BenchLLM Alternatives

An end-to-end open source machine learning platform. TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML powered applications. Build and train ML models easily using intuitive high-level APIs like Keras with eager execution, which makes for immediate model iteration and easy debugging. Easily train and deploy models in the cloud, on-prem, in the browser, or on-device no matter what language you use. A simple and flexible architecture to take new ideas from concept to code, to state-of-the-art models, and to publication faster. Build, deploy, and experiment easily with TensorFlow.

Klu.ai is a Generative AI platform that simplifies the process of designing, deploying, and optimizing AI applications. Klu integrates with your preferred Large Language Models, incorporating data from varied sources, giving your applications unique context. Klu accelerates building applications using language models like Anthropic Claude, Azure OpenAI, GPT-4, and over 15 other models, allowing rapid prompt/model experimentation, data gathering and user feedback, and model fine-tuning while cost-effectively optimizing performance. Ship prompt generations, chat experiences, workflows, and autonomous workers in minutes. Klu provides SDKs and an API-first approach for all capabilities to enable developer productivity. Klu automatically provides abstractions for common LLM/GenAI use cases, including: LLM connectors, vector storage and retrieval, prompt templates, observability, and evaluation/testing tooling.

Release high-quality LLM apps quickly without compromising on testing. Never be held back by the complex and subjective nature of LLM interactions. Generative AI produces subjective results. Knowing whether a generated text is good usually requires manual labor by a subject matter expert. If you’re working on an LLM app, you probably know that you can’t release it without addressing countless constraints and edge-cases. Hallucinations, incorrect answers, bias, deviation from policy, harmful content, and more need to be detected, explored, and mitigated before and after your app is live. Deepchecks’ solution enables you to automate the evaluation process, getting “estimated annotations” that you only override when you have to. Used by 1000+ companies, and integrated into 300+ open source projects, the core behind our LLM product is widely tested and robust. Validate machine learning models and data with minimal effort, in both the research and the production phases.

Build and manage AI applications easily without needing to move your data to complex pipelines and specialized vector databases. Integrate AI and vector search directly with your database including real-time inference and model training. A single scalable deployment of all your AI models and APIs which is automatically kept up-to-date as new data is processed immediately. No need to introduce an additional database and duplicate your data to use vector search and build on top of it. SuperDuperDB enables vector search in your existing database. Integrate and combine models from Sklearn, PyTorch, and HuggingFace with AI APIs such as OpenAI to build even the most complex AI applications and workflows. Deploy all your AI models to automatically compute outputs (inference) in your datastore in a single environment with simple Python commands.

Launch production-ready apps with the LMOps stack for monitoring, model management, and more. Replace your OpenAI or other provider APIs with the Portkey endpoint. Manage prompts, engines, parameters, and versions in Portkey. Switch, test, and upgrade models with confidence! View your app performance & user level aggregate metics to optimise usage and API costs Keep your user data secure from attacks and inadvertent exposure. Get proactive alerts when things go bad. A/B test your models in the real world and deploy the best performers. We built apps on top of LLM APIs for the past 2 and a half years and realised that while building a PoC took a weekend, taking it to production & managing it was a pain! We're building Portkey to help you succeed in deploying large language models APIs in your applications. Regardless of you trying Portkey, we're always happy to help!

Discuro is the all-in-one platform for developers looking to easily build, test & consume complex AI workflows. Define your workflow in our easy-to-use UI, and when you're ready to execute, simply make one API call to us, with your inputs, any meta-data, and we'll do the rest. Use an Orchestrator to feed generated data back into GPT-3. Reliably integrate with OpenAI and extract the data you need with ease. Create & consume your own flows in minutes. We've built everything you need to integrate with OpenAI, at scale, so you can focus on the product. The first challenge in integrating with OpenAI is extracting the data you need, we'll handle this for you by collecting input/output definitions. Easily chain completions together to build large data sets. Use our iterative input feature to feed GPT-3 output back in, and have us make consecutive calls to expand your data set, and much more. Easily build & test complex self-transforming AI workflows & datasets.

