agent. A fine-tuned, specialized model to accelerate software development. Automatically handle concurrency and rate limiting.

Clevis allows users to create AI applications without writing code. Users can easily create, execute and market apps that include text generation, image creation, and web scraping, using a variety of pre-built processing step. Learn how to create an app that can generate recipes based on dietary preferences, or one that can create character biographies and pictures using only a name and year. Create your app by combining text generation, image creation, and API requests. Start your journey quickly with one of our templates. Share a link that is publicly accessible to allow anyone to run your app. Clevis provides a set of features to simplify the creation of your AI application. You can monetize by selling access to your app with usage-based pricing. Start your app with a simple HTTP call using your API key.

Embeddings for your images and vector stores. Imagine OpenAI + Pinecone for images. Say goodbye to manual tagging of images and hello to seamless integration. Image embeddings are powerful tools that streamline the process of searching, storing, and retrieving pictures. Add image search functionality to your GPT bots with just a few easy steps. Add visual capabilities to AI searches. Search your own photo catalog and answer your customers' questions.

Aigur makes it easy to create multi-user generative AI applications that manage data pipelines, user plans, security, and other aspects. We can help you manage and monitor your users' usage plans. You can grant and regenerate credits, limit usage over the time, use partial credits, and much more. A visual editor allows you to define your backend logic. It is supported by code that can be edited. Our pre-defined pipelines will reduce development time so you can focus on the logic of your application. Aigur makes it simple to develop your front end. Aigur's prebuilt component library for web and mobile AI allows you to authenticate users and handle job updates based upon web sockets. This will cut down development time and help you reduce your development time. You will receive a simple API that allows you to manage the user flows. You don't have to replace your entire infrastructure. Just call a few functions, and you're done. For more information, see our opensource library's documentation.

Wordware allows anyone to create, iterate and deploy useful AI agents. Wordware combines software's best features with the power of language. Remove the constraints of traditional tools that don't require code and empower each team member to iterate on their own. Natural language programming will be around for a long time. Wordware removes prompt from codebases by providing non-technical and technical users with a powerful AI agent creation IDE. Our interface is simple and flexible. With an intuitive design, you can empower your team to collaborate easily, manage prompts and streamline workflows. Loops, branching and structured generation, as well as version control and type safety, help you make the most of LLMs. Custom code execution allows you connect to any API. Switch between large language models with just one click. Optimize your workflows with the best cost-to-latency-to-quality ratios for your application.

IBM Watson Machine Learning, a full-service IBM Cloud offering, makes it easy for data scientists and developers to work together to integrate predictive capabilities into their applications. The Machine Learning service provides a set REST APIs that can be called from any programming language. This allows you to create applications that make better decisions, solve difficult problems, and improve user outcomes. Machine learning models management (continuous-learning system) and deployment (online batch, streaming, or online) are available. You can choose from any of the widely supported machine-learning frameworks: TensorFlow and Keras, Caffe or PyTorch. Spark MLlib, scikit Learn, xgboost, SPSS, Spark MLlib, Keras, Caffe and Keras. To manage your artifacts, you can use the Python client and command-line interface. The Watson Machine Learning REST API allows you to extend your application with artificial intelligence.

FieldDay lets you explore the world of AI, Machine Learning and AI right on your smartphone. We've simplified the process of creating machine learning models by turning it into a hands-on, engaging experience that's as easy as using your camera. FieldDay lets you create custom AI apps, and embed them into your favorite tools using only your phone. You can use FieldDay examples as a learning tool and create a custom model that is ready to embed in your app/project. FieldDay machine-learning models are used in a variety of projects and applications. Our range of export and integration options makes it easy to embed a machine learning model into any platform. FieldDay allows you to collect data from your phone camera. Our interface is designed to allow for intuitive and easy annotation during collection. You can create a custom dataset quickly. FieldDay allows you to preview and correct models in real-time.