Open Agent Studio is not just another co-pilot it's a no-code co-pilot builder that enables solutions that are impossible in all other RPA tools today. We believe these other tools will copy this idea, so our customers have a head start over the next few months to target markets previously untouched by AI with their deep industry insight. Subscribers have access to a free 4-week course, which teaches how to evaluate product ideas and launch a custom agent with an enterprise-grade white label. Easily build agents by simply recording your keyboard and mouse actions, including scraping data and detecting the start node. The agent recorder makes it as easy as possible to build generalized agents as quickly as you can teach how to do it. Record once, then share across your organization to scale up future-proof agents.

Unexpected results happen all the time. With full visibility into the entire chain sequence of calls, you can spot the source of errors and surprises in real time with surgical precision. Software engineering relies on unit testing to build performant, production-ready applications. LangSmith provides that same functionality for LLM applications. Spin up test datasets, run your applications over them, and inspect results without having to leave LangSmith. LangSmith enables mission-critical observability with only a few lines of code. LangSmith is designed to help developers harness the power–and wrangle the complexity–of LLMs. We’re not only building tools. We’re establishing best practices you can rely on. Build and deploy LLM applications with confidence. Application-level usage stats. Feedback collection. Filter traces, cost and performance measurement. Dataset curation, compare chain performance, AI-assisted evaluation, and embrace best practices.

The prompt engineering platform to experiment with different prompt versions, evaluate and compare prompts across a suite of tests, optimize prompts with one-click, share, and more. Optimize your AI development workflow. Key features to help you get and identify the best prompts for your production use cases. Side-by-side comparison of prompts across test cases with evaluation. CSV import test cases, and define custom evaluation metrics. Improve LLM results with automatic prompt and template optimization. View and manage all prompt versions and create OpenAI functions. Access all of your prompts programmatically, including observability and analytics. Determine the costs, latency, and efficacy of each prompt. Start enhancing your prompt engineering workflow with Parea today. Parea makes it easy for developers to improve the performance of their LLM apps through rigorous testing and version control.

Freeplay gives product teams the power to prototype faster, test with confidence, and optimize features for customers, take control of how you build with LLMs. A better way to build with LLMs. Bridge the gap between domain experts & developers. Prompt engineering, testing & evaluation tools for your whole team.

Transition seamlessly between eager and graph modes with TorchScript, and accelerate the path to production with TorchServe. Scalable distributed training and performance optimization in research and production is enabled by the torch-distributed backend. A rich ecosystem of tools and libraries extends PyTorch and supports development in computer vision, NLP and more. PyTorch is well supported on major cloud platforms, providing frictionless development and easy scaling. Select your preferences and run the install command. Stable represents the most currently tested and supported version of PyTorch. This should be suitable for many users. Preview is available if you want the latest, not fully tested and supported, 1.10 builds that are generated nightly. Please ensure that you have met the prerequisites (e.g., numpy), depending on your package manager. Anaconda is our recommended package manager since it installs all dependencies.

Build better AI with multiple models. AI models are a new kind of building block. Sieve is the easiest way to use these building blocks to understand audio, generate video, and much more at scale. State-of-the-art models in just a few lines of code, and a curated set of production-ready apps for many use cases. Import your favorite models like Python packages. Visualize results with auto-generated interfaces built for your entire team. Deploy custom code with ease. Define your environment compute in code, and deploy with a single command. Fast, scalable infrastructure without the hassle. We built Sieve to automatically scale as your traffic increases with zero extra configuration. Package models with a simple Python decorator and deploy them instantly. A full-featured observability stack so you have full visibility of what’s happening under the hood. Pay only for what you use, by the second. Gain full control over your costs.

OpenPipe provides fine-tuning for developers. Keep your datasets, models, and evaluations all in one place. Train new models with the click of a button. Automatically record LLM requests and responses. Create datasets from your captured data. Train multiple base models on the same dataset. We serve your model on our managed endpoints that scale to millions of requests. Write evaluations and compare model outputs side by side. Change a couple of lines of code, and you're good to go. Simply replace your Python or Javascript OpenAI SDK and add an OpenPipe API key. Make your data searchable with custom tags. Small specialized models cost much less to run than large multipurpose LLMs. Replace prompts with models in minutes, not weeks. Fine-tuned Mistral and Llama 2 models consistently outperform GPT-4-1106-Turbo, at a fraction of the cost. We're open-source, and so are many of the base models we use. Own your own weights when you fine-tune Mistral and Llama 2, and download them at any time.

Your platform for developing generative AI solutions and custom copilots. Build solutions faster, using pre-built and customizable AI models on your data—securely—to innovate at scale. Explore a robust and growing catalog of pre-built and customizable frontier and open-source models. Create AI models with a code-first experience and accessible UI validated by developers with disabilities. Seamlessly integrate all your data from OneLake in Microsoft Fabric. Integrate with GitHub Codespaces, Semantic Kernel, and LangChain. Access prebuilt capabilities to build apps quickly. Personalize content and interactions and reduce wait times. Lower the burden of risk and aid in new discoveries for organizations. Decrease the chance of human error using data and tools. Automate operations to refocus employees on more critical tasks.

Capture production data, evaluate outputs collaboratively, and fine-tune your LLM's performance. Know exactly what goes on in production with an in-depth log overview. Collaborate with product managers, domain experts and engineers to build reliable model outputs. Track AI metrics such as speed, quality scores, and token usage. Copilot automates evaluations and model improvements for your use case. Create, manage, and optimize prompts to achieve precise and relevant interactions between users and AI models. Compare foundation models, and fine-tuned versions to improve prompt performance and save tokens. Collaborate with your team to build a proprietary fine-tuning dataset for your AI models. Build custom fine-tuning datasets to optimize model performance for specific use cases.

The open-source ML observability platform. Evaluate, test, and monitor ML models from validation to production. From tabular data to NLP and LLM. Built for data scientists and ML engineers. All you need to reliably run ML systems in production. Start with simple ad hoc checks. Scale to the complete monitoring platform. All within one tool, with consistent API and metrics. Useful, beautiful, and shareable. Get a comprehensive view of data and ML model quality to explore and debug. Takes a minute to start. Test before you ship, validate in production and run checks at every model update. Skip the manual setup by generating test conditions from a reference dataset. Monitor every aspect of your data, models, and test results. Proactively catch and resolve production model issues, ensure optimal performance, and continuously improve it.

Langtail is an end-to-end platform that accelerates the development and deployment of language model (LLM) applications. It enables companies to rapidly experiment, collaborate, and launch production-grade LLM products. Key features include: 1. No-code LLM playground for prompt debugging and ideation 2. Collaborative workspaces for sharing prompts and insights 3. Comprehensive observability suite with logging and analytics 4. Evaluation framework for systematically testing prompt performance 5. Deployment infrastructure for serving prompts via API in multiple environments 6. Upcoming fine-tuning capabilities to improve models with user feedback Langtail empowers both technical and non-technical teams to find high-value LLM use cases, refine prompts for reliable performance, and deploy applications with ease. It's the all-in-one platform to take your LLM projects from prototype to production faster than ever.

PostgresML is a complete platform in a PostgreSQL extension. Build simpler, faster, and more scalable models right inside your database. Explore the SDK and test open source models in our hosted database. Combine and automate the entire workflow from embedding generation to indexing and querying for the simplest (and fastest) knowledge-based chatbot implementation. Leverage multiple types of natural language processing and machine learning models such as vector search and personalization with embeddings to improve search results. Leverage your data with time series forecasting to garner key business insights. Build statistical and predictive models with the full power of SQL and dozens of regression algorithms. Return results and detect fraud faster with ML at the database layer. PostgresML abstracts the data management overhead from the ML/AI lifecycle by enabling users to run ML/LLM models directly on a Postgres database.

RagaAI is the #1 AI testing platform that helps enterprises mitigate AI risks and make their models secure and reliable. Reduce AI risk exposure across cloud or edge deployments and optimize MLOps costs with intelligent recommendations. A foundation model specifically designed to revolutionize AI testing. Easily identify the next steps to fix dataset and model issues. The AI-testing methods used by most today increase the time commitment and reduce productivity while building models. Also, they leave unforeseen risks, so they perform poorly post-deployment and thus waste both time and money for the business. We have built an end-to-end AI testing platform that helps enterprises drastically improve their AI development pipeline and prevent inefficiencies and risks post-deployment. 300+ tests to identify and fix every model, data, and operational issue, and accelerate AI development with comprehensive testing.

Confident AI offers an open-source package called DeepEval that enables engineers to evaluate or "unit test" their LLM applications' outputs. Confident AI is our commercial offering and it allows you to log and share evaluation results within your org, centralize your datasets used for evaluation, debug unsatisfactory evaluation results, and run evaluations in production throughout the lifetime of your LLM application. We offer 10+ default metrics for engineers to plug and use.

No one wants their AI to respond with out-of-date information to a customer. ‍Neum AI helps companies have accurate and up-to-date context in their AI applications. Use built-in connectors for data sources like Amazon S3 and Azure Blob Storage, vector stores like Pinecone and Weaviate to set up your data pipelines in minutes. Supercharge your data pipeline by transforming and embedding your data with built-in connectors for embedding models like OpenAI and Replicate, and serverless functions like Azure Functions and AWS Lambda. Leverage role-based access controls to make sure only the right people can access specific vectors. Bring your own embedding models, vector stores and sources. Ask us about how you can even run Neum AI in your own cloud.

With our low-code platform, you can easily create custom AI solutions that are tailored to your unique needs. Our system is flexible, allowing you to use a wide range of AI algorithms, including OpenAI and ChatGPT, with your own data and knowledge base. OmniMind is a SaaS that allows you to use your own information and data from various sources to search for answers using AI. With OmniMind, you can process data with no-code on AI rails. At OmniMind.ai, we believe in providing our users with a simple, user-friendly interface that makes building custom AI systems a breeze. Whether you're new to AI or an experienced developer, our platform is designed to help you achieve your goals quickly and easily.

Make AI a trusted part of your business. Build better, deploy faster, and audit easily with the flexibility of a cloud-native platform and the power to deploy anywhere. Easily import models and search cataloged models from across your organization. Save time by annotating data rapidly with model-in-the-loop hinting. Understand the full provenance of your data, models, workflows, and inferences. Deploy models where you need them, including for edge and IoT use cases. Getting valuable insights from your data is not just for data scientists. With Chariot’s low-code interface, meaningful collaboration can take place across teams. Train models rapidly using your organization's production data. Deploy models with one click and monitor models in production at scale.

The Saagie cloud data factory is a turnkey platform that lets you create and manage all your data & AI projects in a single interface, deployable in just a few clicks. Develop your use cases and test your AI models in a secure way with the Saagie data factory. Get your data and AI projects off the ground with a single interface and centralize your teams to make rapid progress. Whatever your maturity level, from your first data project to a data & AI-driven strategy, the Saagie platform is there for you. Simplify your workflows, boost your productivity, and make more informed decisions by unifying your work on a single platform. Transform your raw data into powerful insights by orchestrating your data pipelines. Get quick access to the information you need to make more informed decisions. Simplify the management and scalability of your data and AI infrastructure. Accelerate the time-to-production of your AI, machine learning, and deep learning models.

Bring LLM-powered features to production with tools for prompt engineering, semantic search, version control, quantitative testing, and performance monitoring. Compatible across all major LLM providers. Quickly develop an MVP by experimenting with different prompts, parameters, and even LLM providers to quickly arrive at the best configuration for your use case. Vellum acts as a low-latency, highly reliable proxy to LLM providers, allowing you to make version-controlled changes to your prompts – no code changes needed. Vellum collects model inputs, outputs, and user feedback. This data is used to build up valuable testing datasets that can be used to validate future changes before they go live. Dynamically include company-specific context in your prompts without managing your own semantic search infra.

Metal is your production-ready, fully-managed, ML retrieval platform. Use Metal to find meaning in your unstructured data with embeddings. Metal is a managed service that allows you to build AI products without the hassle of managing infrastructure. Integrations with OpenAI, CLIP, and more. Easily process & chunk your documents. Take advantage of our system in production. Easily plug into the MetalRetriever. Simple /search endpoint for running ANN queries. Get started with a free account. Metal API Keys to use our API & SDKs. With your API Key, you can use authenticate by populating the headers. Learn how to use our Typescript SDK to implement Metal into your application. Although we love TypeScript, you can of course utilize this library in JavaScript. Mechanism to fine-tune your spp programmatically. Indexed vector database of your embeddings. Resources that represent your specific ML use-case.

Semantic Kernel is a lightweight, open-source development kit that lets you easily build AI agents and integrate the latest AI models into your C#, Python, or Java codebase. It serves as an efficient middleware that enables rapid delivery of enterprise-grade solutions. Microsoft and other Fortune 500 companies are already leveraging Semantic Kernel because it’s flexible, modular, and observable. Backed with security-enhancing capabilities like telemetry support, hooks, and filters you’ll feel confident you’re delivering responsible AI solutions at scale. Version 1.0+ support across C#, Python, and Java means it’s reliable, and committed to nonbreaking changes. Any existing chat-based APIs are easily expanded to support additional modalities like voice and video. Semantic Kernel was designed to be future-proof, easily connecting your code to the latest AI models evolving with the technology as it advances.

Open source is the core of Flowise, and it will always be free for commercial and personal usage. Build LLMs apps easily with Flowise, an open source UI visual tool to build your customized LLM flow using LangchainJS, written in Node Typescript/Javascript. Open source MIT license, see your LLM apps running live, and manage custom component integrations. GitHub repo Q&A using conversational retrieval QA chain. Language translation using LLM chain with a chat prompt template and chat model. Conversational agent for a chat model which utilizes chat-specific prompts and buffer memory.

The entire process of building machine learning algorithms and predicting outcomes, packed in one single click. Not all data is built to be ready for ML, use the Data Dialog to seamlessly shape your dataset without wrangling your files. Share your prediction reports with your team or make them public. Allow anyone to start making predictions on your model. Bring dynamic ML predictions into your own app using our low-code API. Predict willingness to pay, score leads and much more in real-time. Obviously AI puts the world’s most cutting-edge algorithms in your hands, without compromising on performance. Forecast revenue, optimize supply chain, personalize marketing. You can now know what happens next. Add a CSV file OR integrate with your favorite data sources in minutes. Pick your prediction column from a dropdown, we'll auto build the AI. Beautifully visualize predicted results, top drivers and simulate "what-if" scenarios.

Import data in any format, including text or images from any source like documents, cloud or APIs and launch a ChatGPT-like interface based on your preferred large language model like GPT-4, FLAN and GPT-NeoX and answer user queries based on the imported data. A comprehensive list of sample questions across various departments in different industries that can be asked to an LLM connected to a company’s private data source through ZBrain. Seamless integration of ZBrain as a prompt-response service into your existing tools and products. Enhance your deployment experience with secure options like ZBrain Cloud or the flexibility to self-host on a private infrastructure. ZBrain Flow empowers you to create business logic without writing any code. The intuitive flow interface allows you to connect multiple large language models, prompt templates, and image and video models with extraction and parsing tools to build powerful and intelligent applications.

With our advanced planning engine, even the most complex user requests can be executed. Out-of-the-box automation, inside your product. So your users can ask your system to do awesome things using normal texts, things like "Please show me last month's sales and give me some recommendations". You can plug OpenCopilot into your product using our chat bubble, and no coding skills are required. Or you can use our SDKs to make your copilot truly blend in. You can also feed your copilot all sorts of data and it will be able to understand it and offer help to your users. You can self-host OpenCopilot on your website using a single make install command. All paid plans include personal support from the team. Your users can ask complex questions that require executing multiple actions in one go. The single platform to build, manage, and deploy your next AI-powered feature. You will get new features first, it's going to be super nice since we ship a lot.

Industry-leading developer platform to test and debug AI agents. We built the tools so you don't have to. Visually track events such as LLM calls, tools, and multi-agent interactions. Rewind and replay agent runs with point-in-time precision. Keep a full data trail of logs, errors, and prompt injection attacks from prototype to production. Native integrations with the top agent frameworks. Track, save, and monitor every token your agent sees. Manage and visualize agent spending with up-to-date price monitoring. Fine-tune specialized LLMs up to 25x cheaper on saved completions. Build your next agent with evals, observability, and replays. With just two lines of code, you can free yourself from the chains of the terminal and instead visualize your agents’ behavior in your AgentOps dashboard. After setting up AgentOps, each execution of your program is recorded as a session and the data is automatically recorded for you.

Build powerful enterprise-grade AI applications in minutes, without any coding on the Katonic generative AI platform. Boost the productivity of your employees and take your customer experience to the next level with the power of generative AI. Build AI-powered chatbots and digital assistants that can access and process information from documents or dynamic content refreshed automatically through pre-built connectors. Identify and extract essential information from unstructured text or surface insights in specialized domain areas without having to create any templates. Transform dense text into a personalized executive overview, capturing key points from financial reports, meeting transcriptions, and more. Build recommendation systems that can suggest products, services, or content to users based on their past behavior and preferences.

Braintrust is the enterprise-grade stack for building AI products. From evaluations, to prompt playground, to data management, we take uncertainty and tedium out of incorporating AI into your business. Compare multiple prompts, benchmarks, and respective input/output pairs between runs. Tinker ephemerally, or turn your draft into an experiment to evaluate over a large dataset. Leverage Braintrust in your continuous integration workflow so you can track progress on your main branch, and automatically compare new experiments to what’s live before you ship. Easily capture rated examples from staging & production, evaluate them, and incorporate them into “golden” datasets. Datasets reside in your cloud and are automatically versioned, so you can evolve them without the risk of breaking evaluations that depend on them.

We’ve included some common examples, but the list is far from exhaustive. Our solution engineering team will work with you to customize Kolena for your workflows and your business metrics. Aggregate metrics don't tell the full story — unexpected model behavior in production is the norm. Current testing processes are manual, error-prone, and unrepeatable. Models are evaluated on arbitrary statistical metrics that align imperfectly with product objectives. ‍ Tracking model improvement over time as the data evolves is difficult and techniques sufficient in a research environment don't meet the demands of production.

Guardrails are crucial in AI maintenance, LangWatch safeguards you and your business from exposing sensitive data, prompt injection and keeps your AI from going off the rails, avoiding unforeseen damage to your brand. Understanding the behaviour of both AI and users can be challenging for businesses with integrated AI. Ensure accurate and appropriate responses by constantly maintaining quality through oversight. LangWatch’s safety checks and guardrails prevent common AI issues including jailbreaking, exposing sensitive data, and off-topic conversations. Track conversion rates, output quality, user feedback and knowledge base gaps with real-time metrics — gain constant insights for continuous improvement. Powerful data evaluation allows you to evaluate new models and prompts, develop datasets for testing and run experimental simulations on tailored builds.

Get scores for factual accuracy, context retrieval quality, guideline adherence, tonality, and many more. You can’t improve what you can’t measure. UpTrain continuously monitors your application's performance on multiple evaluation criterions and alerts you in case of any regressions with automatic root cause analysis. UpTrain enables fast and robust experimentation across multiple prompts, model providers, and custom configurations, by calculating quantitative scores for direct comparison and optimal prompt selection. Hallucinations have plagued LLMs since their inception. By quantifying degree of hallucination and quality of retrieved context, UpTrain helps to detect responses with low factual accuracy and prevent them before serving to the end-users.

Tencent Cloud TI Platform is a one-stop machine learning service platform designed for AI engineers. It empowers AI development throughout the entire process from data preprocessing to model building, model training, model evaluation, and model service. Preconfigured with diverse algorithm components, it supports multiple algorithm frameworks to adapt to different AI use cases. Tencent Cloud TI Platform delivers a one-stop machine learning experience that covers a complete and closed-loop workflow from data preprocessing to model building, model training, and model evaluation. With Tencent Cloud TI Platform, even AI beginners can have their models constructed automatically, making it much easier to complete the entire training process. Tencent Cloud TI Platform's auto-tuning tool can also further enhance the efficiency of parameter tuning. Tencent Cloud TI Platform allows CPU/GPU resources to elastically respond to different computing power needs with flexible billing modes.

Build, evaluate, deploy, and refine custom natural language processing models. Empower your team to automate workflows without hiring an AI expert team and costly infra. Metatext simplifies the process of creating customized AI/NLP models, even without expertise in ML, data science, or MLOps. With just a few steps, automate complex workflows, and rely on intuitive UI and APIs to handle the heavy work. Enable AI into your team using a simple but intuitive UI, add your domain expertise, and let our APIs do all the heavy work. Get your custom AI trained and deployed automatically. Get the best from a set of deep learning algorithms. Test it using a Playground. Integrate our APIs with your existing systems, Google Spreadsheets, and other tools. Select the AI engine that best suits your use case. Each one offers a set of tools to assist creating datasets and fine-tuning models. Upload text data in various file formats and annotate labels using our built-in AI-assisted data labeling tool.

Train and serve large AI models at scale with a single command. Point to your S3 bucket and go. We handle the rest, orchestration, efficiency, node failures, and infrastructure. Simple and scalable. MosaicML enables you to easily train and deploy large AI models on your data, in your secure environment. Stay on the cutting edge with our latest recipes, techniques, and foundation models. Developed and rigorously tested by our research team. With a few simple steps, deploy inside your private cloud. Your data and models never leave your firewalls. Start in one cloud, and continue on another, without skipping a beat. Own the model that's trained on your own data. Introspect and better explain the model decisions. Filter the content and data based on your business needs. Seamlessly integrate with your existing data pipelines, experiment trackers, and other tools. We are fully interoperable, cloud-agnostic, and enterprise proved.

Utilize the efficiency of OpenAI’s GPT engine to build supervised large language models which are backed by your very own data. Enterprises looking to integrate AI into their current business can use Supervised to build scalable AI apps. Building your own LLM can be tough. That’s why we let you build and sell your own AI apps with Supervised. Supervised AI provides you an environment to build custom LLM & AI Apps that are powerful and scalable. Using our custom models and data sources, you can build high-accuracy AI at a fast pace. Businesses are utilizing AI in a very layman's way right now, where most of its potential is yet to unlock. At Supervised, we let you harness your data to build a completely new AI model from scratch. Build custom AI apps on data sources and models built by other developers.

Fireworks partners with the world's leading generative AI researchers to serve the best models, at the fastest speeds. Independently benchmarked to have the top speed of all inference providers. Use powerful models curated by Fireworks or our in-house trained multi-modal and function-calling models. Fireworks is the 2nd most used open-source model provider and also generates over 1M images/day. Our OpenAI-compatible API makes it easy to start building with Fireworks. Get dedicated deployments for your models to ensure uptime and speed. Fireworks is proudly compliant with HIPAA and SOC2 and offers secure VPC and VPN connectivity. Meet your needs with data privacy - own your data and your models. Serverless models are hosted by Fireworks, there's no need to configure hardware or deploy models. Fireworks.ai is a lightning-fast inference platform that helps you serve generative AI models.

Apply advanced coding and language models to a variety of use cases. Leverage large-scale, generative AI models with deep understandings of language and code to enable new reasoning and comprehension capabilities for building cutting-edge applications. Apply these coding and language models to a variety of use cases, such as writing assistance, code generation, and reasoning over data. Detect and mitigate harmful use with built-in responsible AI and access enterprise-grade Azure security. Gain access to generative models that have been pretrained with trillions of words. Apply them to new scenarios including language, code, reasoning, inferencing, and comprehension. Customize generative models with labeled data for your specific scenario using a simple REST API. Fine-tune your model's hyperparameters to increase accuracy of outputs. Use the few-shot learning capability to provide the API with examples and achieve more relevant results.

Build, run and manage AI models, and optimize decisions at scale across any cloud. IBM Watson Studio empowers you to operationalize AI anywhere as part of IBM Cloud Pak® for Data, the IBM data and AI platform. Unite teams, simplify AI lifecycle management and accelerate time to value with an open, flexible multicloud architecture. Automate AI lifecycles with ModelOps pipelines. Speed data science development with AutoAI. Prepare and build models visually and programmatically. Deploy and run models through one-click integration. Promote AI governance with fair, explainable AI. Drive better business outcomes by optimizing decisions. Use open source frameworks like PyTorch, TensorFlow and scikit-learn. Bring together the development tools including popular IDEs, Jupyter notebooks, JupterLab and CLIs — or languages such as Python, R and Scala. IBM Watson Studio helps you build and scale AI with trust and transparency by automating AI lifecycle management.

Compose, test, optimize, and deploy reliable prompts for the leading language models and AI platforms to supercharge your apps and workflows. PROMPTMETHEUS is an Integrated Development Environment (IDE) for LLM prompts, designed to help you automate workflows and augment products and services with the mighty capabilities of GPT and other cutting-edge AI models. With the advent of the transformer architecture, cutting-edge Language Models have reached parity with human capability in certain narrow cognitive tasks. But, to viably leverage their power, we have to ask the right questions. PROMPTMETHEUS provides a complete prompt engineering toolkit and adds composeability, traceability, and analytics to the prompt design process to assist you in discovering those questions.

Aicado is your go-to platform for no-code AI solutions. Select your preferred AI model, customize it to fit your needs, and seamlessly integrate it into your business. We’ve got the AI models to match. Test them out, explore the possibilities, and integrate them into your business, all for free. You can create limitless integrations with Aicado. Every model can be integrable and every integration can have different purposes and can connect with different domains. Easily swap faces in videos with high accuracy. Ideal for creating fun and creative edits. Simply speak or upload a voice recording. Simply type a few words describing the scene or object you have in mind, and the AI will take care of the rest, presenting you with a visual representation. Simply enter the text, and the AI will handle the rest, providing you with an audio version to listen to. You can even turn your blog into a podcast.

Powerful language models a click away. Join over 8,000 developers building the next wave of world-changing applications. Fine-tune and deploy GPT-J, GPT-NeoX, Codegen, and FLAN-T5. Multiple models, each with different capabilities and price points. GPT-J is the fastest model, while GPT-NeoX is the most powerful—and more are on the way. Use these models for classification, entity extraction, code generation, chatbots, content generation, summarization, paraphrasing, sentiment analysis, and much more. These models have been pre-trained on a vast amount of text from the open internet. Fine-tuning improves upon this for specific tasks by training on many more examples than can fit in a prompt, letting you achieve better results on a wide number of tasks.

Select a model from our open source collection, run the container and access the model API in your product. No matter if Image Recognition or Language Processing - all models are pre-trained and packaged in an easy-to-use API. Choose from a large selection of models that is always growing. We curate and fine-tune the best models from HuggingFace and Github. You can either host the model yourself very easily or get your personal endpoint and API-Key with one click. Cargoship is keeping up with the development of the AI space so you don’t have to. With the Cargoship Model Store you get a collection for every ML use case. On the website you can try them out in demos and get detailed guidance from what the model does to how to implement it. Whatever your level of expertise, we will pick you up and give you detailed instructions.

Empower your product with AI. Our platform offers a vast selection of pre-built models and a user-friendly no-code interface for custom models. Integrate AI seamlessly into your application and gain a competitive edge. Sentiment analysis, also known as opinion mining, is the process of extracting subjective information from text data, such as reviews, social media posts, or customer feedback, and categorizing it as positive, negative, or neutral. This technology has gained increasing importance in recent years, as more and more companies are using it to understand their customers' opinions and needs, and to make data-driven decisions that can improve their products, services, and marketing strategies. Sentiment analysis is a powerful technology that helps companies understand customer feedback and make data-driven decisions to improve their products, services, and marketing strategies.

Unstructured data is the future of AI. Unlock this future now and build an ML/AI pipeline that scales all of your unstructured data in one place. Use better data to deliver better models, only with Graviti. Get to know the data platform that enables AI developers with management, query, and version control features that are designed for unstructured data. Quality data is no longer a pricey dream. Manage your metadata, annotation, and predictions in one place. Customize filters and visualize filtering results to get you straight to the data that best match your needs. Utilize a Git-like structure to manage data versions and collaborate with your teammates. Role-based access control and visualization of version differences allows your team to work together safely and flexibly. Automate your data pipeline with Graviti’s built-in marketplace and workflow builder. Level-up to fast model iterations with no more grinding.